Mrs Sandrine Ruffel

Mr Christian

Mr Claude Maranges

Mrs Fabienne Vailleau

Mrs Dominique Pantalacci

Mrs Ariel Rossi

Mrs Catherine

Mr José

Manuel Estevez
email: jestevez@leloir.org.ar

Mr Philippe Ranocha

Mr Hervé Canut

Mr David Roujol

Mrs Josiane Chourre

Ali Eljebbawi

Christophe Dunand
email: dunand@lrsv.ups-tlse.fr

Variation of gene expression in response to abiotic stress in Arabidopsis thaliana Pyrenean populations

Keywords: Abiotic stress, Arabidopsis thaliana populations, RNA-seq, root development, ROS

their interaction on the bench. I would like to thank every person in my laboratory, the "LRSV". Thanks to all the people from the administration and bioinformatics units. Thanks to all the people from the common-services unit for their valued work. Thanks to all the people from the TRI-GENOTOUL imaging facility. Thanks to all the working committees for their appreciated efforts in enhancing the research quality. Thanks to all the non-permanent employees who assisted my integration and shared many coffees and cakes. Thanks to all the research teams for their positive interaction throughout my journey.

Warm thanks to my fellow "lab mates", or I would say my "friends". Thanks to Sebastien for sharing the desk for 3 years and for all the fascinating conversations about science, humanity, and the entire existence. Thanks to Maxime for also sharing the desk and the bench and for all the laughter and activities. Thanks to Bastien for his kindness and essential humor during the stressful periods. And thanks to my

Résumé

Dans le contexte du changement climatique, les plantes seront confrontées à des contraintes environnementales de plus en plus récurrentes qui affecteront négativement leur productivité et leur survie. L'élévation et les brusques fluctuations de température exposeront les plantes à des stress thermiques critiques pour leur développement. De plus, les événements d'inondation associés à la montée du niveau de la mer augmenteront la salinité des sols ce qui perturbera les plantes sauvages et cultivées. Ainsi, une préoccupation majeure de la biologie végétale est de définir des stratégies pour faire face aux stress thermiques et salins afin de maintenir la biodiversité et la productivité agricole.

Dans ce cadre, l'acclimatation et l'adaptation des plantes aux stress abiotiques ont été massivement étudiées à différents niveaux et sous de multiples aspects. Parce que les plantes sont sessiles, elles ont une dispersion restreinte qui limitera leur migration vers des régions aux cadres climatiques plus favorables. Par conséquent, elles sont amenées à s'acclimater rapidement à de nouvelles conditions environnementales via leur plasticité phénotypique. À long terme, les plantes peuvent s'adapter à leurs microenvironnements locaux via la sélection naturelle qui améliore leur adaptation à leur niche écologique. Ce mécanisme est à la base de la diversité naturelle.

La diversité naturelle intra-espèces est un outil puissant pour étudier la réponse de la plante aux changements environnementaux. Arabidopsis thaliana a été adoptée comme espèce modèle pour de telles études. Dans ce travail, des populations naturelles d'A. thaliana provenant du versant Français des Pyrénées sont utilisées pour caractériser la plasticité phénotypique et transcriptomique en réponse aux stress thermiques et salins. L'intérêt particulier de ces populations provient de leur origine géographique restreinte mais présentant des climats très contrastés du fait de son caractère montagnard.

Plus spécifiquement, l'étude se concentre sur la plasticité au niveau des racines. Les racines représentent la moitié de la plante et jouent un rôle fondamental tout au long de son cycle de vie. En conséquence, les régulations moléculaires des espèces réactives de l'oxygène (ROS) au cours du développement racinaire ont été répertoriées. Aussi, le développement racinaire d'une trentaine de populations pyrénéennes d'A. thaliana, plus Columbia (Col-0, Pologne, 200 m) et Shahdara (Sha, Tadjikistan, 3400 m), a été phénotypé lors de combinaison de stress thermique et salin. Enfin, des analyses transcriptomiques ont été effectuées via un séquençage d'ARN. Elles mettent en évidence la régulation des gènes dans des populations pyrénéennes sélectionnées d'A. thaliana présentant des phénotypes tolérants au stress.

Les résultats obtenus ont révélé l'énorme plasticité phénotypique entre les populations étudiées en réponse aux contraintes de température -froid ou chaleur-et/ou salines. Les analyses intégratives des données phénotypiques ont mis en évidence des populations dont les racines sont peu ou fortement impactées par la contrainte abiotique. Elles ont donc été classées en populations tolérantes ou sensibles au stress.

De plus, les analyses transcriptomiques des populations tolérantes ont mis en lumière les variations de leur expression génique sous les contraintes appliquées, avec un accent particulier sur les gènes liés à la paroi cellulaire et à l'homéostasie des ROS, car ils sont fortement corrélés aux phénotypes observés. Les résultats ont montré que dans les populations tolérantes au stress, davantage de gènes codant pour la paroi cellulaire, la lignine et la biosynthèse des anthocyanes étaient régulés à la hausse. Le réseau de gènes ROS était aussi fortement impliqué dans la réponse des plantes à la contrainte environnementale. Par exemple, les populations tolérantes ont activé de nouveaux gènes tels que les peroxydases de classe III dans leur réponse d'acclimatation. [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. The 5 concentric tissues are: stele, endodermis (Endo), endodermis and cortex (Endo+cortex), epidermis (Epi), and lateral root cap (Lrc). The 3 developmental stages are in the meristematic zone (1), the elongation zone (2), and the differentiation zone (3) [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF] Tables Table 1: The phylogenetic classification of the model plant Arabidopsis thaliana .............................. 10

Table of Figures

Table 2:

The geographic localization of the studied Pyrenean A. thaliana populations and the climatic parameters of their collection sites calculated from the monthly data of the WorldClim project (annual minimum, mean, and maximum temperatures and annual precipitation). The annual UV radiation was obtained from the Photovoltaic Geographical Information System of the European Community. Climate PC1 values are the position of populations on the first principal component of the PCA of bioclimatic variables that allows to classify populations in function of their environmental conditions (Duruflé et al. 2019) Table 3: Heat-map summary of the expression of 44 class III peroxidases that were detected in any of the 5 different primary tissues (Stele, endodermis (Endo), endodermis and cortex (Endo + cortex), epidermis (Epi), or lateral root cap (Lrc) in at least 1 of the 3 root developmental zones.

The color code represents the magnitude of expression of all detected genes in each developmental zone increasingly in green, yellow, and red [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF] February 22, 2021) In this context, 196 parties of the "United Nations Framework Convention on Climate Change, UNFCCC", adopted "The Paris Agreement" on December 12, 2015. This agreement represents a legally binding international treaty on climate change. It aims at limiting global warming to well below 2 °C, preferably to 1.5 °C, compared to pre-industrial levels (https://unfccc.int/process-andmeetings/the-paris-agreement/the-paris-agreement; visited on February 22, 2021).

Also, "The Kyoto Protocol", adopted on December 11, 1997, operationalizes the UNFCCC by committing industrialized countries and economies in transition to limit and greenhouse gases "GHGs" emissions in accordance with agreed individual targets. Currently, 192 parties abide to this protocol (https://unfccc.int/kyoto_protocol; visited on February 22, 2021).

Henceforth, what is climate change, why it is a critical subject on the table, and which acts should be taken are intriguing questions to be answered by all disciplines starting from social science and going to the applied science.

The Context of Climate Change

In definition, climate change designates the occurring variations in the climate system, the atmosphere, the biogeochemical cycles (Carbon cycle, Nitrogen cycle and Hydrological cycle), the land surface, and the biotic and abiotic components of Earth [START_REF] Ahmed | Introduction to Modern Climate Change[END_REF]. In a historical narrative, the theme of climate change emerged in the early 19 th century, simultaneously with the First and Second Industrial Revolutions and the massive urbanization (Martinez 2017).

Associated with the dramatic increase of productivity, the atmospheric concentrations of greenhouse gases "GHGs" were concurrently enormously increasing. According to the records of the "United States Environmental Protection Agency" (EPA) the concentrations of carbon dioxide (CO2)

have increased by nearly 30%, concentrations of methane (CH4) have more than doubled, and nitrous oxide (NO2) concentrations have risen by about 15% since the industrial revolution. These

GHGs emitted from industrial factories and automobiles have been consecutively identified for their significant role in potentiating global warming (Martinez 2017).

By the late 1960s, the evidence to climate change became more vivid, upon observing alterations in the global atmospheric fashion in several major climates. A rapid global climate shift was recorded in tropical regions, the southern hemisphere, and the Atlantic sector of the northern hemisphere [START_REF] Baines | Evidence for a rapid global climate shift across the late 1960s[END_REF]. To exemplify, the drought in the Sahel of West Africa has been documented by the rainfall stations data sets, indicating a severely decreasing rainfall trend from the late 1950s to the late 1980s. This emerging condition led to drastic alterations in the vegetation cover, and other agricultural and societal aspects [START_REF] Dai | The recent Sahel drought is real[END_REF].

By the 1990s, climate change-related research widely expanded, and scientists from multiple disciplines associated together to decipher the challenges of climate change. Advocated by the increasing fidelity of computers and massive datasets, the interdisciplinary research was the basis to "Intergovernmental Panel on Climate Change" (IPCC) foundation in 1988. IPCC endorses the limitation of temperature increase at 1.5°C above preindustrial levels; further than that, global warming may turn into an existential threat to humankind.

Therefore, the mitigation strategies against climate change represent empirical procedures to reduce the existential posed risks. The conventional approach targets reducing fossil-based CO2

emissions by replacing the traditional fuels with renewable sources of energy. Another strategy implements negative emissions technologies to capture, sequester, and reutilize CO2 from the atmosphere. These currently available mitigation routes, in addition to other evolving routes, are inevitable in the international act against climate change (Fawzy et al. 2020).

The Manifestations of Climate Change 1.1.3.1 Global Warming

The primary aspect of climate change is global warming which is defined as the occurring increase of the Earth's surface average temperature related to the increase in the concentrations GHGs.

Although GHGs are naturally occurring and are essential for the planet's well-being, however, their abrupt elevations due to anthropogenic activities caused this tragic phenomenon. With higher levels of GHGs, the heat retention mechanism is boosted where more short-wave infrared radiations are absorbed and retained in the atmosphere instead of their discharge to the outer space, leading to the excessive heating of Earth (Al-Ghussain 2019).

In fact, the "NASA Goddard Institute for Space Studies (GISS) and a joint effort of the "UK Met Office

Hadley Centre and the University of East Anglia Climatic Research Unit (HadCRUT) routinely carry the observations and analyses of the global surface temperature. Benefitting from input data of different meteorological stations, both show temperature anomalies in almost all regions of the globe where the mean global temperature has increased for up to 0.8-2 °C in the past half-century [START_REF] Hansen | Global surface temperature change[END_REF]) (Figure 1). This rising situation poses drastic and radical threats on sustainable livelihood by increasing health risks [START_REF] Parry | The (in) visible health risks of climate change[END_REF], overloading the world's economy [START_REF] Diaz | Quantifying the economic risks of climate change[END_REF], and degrading natural environments and ecosystems structures and functions [START_REF] Satta | Assessment of coastal risks to climate change related impacts at the regional scale: The case of the Mediterranean region[END_REF]. In our scope of plant science, global warming is a critical issue to be addressed as it drives detrimental impacts on natural environments, biodiversity, and agriculture.

For instances, the warming of oceans and the melting of ice is constitutively rising sea levels, which endangers the habitat-forming species as coral reefs and mangroves in the coastal ecosystems [START_REF] Grimm | The impacts of climate change on ecosystem structure and function[END_REF]. Also, it is imposing biome shifts by shifting the distribution of plant species (Figure 2). A biome is an integration among climatic variables such as temperature and rainfall, vegetation structures like forests or heathlands, or dominance of key plant lineages (e.g. conifers in forests or grasses in savannas) [START_REF] Donoghue | Biome shifts and niche evolution in plants[END_REF]. Trees are increasingly growing in forests at or near latitudinal and altitudinal tree lines, and they are moving into adjacent tundra. It is known that species shifts occur where the climate-change velocity is high. This velocity represents the rate at which an area of constant temperature moves across the Earth. In the USA, species shifts velocities of up to 20 km per year were observed from 1960 to 2009, as compared with velocities of 0.002 km per year from the last glacial maximum 21000 years ago [START_REF] Burrows | The pace of shifting climate in marine and terrestrial ecosystems[END_REF]. Consequently, the spatial analyses performed by vegetation models predict that 15% to 35% of the US ecosystems are exposed to biome shifts, and by the year 2100, biome shifts driven by climate change will occur in 5% to 20% of USA land. These shifts that endanger many species with significant ecological services will reduce the existing biodiversity and manipulate the occurrence and extents of wildfires, leading to ecosystems' degradation [START_REF] Gonzalez | Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change[END_REF].

Furthermore, global warming causes not only biome but also phenological shifts of plant species.

These changes can be in different forms such as rescheduling the switch between the vegetative and reproductive phases in the plants' life cycles, mishandling their inter-and intra-species variations, and altering their timing of growth and senescence. These phenological shifts disrupt the concerted flowering of plants which is the key for their reproduction and consequently their existence; they also hinder the coexistence in the diverse plant communities by messing the delicate balance of plant-plant interactions such as competition for pollinators and nutrients; they as well disorder the annual carbon cycles on land which threatens the sustainability of natural resources [START_REF] Cleland | Shifting plant phenology in response to global change[END_REF]). Altogether, these deleterious outcomes of global warming distress the environment and necessitate goal-oriented and sustainable interventions to save our living niches.

Cold and Salinization

Where global warming is the most prevalent showcase of climate change, unseasonal cold also stands as a rising threat due to the alterations in the weather fashion. As snow has been always known for its ecological importance although it reduces the growing season, however, it protects plants from exposure to cold and desiccating winds. During winter, cold-adapted plant species rely on snow, particularly on the moist and stable conditions created at the land-snow interface [START_REF] Pauli | The subnivium: a deteriorating seasonal refugium[END_REF].

Even if climate change is expected to prolongate the growing seasons in cold environments, it may as well intensify the exposure to extremely cold microclimates by reducing the snow depth and duration. This reduction of snow can trick plant species to exit their winter hibernation earlier, which will make them experience colder conditions [START_REF] Kearney | How will snow alter exposure of organisms to cold stress under climate warming?[END_REF]. This fluctuation of the temperature fashion that plants encounter will put them under stressing environmental conditions that deleteriously affect their growth, development, reproduction, and consequently their existence.

Also, more freezing events, without any preceding chilling period, associated to sudden elevations of temperatures, will be critical to plant development [START_REF] Thakur | Cold stress effects on reproductive development in grain crops: an overview[END_REF].

Moreover, salinization is a mounting problem in the context of climate change. The sea level rise and the increased water salinity from saltwater intrusions challenge about 600 million persons populating coastal zones. The sea level rise is expected to reach 1 m by the year 2100, and this elevation is not expected to stop soon even if GHGs have been immediately reduced [START_REF] Church | Sea-level rise by 2100[END_REF]. Accordingly, the elevated salinity of soils and fresh waters by sea water intrusions threats the livelihoods and public health of millions of people due to its impacts on agriculture, aquaculture, and coastal ecosystems. For example, Bangladesh is one of the most threatened countries by climate change driven salinization. It has 30% of its the cultivated land in coastal areas, where salinity is boosting by the tidal floods of the wet season and the movement of saline ground water during the dry season [START_REF] Dasgupta | Climate change, soil salinity, and the economics of high-yield rice production in coastal Bangladesh[END_REF]. Similarly, the "Food and Agriculture Organization" (FAO) of the United Nations have reported tens of millions of hectares of salinized soils from all over the globe.

Climate Change and Agriculture

The innovation of agriculture is recognized as a remarkable plot twist in the human history. In the Neolithic era, the first agricultural revolution had begun originally in the Fertile Crescent which spans the modern southwest of Iran, Iraq, Syria, South Turkey, Lebanon , Jordan, Palestine, and Egypt.

This innovation dramatically altered the nomadic lifestyles of the hunters and gatherers in the prehistory and Paleolithic era, into a permanent settling lifestyle. Eventually, with the evolving grain agriculture and the vital need of labor division, farming and the domestication of species furnished the world into the foundation of the sedentary human civilization [START_REF] Tudge | Neanderthals, bandits and farmers: how agriculture really began[END_REF].

Presently, agriculture is the basis that ensures global food security and production such as cereals, fruits, vegetables, and oils. Thirty crops provide 90% of our food either directly or as livestock to animals. Agriculture contributes as well to the industry by producing fuels and raw materials as fibers and rubber. Also, it employs about one third of the global population, even though this number is decreasing due to the prevalence of big industry and mechanization [START_REF] Pawlak | The role of agriculture in ensuring food security in developing countries: Considerations in the context of the problem of sustainable food production[END_REF].

Unfortunately, agriculture is currently facing serious threats by the plausible scenarios of climate change. The increase of temperatures by 0.2 °C to 0.4 °C per decade with higher warming in high latitudes, the changes in precipitation by the poleward advance of monsoon rainfall, the increase of drought-prone regions by the reduction of water availability, in addition to many other circumstances will have drastic impacts on agricultural productivity and sustainability [START_REF] Parry | Climate change and world agriculture[END_REF].

This concern about the potential effects of long-term climatic change on agriculture has motivated a substantial body of research over the past decades.

In fact, crops are prone to various environmental factors that interact either synergistically or antagonistically in determining their yield. Elevated temperatures and drought stress reduce crops yields by decreasing their harvest index, shortening their life cycles, and altering their seed number, size, and composition [START_REF] Cohen | Meta-analysis of drought and heat stress combination impact on crop yield and yield components[END_REF]. Additionally, the aberrant climate has been shown to intensify the pest occurrences, change their virulence patterns, and facilitate the emergence of pathogens in new areas, which may result in 40% loss in yield in south Asia by the year 2100 [START_REF] Pathak | Impact of climate change on host, pathogen and plant disease adaptation regime: a review[END_REF]. Moreover, the production of cereal grains as wheat and maize are inferred to be reduced by different predictive models, although their production must be doubled by the year 2050 to match the needs of the growing population [START_REF] Wang | Effect of climate change on the yield of cereal crops: a review[END_REF]. Likewise, yield is reduced if soil salinity surpasses crop-specific thresholds leading to salt toxicity, and hence inhibiting biochemical physiological and metabolic processes that contribute to the yield [START_REF] Zörb | Salinity and crop yield[END_REF]).

Climate Change and Plant Science

Altogether, these distressing indicators alarm researchers, governments, and public opinion about the vital need to act immediately against climate change. As for researchers, their primary objective is to first understand the occurring status of the climate and predict its future, to elucidate its impacts on the environment, ecosystems, plants, and agriculture, and come up with effective and sustainable solutions. Additionally, due to the massive impacts on the environment, ecosystems, biodiversity, and agriculture, plant science research in turn must contribute to the global act against climate change. For this aim, a magnitude of studies has highlighted different aspects of how the changing climate impacts all members of the plant kingdom, from the first evolving modern algae to the latest angiosperms, in terms of their growth, physiology, reproduction, diversity, habitats, agriculture, microbial interactions, and disease resistance.

Plant science, which is the core of understanding the biology of plants, their multileveled interactions with their environments, and their acclimations and adaptations to abiotic and biotic stresses is essential to survive. Accordingly, plant biologists achieved deep knowledge of how plants evolve, grow, develop, and reproduce. They unraveled the relationships of these sessile organisms with various signals from their living niche. They also deciphered how plants respond and choreograph their existence and lifestyles in accordance with the surrounding conditions. Yet, lots remain to be discovered in these interdisciplinary scopes to decipher the present and future components of both the climate system and plants and the interaction among them.

The Plant

Preface

In the framework of examining the plant kingdom "Plantae", phylogenomic studies have improved our understanding of the evolution and diversification of these organisms. The story began with the Greek philosopher Aristotle who divided all living beings into either plants or animals based on their mobility. Later on, the Swedish botanist Carl Linnaeus, the father of the modern taxonomy, classified every non-animal creature into the Plantae kingdom, including disparate fungi and algae [START_REF] Eddy | Tools for reordering: commonplacing and the space of words in Linnaeus's Philosophia Botanica[END_REF].

Presently, the notion of Plantae follows a funnel spectrum, with the broadest definition of Linnaeus, successively narrowed into the Archaeplastida comprising the red algae "Rhodophyta" and the glaucophyte algae "Glaucophyta" in addition to the green plants (Cavalier-Smith 1981), the Virdiplantae holding only green algae and the emerging land plants characterized by the presence of cellulosic cell wall, chlorophylls a and b, and plastids as sites for photosynthesis [START_REF] Copeland | The classification of lower organisms. The classification of lower organisms[END_REF], and finally the narrowest is the Embryophyta which includes land plants as liverworts, hornworts, mosses, and vascular plants [START_REF] Whittaker | New Concepts of Kingdoms of Organisms: Evolutionary relations are better represented by new classifications than by the traditional two kingdoms[END_REF].

Currently, the development of high-quality technologies such as the next generation sequencing to analyze genomes and transcriptomes together with the massive improvements in functional genomics and the available computational capacities facilitated a deeper and more precise understanding of the phylogeny. In the cadre of the "One Thousand Plant Transcriptomes Initiative", transcriptomes from 1124 plants of the Archaeplastida have been sequenced for a robust study of plant evolution [START_REF] Leebens-Mack | One thousand plant transcriptomes and the phylogenomics of green plants[END_REF].

Focusing on the most familiar Embryophyta, these plants exhibit novel innovations allowing their survival on land. Among these are their tolerance to desiccation, shifts in the dominance of multicellular haploid and diploid generations, and parental retention of multicellular embryos.

Furthermore, the vascular plants, Tracheophytes, innovated specialized conducting tissues to water, the xylem, and nutrients, the phloem, increasing their absorption efficiency and opening new opportunities of growth. Also, Spermatophytes, a sub clade of the Tracheophytes, have evolved a remarkable mechanism of seed production that increases their capacity to reproduce, spread, and overcome challenging conditions. Spermatophytes consist of the gymnosperms with naked seeds and the angiosperms that add protective layers to their embryo-carrying seeds, the fruits (Leebens-

Mack et al. 2019).

This fascinating diversity of plants and their associated innovations to react to their environments provide exceptionally precious tools and resources to respond to the growing challenges of climate change. Thoroughly understanding the natural mechanisms of adaptation that occur in plants, their origins, their goals, and their strategies is the key to unlock future perspectives to enhance plant's tolerance to environmental stresses. For instance, improving plants' resistance to pests and herbivores can be achieved by improving and amplifying their already existing defense mechanisms.

Also, in response to the climate change driven abiotic stresses such as heat, cold, and salinization, heat-, cold-, and salt-tolerant plants can be engineered based on the rich thesaurus of plants natural adaptations processes.

Arabidopsis thaliana: a Model Plant

Arabidopsis thaliana has been adopted as a model to study the physiology and molecular biology, and more recently, the ecology and evolution in Plantae. In 2015, 50 years of Arabidopsis research were celebrated [START_REF] Provart | 50 years of Arabidopsis research: highlights and future directions[END_REF]. In fact, the usefulness of this plant in experimentation is related to its important features. First, it has a small stature which facilitates its growing in large populations within limited laboratories' facilities. Second, it was well established by classical forward genetics during which random mutagenesis, followed by the identification of desired phenotypes, and then mapping the mutations to the phenotype were a very powerful routine. Additionally, A.

thaliana is practical in terms of crossing, short generation time, and high fecundity as it can produce up to 10000 seeds per plant via self-fertilization [START_REF] Provart | 50 years of Arabidopsis research: highlights and future directions[END_REF].

Its 135 mega base pairs relatively small nuclear genome was the first to be sequenced in the Plantae kingdom in 2001 [START_REF] Huala | The Arabidopsis Information Resource (TAIR): a comprehensive database and webbased information retrieval, analysis, and visualization system for a model plant[END_REF]. Following numerous technological outbreaks, many databases have been constructed encompassing the comprehensive knowledge of this plant, such as "The Arabidopsis Information Resource, TAIR" [START_REF] Lamesch | The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools[END_REF], "Arabidopsis Information Portal, Araport" [START_REF] Krishnakumar | Araport: the Arabidopsis information portal[END_REF], a public database for A. thaliana phenotypes "Arapheno" (Grimm et al. 2017), "Arabidopsis Hormone Database, AHD" (Jiang et al. 2011), and many others. Correspondingly, the 1001 Genomes Project was launched in 2008; this consortium aims at discovering detailed whole-genome sequence variation in at least 1001 geographically diverse accessions of A. thaliana, which highlights the massive intraspecies variations of this widely spread reference plant [START_REF] Cao | Whole-genome sequencing of multiple Arabidopsis thaliana populations[END_REF]. Altogether, these handy resources provide effective tools to investigate plant biology and its interaction with the environment.

Taxonomy

In his book "Sylva Hercynia", the German botanist Johann [START_REF] Khanna | Arabidopsis: two-hundredths anniversary of its name and the possibility of a hidden universal regulatory signal[END_REF]. The taxonomic classification of A. thaliana is depicted in table 1. A. thaliana is an annual plant profusely branched from the base and with a rather dense rosette that grows up to 25 cm tall. Its stem is erect and ascending and is moderately covered by stellate and simple hairs. Its rosette comprises spathulate, obtuse, attenuate, and indistinctly petiole leaves that are 0.5 cm to 4 cm long and 0.3 cm to 1.5 cm wide. Its cauline leaves are however few, sessile, elliptic, rather acute, and are 0.5 cm to 1.5 cm long and 0.2 cm to 1 cm wide. All leaves are covered with unicellular hairs named trichomes. A. thaliana develops a raceme corymbose inflorescence with up to 15 to 30 flowers, with green sepals in the calyx, white petals in the corolla, four long and two short stamens with rounded anthers in the androecium, and linear siliques as fruits. Its seeds are reddish brown in color, elliptic to ovate, 0.7 mm long, and 0.4 mm broad (Krämer 2015) (Figure 3).

It is worth noting that these organ shapes as well as the general architecture of A. thaliana are under the control of a huge consortium of genes [START_REF] Dinneny | NUBBIN and JAGGED define stamen and carpel shape in Arabidopsis[END_REF]. Similarly, several genes were depicted for their roles in determining the leaf shape by controlling their expansion (Tsukaya 2005).

Furthermore, variations in seed morphology were observed among different accessions of A.

thaliana owing to the underlying genetic control of this trait and the intra-species polymorphism of these genes [START_REF] Robert | Morphological analysis of seed shape in Arabidopsis thaliana reveals altered polarity in mutants of the ethylene signaling pathway[END_REF]. In fact, the wide distribution of this species around the world fired a huge evolutionary divergence where different accessions of Arabidopsis evolved different traits to accommodate with their diverse local environments. This phenomenon is to be further detailed.

Geographical Distribution

A. thaliana is popularly described as native to the Eurasian landmass to which its centers of origin have been attributed (Hoffmann 2002). It has been further introduced and naturalized in north America and Australia [START_REF] Exposito-Alonso | The rate and potential relevance of new mutations in a colonizing plant lineage[END_REF][START_REF] Koornneef | Naturally occurring genetic variation in Arabidopsis thaliana[END_REF]). It has been observed to be a colonizer and pioneer plant in poor and disturbed stony and shallow soils, and it can be also found in nutrient-poor sandy, meadow, and forest habitats [START_REF] Krämer | The natural history of model organisms: Planting molecular functions in an ecological context with Arabidopsis thaliana[END_REF]. Upon investigating its prehistoric distribution via population genetic data, it has been proposed that this species recolonized Europe from post-glacial refugia, although contradicting scenarios have been predicted

based on linkage disequilibrium studies. Further analyses of huge data sets of genetic variations suggest that it has a complex population structure [START_REF] François | Demographic history of European populations of Arabidopsis thaliana[END_REF]. Accordingly, the centers of origin of A. thaliana and how and when it spread are still debatable.

Moreover, the main factor of determining a species range is the climate. This phenomenon has been attributed to many local observations of plants that have revealed their rapid responses to temporary climatic fluctuations as well as to durable climatic trends. In fact, the geographical distribution map of A. thaliana has been established, where its highest frequency has been obtained in central, western, and northern Europe, and the Atlantic states of north America indicating its contiguous distribution (Figure 4). As for its altitudinal distribution, it inhabits a gradient starting from the sea level up to 2000 m in the European central Alps and to 2500 m in the North African

Atlas Mountains. This range increases towards the east, where it occurs between 800 m and 3000 m in the Tien Shan (Hoffmann 2002). In response to such a broad altitudinal distribution, A. thaliana must survive varying environmental conditions such as vast differences in temperature, humidity, UV radiations, and atmospheric pressure. The local adaptations of these plants to the changing climatic factors require tight regulations of their physiological processes and efficient modifications of their phenotypes. Such accumulative adaptations that occur over an evolutionary scale are the basis of the intraspecific natural variation, the within-species genetic and phenotypic variations (Duruflé et al. 2019). In this context, many foundations have been initiated to decipher the vast intra-species variations in Arabidopsis such as the 1001 Genomes Project [START_REF] Cao | Whole-genome sequencing of multiple Arabidopsis thaliana populations[END_REF]. Furthermore, the molecular mechanisms underlying these adaptations have been extensively studied at multiple levels, genomic, transcriptomic, proteomic, metabolomic, and phenotypic. The screening approaches rely on analyzing key functional traits such as growth, stress resistance, defense, and reproduction [START_REF] Vasseur | Climate as a driver of adaptive variations in ecological strategies in Arabidopsis thaliana[END_REF]).

Intraspecific Natural Diversity

The selective forces of evolution are derived from the different ecological conditions that the species experience. They trigger genetic variations in natural populations as a direct consequence of their adaptation to their local environments. These genetic variations promote phenotypic plasticity which provides the plants with adaptational traits (Figure 5). Consequently, the advantageous traits will be naturally selected and preserved into next generations in accordance with the experienced conditions (Ferrero-Serrano and Assmann 2019). The importance of phenotypic plasticity is magnified in plants due to their sessile lifestyle. To illustrate, it is true that climate change can drive plant migration but at an evolutionary long-term scale; however, at short and intermediate terms, plants, being unable to move, must cope with their surrounding conditions to be able to survive (Ferrero-Serrano and Assmann 2019).

For instance, among the most remarkable adaptive phenotypes in Arabidopsis is the adjustment of their life cycles, the seasonal timing of development spanning from seed-to-seed. This trait is regulated by the interaction between intrinsic genetic and extrinsic environmental factors that influence the seed dormancy and flowering time, which mark the beginning and the end of the cycle, respectively [START_REF] Marcer | Results of 50 years of climate reanalysis in the French Pyrenees (1958-2008) using the SAFRAN and CROCUS models[END_REF]). These two latter phenomena are prominently affected by two external factors, which are the photoperiod and the temperature.

In fact, two distinct life cycles have been distinguished in A. thaliana, resembled by the winter annuals and the summer annuals. The winter annuals germinate in the fall, overwinter as a rosette, and flower in the spring. Their flowering is induced by vernalization, their exposure to prolonged winter cold. Whereas, the summer annuals germinate and flower rapidly in the same season owing to the long-day photoperiod, which may allow two cycles in one season [START_REF] Burghardt | Modeling the influence of genetic and environmental variation on the expression of plant life cycles across landscapes[END_REF]. It is notable that each of the developmental stages has a distinct environmental tolerance, where the plant, as a part of its adaptation, synchronize its life cycle in accordance to its tolerance threshold [START_REF] Vidigal | Altitudinal and climatic associations of seed dormancy and flowering traits evidence adaptation of annual life cycle timing in Arabidopsis thaliana[END_REF]. Additionally, analyzing natural variation within a species is a useful method to unravel the genetic architecture underlying its adaptive phenology. In this context, A. thaliana has a privileged position owing to its broad geographical distribution and hence its exposure to a wide spectrum of climatic conditions leading to massive evolutionary divergence. It also possesses the most complete set of resources for basic research to study its development, physiology, and adaptations to fluctuating environments (Alonso-Blanco et al. 2009). In the past years, numerous studies have been conducted in this sense. To exemplify, genome-wide associated studies (GWAS) have been performed to link interesting observed phenotypes with genetic variants. The AraGWAS Catalog is a newly developed repository for these studies which provides an overview about top associated markers across all the phenotypes available in AraPheno [START_REF] Togninalli | The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog[END_REF]).

The Mountainous Terrains: Hotspots for Natural Diversity

Mountains are noted for their important role as cradles of biodiversity, and they hence represent hotspots to study natural diversity. They are great repertoires characterized by environmental gradients of climatic conditions along their altitudinal gradients [START_REF] Chakraborty | Mountains as a global heritage: arguments for conserving the natural diversity of mountain regions[END_REF]. In mountains, plants are exposed to a myriad of abiotic stresses such as elevated UV radiations accompanied by augmented light intensities, extreme temperatures, and reductions in the vegetative seasons.

Accordingly, the ecological plant distribution follows an altitudinal zonation pattern due to the alterations in temperature, precipitation, and luminosity with altitude [START_REF] Körner | The use of 'altitude'in ecological research[END_REF].

Moreover, the mountainous climatic gradient triggers phenotypic modifications in ecotypes of the same species. The triggered phenotypic plasticity allows these ecotypes to adapt to their highly changing microenvironment (Duruflé et al. 2019). Therefore, individuals of the same species may show important morphological differences in response to the different climatic conditions. For instances, the genus Camelina shows intra-and inter-specific variation in the cuticle as an adaptational response to drought stress [START_REF] Tomasi | Characterization of leaf cuticular waxes and cutin monomers of Camelina sativa and closely-related Camelina species[END_REF]. Also, Setaria viridis shows physiological and phenological plasticity when subjected to water stress and temperature allowing to distinguish tolerant and sensitive accessions to these stresses [START_REF] Saha | Spike-dip transformation of Setaria viridis[END_REF]. These findings open up new promising pathways in evolutionary biology and systems biology, thanks to the natural variation.

To sum up, plants are constantly exposed to a broad spectrum of fluctuating environmental conditions, which drive intraspecific diversity via genetic variations leading to phenotypic plasticity.

To cope with their continuously changing environments, they have developed multiple adaptational mechanisms against abiotic stresses, such as heat, cold, and salinization. These stress-mitigation strategies are constituted by complex interconnecting networks involving various molecular players.

How plants perceive, transduce, and respond to these environmental signals is one great interest in biology.

1.3 The Plant and the Environment

The Plant and Abiotic Stresses

As plants are under continuous exposure to a wide range of abiotic stresses, they may suffer from growth limitations that hinder their development, productivity, and well-being. Consequently, they face these limitations in complex and integrated ways involving changes at whole plant, tissue, cellular, physiological, and molecular levels (Cramer et al. 2011). If successful, the plant's integrative responses against the abiotic constraints lead to tolerance; however, the plant may fail to adapt to the changing environment and hence be susceptible to the new conditions (Ciarmiello et al. 2011).

Moreover, tolerance or susceptibility are indeed complex traits that are determined by various parameters such as the stress intensity and duration, the co-occurrence of multiple stresses, and the plant's status itself.

The first step of the plant-environment interaction is the perception of the extrinsic signals and their incorporation into intrinsic signaling pathways within the plant. These stimulated signals are then processed and translated into adaptive responses against the abiotic constraint [START_REF] Lamers | How plants sense and respond to stressful environments[END_REF].

The adaptive mechanisms involve multiple components such as signals, sensors, or effectors which are organized into integrative networks at cellular and molecular levels [START_REF] Jeandroz | Plant responses to biotic and abiotic stresses: lessons from cell signaling[END_REF].

For instance, reactive oxygen species (ROS) have been well-documented as key players in stress signaling (Saini et al. 2018;Sewelam et al. 2016). In fact, ROS were formerly known as toxic byproducts of the aerobic metabolism; however, they have been characterized for their important roles in stress signaling. ROS in collaboration with other actors regulate several biological processes of the plant's adaptative response to abiotic constraints (Baxter et al. 2014;Miller et al. 2010).

Under environmental stress, ROS levels rise dramatically leading to oxidative burst that triggers downstream signaling, physiological responses, or programmed cell death. Indeed, ROS levels are maintained below the cytotoxicity threshold via ROS scavenging machineries to prevent cellular damage (Saini et al. 2018).

Furthermore, the transcriptional regulation represents an important feature of the plant's response to abiotic stresses [START_REF] Rasmussen | Transcriptome responses to combinations of stresses in Arabidopsis[END_REF]. Under stressful conditions, plants modify their cellular metabolism by changing the expression patterns of the genes [START_REF] Rajappa | Regulation of AtKUP2 expression by bHLH and WRKY transcription factors helps to confer increased salt tolerance to Arabidopsis thaliana plants[END_REF]. For instance, under temperature or drought stresses, the upregulation in the expression of a myriad of stressresponsive genes has been reported (Ohama et al. 2017).

In short, when plants encounter adverse abiotic stresses, they are capable of perceiving these signals and translating them downstream into physiological responses. Regulations in the gene expression are at the basis of such mechanisms where stress-responsive genes are activated to trigger an adaptational revolution within the plant. It is hence highly important to study the alterations in the plant transcriptome, which will lead to further insights into how abiotic stress affects plant physiology [START_REF] Hazen | Gene expression profiling of plant responses to abiotic stress[END_REF]). (Hassan et al. 2021).

Primarily, HS delays seed germination by disrupting the activity of the starch hydrolyzing enzyme αamylase and abscisic acid (ABA) catabolism via DNA methylation of their genes promoters leading to their transcriptional downregulation, and via the impair of the protein expression profiles and the mitochondrial functions in embryos [START_REF] Suriyasak | Mechanism of delayed seed germination caused by high temperature during grain filling in rice (Oryza sativa L.)[END_REF]. Also, HS reduces the growth duration and shortens the life cycle leading to decreased grain filling, improper stand establishment, and lower biomass and yields in many species. It also has severe manifestations on leaf development such as rolling, drying, hyponasty, necrosis, and senescence and on tillers formation (Akter and Rafiqul Islam 2017).

During the reproductive phase, HS has superior detrimental effects. First, it obstructs proper microsporogenesis and megasporogenesis which demolishes antheral dehiscence and pollen fertility and hence leads to insufficient pollen depositions on stigmas. Also, the HS-enhanced ethylene production can lead to male sterility. Plus, it may cause tapetal degradation and hampered fertilities of the gametophytes [START_REF] Wu | Enclosed stigma contributes to higher spikelet fertility for rice (Oryza sativa L.) subjected to heat stress[END_REF]. Moreover, extreme HS may induce programmed cell death (PCD) due to protein denaturation leading to leaf shedding, flower and fruit abortion, and eventually plant death [START_REF] Locato | Programmed cell death in plants: an overview[END_REF].

In addition, HS impedes the plant-water relationships by increasing the stomatal evapotranspiration in leaves while decreasing the water uptake from roots. Simultaneously, HS-driven stomatal closure negatively influences photosynthesis by decreasing CO2 uptake. Accordingly, the solubilities of O2 and CO2 are altered, which leads to disruption the balance of RUBISCO's carboxylase versus oxygenase activities and favoring cellular respiration causing additional C losses that limit ATP production (Hassan et al. 2021). Also, photosynthesis is hindered due to the associated injuring of several enzymes catalyzing the carbon metabolism in the chloroplastic stroma and thylakoids, disorganizing the chloroplastic structures, and declining photosystems activities [START_REF] Allakhverdiev | Heat stress: an overview of molecular responses in photosynthesis[END_REF]. Consequently, the osmotic adjustment countering HS via solutes production (e.g. glucose)

becomes incompetent due to the leaf-senescence driven reduction in photosynthesis, the amplified fluidity in membrane lipids, and ROS production [START_REF] Fahad | Crop production under drought and heat stress: plant responses and management options[END_REF].

Similarly, plant-nutrient relationships have been shown to be disturbed by HS, although fewer studies focus on their impacts on roots, the nutrients absorbing organs, rather than shoots.

However, it has been shown that HS decreases nutrient content by limiting the absorption capacity of roots due to their reduced biomass and smaller hair surfaces as well as by damaging enzymes involved in nutrients assimilation [START_REF] Giri | Heat stress decreases levels of nutrientuptake and-assimilation proteins in tomato roots[END_REF]. HS can further cause disparities in nutrients partitioning such as carbon (C) and nitrogen (N) which can impact starch and protein metabolism, and it can mess the translocation of soluble carbohydrates from the stem to the grains thus decreasing the fecundity [START_REF] Ram | Stem reserve mobilization in relation to yield under different drought and high temperature stress conditions in wheat (Triticum aestivum L) genotypes[END_REF]. Last but not least, HS provokes accumulation of ROS which damage many biomolecules such as proteins, lipids, and pigments leading to serious injuries and may lead to PCD (Eljebbawi et al. 2021).

The Plant Response to Heat Stress

In response to these brutalities, plants cope with HS via short-and long-term strategies. At the shortterm, plants adopt acclimation and heat avoidance. These mechanisms include increasing the stomatal transpiration to cool down the plant and rolling of leaves to reduce the exposure to sunlight [START_REF] Nadeem | Unraveling field crops sensitivity to heat stress: Mechanisms, approaches, and future prospects[END_REF]. At long term, natural selection forces evolutionary adaptations in plants against HS leading to phenotypic modifications, which are dependent on the species and their corresponding genetic variants. Growing smaller leaves that disperse heat more efficiently, developing more trichomes and stomata per leaf, and acquiring additional lignification of xylem vessels in shoots and roots are among the manifestations of these evolutionary adaptations [START_REF] Zhao | Plant responses to heat stress: physiology, transcription, noncoding RNAs, and epigenetics[END_REF].

In A. thaliana, stress hormones such as abscisic acid (ABA) and ethylene play key roles in HS signal transduction and the consequent initiation of the plant's adaptive response. For instance, ABAdependent signals induce the antioxidant capacity against ROS toxicity, regulate the stomatal closure to reduce water loss, and upregulate the expression of Heat Shock Proteins (HSPs) which reestablish the regular conformations of denatured proteins under HS [START_REF] Islam | Role of abscisic acid in thermal acclimation of plants[END_REF]. In fact, a huge network of transcription factors (TFs) and other regulators controls HS-inducible genes expression throughout the HS response, where HEAT SHOCK TRANSCRIPTION FACTOR A1s (HsfA1s) play master roles, leading to the acquisition of thermotolerance via activating chaperones and other enzymes and of heat stress memory via epigenetic modifications (Ohama et al. 2017). Also, secondary metabolites such as flavonoids, anthocyanins, phenylpropanoids, and carotenoids contribute to the plants tolerance mechanisms under HS [START_REF] Ashraf | Environmental stress and secondary metabolites in plants: an overview[END_REF].

Therefore, HS induces a wide array of adaptive responses among different species and even within species natural variants, and at different levels such as morphology and physiology where all these manifolds contribute to enable the plant's survival and persistence. Hence, acquiring new insights about the manifestations of HS on plants is of high interest for selected adapted genotypes with enhanced heat tolerance. (COR15a) that mediate stabilizing the cellular structures and biomolecules as well as anti-freezing osmolytes and ice nucleators such as soluble sugars and glucose to lower the freezing point of tissues [START_REF] Janská | Cold stress and acclimation-what is important for metabolic adjustment?[END_REF]).

Furthermore, it has been well established that exposing plants to periods of chilling temperatures can rather enhance their chilling as well as freezing tolerance by creating a cold-tolerance memory, a process known as cold acclimation [START_REF] Baier | Preparing plants for improved cold tolerance by priming[END_REF]). Cold acclimation is a complex phenomenon involving multiple players such as hormones, osmolytes, and enzymes, and its underlying genetic regulatory networks have also been thoroughly analyzed where many cold-responsive genes have been identified. For instance, an ICE-CBF-COR pathway was identified where ICE, a MYC-type basic helix-loop-helix family transcription factor, is a CBF regulator (C-repeat binding factor) which, under cold stress conditions, induces several cold stress-related genes to regulate the cold tolerance of plants. To exemplify, CBFs control the expression of the COR genes which are responsible for chilling tolerance and cold acclimation processes in plants (Ritonga and Chen 2020).

To sum up, cold stress limits the plants well-being and contribute to major losses in agriculture.

Plants are naturally equipped with a magnitude of adaptive strategies that are manifested at interand intraspecies levels. Therefore, understanding how plants adapt to this stress and deciphering the underlying genetic regulatory networks of its perception, signaling, and response is highly important to improve the plant's tolerance. Moreover, several genes have been highlighted for their putative roles in enhancing salt tolerance in A. thaliana. Many TFs including basic leucine zipper (bZIP) [START_REF] Hartmann | Crosstalk between two bZIP signaling pathways orchestrates salt-induced metabolic reprogramming in Arabidopsis roots[END_REF], WRKY [START_REF] Rajappa | Regulation of AtKUP2 expression by bHLH and WRKY transcription factors helps to confer increased salt tolerance to Arabidopsis thaliana plants[END_REF], APETALA2/ ETHYLENE RESPONSE FACTOR (AP2/ERF) [START_REF] Xie | AP2/ERF transcription factor regulatory networks in hormone and abiotic stress responses in Arabidopsis[END_REF], MYB [START_REF] Li | The Arabidopsis MYB transcription factor, MYB111 modulates salt responses by regulating flavonoid biosynthesis[END_REF], and basic helix-loop-helix (bHLH) [START_REF] Verma | A bHLH transcription factor, MYC2, imparts salt intolerance by regulating proline biosynthesis in Arabidopsis[END_REF] have been reported to be differentially expressed under salt conditions, where the produced TF proteins lead the transcriptional regulation of the adaptive response against SS [START_REF] Deinlein | Plant salttolerance mechanisms[END_REF]. Furthermore, Na + /H + exchanger 1 (NHX1)

and SALT OVER SENSITIVE 1 (SOS1) encode the Na + /H + antiporters in the tonoplast and plasma membrane, respectively, that maintain low cytosolic Na + concentrations [START_REF] Julkowska | Tuning plant signaling and growth to survive salt[END_REF]. As well, SALT TOLERANCE 32 (SAT32) has been identified to increase the activity of vacuolar H+ transport pyrophosphatase in high salt conditions [START_REF] Park | Isolation and functional characterization of the Arabidopsis salt-tolerance 32 (AtSAT32) gene associated with salt tolerance and ABA signaling[END_REF]). HIGH-AFFINITY K + TRANSPORTER 1 (HKT1) also contributes to the ionic partitioning between roots and shoots [START_REF] Ali | Role and functional differences of HKT1type transporters in plants under salt stress[END_REF]. Besides, genes involved in cell cycle activation as CYCLIN A2 (CYCA2) and CYCLIN B1 (CYCB1) are downregulated under salt-triggered osmotic stress, and hence impair normal root growth by minimizing the cellular division rate in the meristematic zone [START_REF] Qi | Cell cycle regulation in the plant response to stress[END_REF]. Moreover, genes employed in Ca 2+ signaling and ROS scavenging are upregulated under SS as they are implemented in stress signal transduction and oxidative burst mitigation, respectively [START_REF] Manishankar | Calcium signaling during salt stress and in the regulation of ion homeostasis[END_REF].

Overall, examining the plant mechanisms of salt tolerance is essential in the fight against climate change. Such examination becomes of higher importance in roots rather than shoots, as they are at the direct interface with salinized soils. In fact, the root system architecture (RSA) is greatly influenced by salt stress, which affects the whole plant's well-being [START_REF] Zolla | Mild salinity stimulates a stress-induced morphogenic response in Arabidopsis thaliana roots[END_REF]. Not only SS, but also HS, CS, and other abiotic or biotic stresses have momentous impacts on roots, which must drag research's attention to analyze the impacts of these environmental cues on roots at multiple levels and from different perspectives.

1.4 The Plant Root

Preface

Roots are crucial organs in plants representing a sizable portion of their bodies. However, they were relatively neglected throughout the history of plant research, despite the knowledge of their fundamentality. As they grow inside opaque and heterogenous soils, their observation and manipulation have always been challenging. In the past decades, these limitations are being gradually surpassed, thanks to innovative methodologies such as in vitro culture and non-invasive imaging. Roots are mostly famous for their main roles in anchoring plants into the soil, absorbing and conducting water and nutrients, in addition to interacting with their surroundings such as with neighboring plants (e.g. competition) and microorganisms (e.g. mycorrhization; nodulation) (Petricka et al. 2012).

The primary root development and patterning follow genetically programmed intrinsic signals (Novoplansky 2019), but the fate of the root system architecture (RSA) is continuously adjusted by extrinsic environmental cues. These adjustments reflect the phenotypic plasticity of roots, which allow them to cope with constantly changing environments (Novoplansky 2019;Simard 2018). To illustrate, when roots perceive external signals as biotic or abiotic stresses, they are capable of acclimating and adapting via fitting their morphologies and physiologies. These regulations relay on multi-leveled and overlapping molecular networks that have been extensively studied (Wachsman et al. 2015). Besides, natural variation provides an elaborated means to thoroughly comprehend the different players in root's plasticity (Ristova and Busch 2014).

Anatomy

The anatomy of roots and the molecular pathways that govern their patterning have been well established in A. thaliana (Petricka et al. 2012). The distal root tips comprise the root apical meristem (RAM), which is a set of stem cells surrounding the inactive quiescent center (QC). The stem cells at the root ward side of QC produce the root cap which is composed of central columella cells involved in gravity sensing, and of peripheral cells that secrete mucilage. The QC maintains the stem cell niche (SCN) by replacing the meristematic cells in the RAM and regulates the organization of the root's primary tissues [START_REF] Perilli | Growth and development of the root apical meristem[END_REF]).

The root's primary tissues are organized as four concentric cylinders of cellular layers along a transverse axis. First, the epidermis is the outermost layer that forms the root surface alongside with the apical root cap. It has two types of cells, the hair cells (trichoblasts) and the non-hair cells (atrichoblasts), and it hence protects the root and enhances its absorption capacity via root hair formation (Bruex et al. 2012). Next, the cortex is the second layer which conducts and stores water and nutrients from the epidermis into the underlying layers [START_REF] Lux | Root cortex: structural and functional variability and responses to environmental stress[END_REF]). Third, the endodermis is one layer of compacted cells. It forms a selective barrier via blocking the apoplastic transport with a specialized cell wall, the Casparian strip (Pengxue et al. 2018;Yuree et al. 2013). Fourth, the stele is the innermost vascular cylinder that conducts water and nutrients via the xylem and photosynthates via the phloem, where the protoxylem and the metaxylem represent the two types of xylems, and the phloem comprises sieve elements and companion cells. Both xylem and phloem are separated with procambial cells and surrounded by the pericycle, the site of initiation of lateral roots (LRs) [START_REF] Hacke | Functional and ecological xylem anatomy[END_REF][START_REF] Heo | Phloem development: current knowledge and future perspectives[END_REF]) (Figure 6).

Furthermore, the plant root is divided into three developmental zones along a vertical axis: the meristematic zone (MZ), the elongation zone (EZ), and the differentiation zone (DZ). The MZ is the site for cellular division and proliferation. The mitotic competence in the MZ is disproportionate with the distance from the stem cell niche. At the transition zone, the interface between the MZ and the EZ, the cells exit their life cycles. In the EZ, cells expand and contribute to the primary root growth.

This expansion is achieved by the tonoplast water uptake and modifications in the cell walls. Lastly, the DZ comprises mature cells with specialized functions. The DZ is characterized by two notable features: epidermal root hairs and endodermal Casparian strips (Petricka et al. 2012) (Figure 6).

Roots and Abiotic Stresses

Being in intact and direct contact with the soil, roots are highly prone to adverse effects by a myriad of abiotic stresses such as salinity, drought, waterlogging, abrupt temperature, nutrient imbalance, and mechanical restrictions. Nevertheless, the impacts of environmental stresses on their growth and development are relatively less studied due to technical limitations. In fact, roots can sense the physiochemical status in the surrounding soil and accordingly adjust their development and physiology. They have revealed an enormous range of adaptations in response to environmental heterogeneities (Novoplansky 2019).

Several studies have well documented the impacts of HS on roots in several species under various stress regimes. For instances, soybean roots showed altered color and texture, plasmolysis in the root tip cells, cytoplasmic coagulation, vacuolar breakage, and death under extreme temperatures [START_REF] Chen | Observations of soybean root meristematic cells in response to heat shock[END_REF]. Also, Pisum sativum revealed least growth primary root and lateral root initiation under HS [START_REF] Gladish | The effects of temperature on primary root growth dynamics and lateral root distribution in garden pea (Pisum sativum L., cv."Alaska")[END_REF]. Moreover, other studies showed reductions in the root mass, branching, elongation, hydraulic conductivity, enzymatic activity, and viability and elevations in the root membrane damage and mortality due to heat [START_REF] Heckathorn | Heat stress and roots. Climate change and plant abiotic stress tolerance[END_REF].

Furthermore, roots have been shown to be highly sensitive to cold stress (CS) as plants are more sensitive to cold soil temperature compared to cold air temperature [START_REF] Sun | Effects of cold stress on root growth and physiological metabolisms in seedlings of different sugarcane varieties[END_REF]. In fact, CS alters the structure and function of the root system. It hinders the root growth and hence reduces the root biomass, length, branching, surface area, and volume which impacts its morphology and metabolism. For instances, it limits the hydraulic conductivity and the absorption capacity and quality of water and minerals which disturbs the whole plant homeostasis and retards its growth (Franco et al. 2015).

Additionally, salt stress (SS) has severe effects on the root development which is hindered upon the exposure to elevated salinity. SS translates into osmotic stress induced by the disturbed water potential in the rhizosphere and into ionic stress due to the alterations in the ionic concentrations inside the root tissues. In fact, SS highly influences the root architecture leading to the development of shorter but more branched roots in Lycopersicon esculentum [START_REF] Karni | Involvement of root ethylene and oxidative stress-related activities in pre-conditioning of tomato transplants by increased salinity[END_REF]) and to the formation of shallow roots in wheat [START_REF] Rose | Development and performance of wheat roots above shallow saline groundwater[END_REF]. Furthermore, SS changes the concentrations of micronutrients such as Cu, Zn, Mn, and Fe within the root live tissues [START_REF] Khayyat | Calcium effects on changes in chlorophyll contents, dry weight and micronutrients of strawberry (Fragaria× ananassa Duch.) plants under salt-stress conditions[END_REF]. How roots respond to SS is considerably variable between families, genera, or within a species (Franco et al. 2015).

The Plant Cell Wall

The cell wall (CW) encases the plant cell, provides it with rigidity, and determines its growth, structure, and diverse functions. As the CW is an extracellular layer, it is directly exposed to the environment and plays essential roles in signaling and in protecting the cells from abiotic constraints.

Therefore, CWs are highly dynamic and diversified structures capable of remodeling by stiffening or loosening throughout the development of different plant tissues and organs and in response to extrinsic cues (Tenhaken 2015).

The CW is formed during cellular division and is set up as in multiple layers, which are the middle lamella (ML), the primary CW (PCW), and the secondary CW (SCW) [START_REF] Voragen | Pectin, a versatile polysaccharide present in plant cell walls[END_REF]. Basically, the PCW consists of cellulosic fibers linked to hemicellulose tethers and embedded into a matrix of pectins. It also contains proteins that build up to 5-10% of its total composition. Among these are the expansins which are pH-dependent proteins that catalyze the primary CW growth [START_REF] Cosgrove | Growth of the plant cell wall[END_REF].

Additionally, the SCWs have distinct composition and organization and are not detected in all cells.

To illustrate, they are deposited in certain specialized cells during their differentiation to provide them with extra mechanical sustenance such as in the root endodermis and tracheary elements.

They are majorly composed of cellulose, hemicellulose, lignin, and suberin [START_REF] Zhong | Secondary cell walls: biosynthesis, patterned deposition and transcriptional regulation[END_REF].

Moreover, the ML is the layer that sticks together adjacent CWs and is majorly composed of pectins.

However, it was recently characterized to be involved in numerous biological activities beyond its function as a glue [START_REF] Zamil | The middle lamella-more than a glue[END_REF].

Being the outermost layers of cells, CWs are the primary lines of defense against recurrent environmental constraints. For instance, the plant growth relies on the mitotic divisions in the meristematic zones and on the subsequent turgor-driven cellular elongation, during which cell walls notable expand. However, abiotic stresses casually hinder growth as they induce CW stiffening and hence hinder its expansion. In this context, reactive oxygen species and class III peroxidases play key roles in signaling and in in catalyzing the cross-linking of phenolic compounds and glycoproteins (Francoz et al. 2015).

ROS and Abiotic Stress

The roles of ROS as key players orchestrating root development have been thoroughly elaborated.

Furthermore, ROS mediate the acclimation process to extrinsic signals such as pathogen infections, environmental stress, and other developmental stimuli (Choudhury et al. 2017). The oxidative burst due to rapid ROS generation was found to play important roles in such plant-environment interactions. ROS interplay with molecular other actors to deliver convenient adaptational modifications in the plant (Liu and He 2016) (Figure 7).

For instances, the ROS regulatory machineries coordinate with calcium and hormonal signaling to fine tune the plant's status when exposed to elevated temperatures [START_REF] Suzuki | Coordination between ROS regulatory systems and other pathways under heat stress and pathogen attack[END_REF]. Also, ROS are involved in the induction of programmed cell death (PCD) as a defense mechanism to avoid further damage under extreme heat [START_REF] Petrov | ROS-mediated abiotic stressinduced programmed cell death in plants[END_REF]. Similarly, low temperatures disturb the ROS homeostasis by decreasing the activities of several enzymes such as ascorbate peroxidases, catalases, and glutathione peroxidases which disrupts the delicate balance between ROS generation and scavenging. Consequently, this derangement may lead to cellular damage due to the oxidation of biomolecules such as lipids, proteins, and nucleic acids [START_REF] Zhao | The β-amylase PbrBAM3 from pear (Pyrus betulaefolia) regulates soluble sugar accumulation and ROS homeostasis in response to cold stress[END_REF]. Furthermore, salt stress (SS) induces ROS production and accumulation. To illustrate, under elevated salinity, plants decrease their stomatal conductance to minimize the water loss, which indeed reduces the CO2 availability to the Calvin cycle, resulting in surplus light excitation beyond the photosynthetic demand. Consequently, the excess light hinders the activity of the electron transport chain and increases ROS production (Bose et al. 2014). However, the accumulated ROS interacts with ethylene to promote salt tolerance. To illustrate, in response to salt stress, ethylene reduces the oxidative damage by enhancing ROS scavenging; it also triggers ROS accumulation in the root stele to maintain the Na + /K + homeostasis. Additionally, the accumulated ROS may further reduce the Na + /K + ratio by increasing the cytosolic levels of free calcium ions (Zhang et al. 2016).

Class III Peroxidases and Abiotic Stress

Th class III peroxidases are members in the ROS regulatory systems. They are present in all Embryophytes but missing from Chlorophyceae; in Arabidopsis thaliana, 73 members of this family have been found (Tognolli et al. 2002). They are apoplastic proteins characterized by a dual hydroxylic and peroxidative cycles by which they can generate ROS and hence oxidize various substrates by using H2O2 as an electron acceptor, but they can also regulate the local concentration of H2O2 or produce ROS (Francoz et al. 2015). Therefore, they play a pivotal role in cellular growth by regulating a tight balance between cell wall loosening or stiffening.

Also, they contribute to numerous biological processes all along the plant's life cycle such as auxin metabolism, lignin and suberin formation, cross-linking of cell wall components, defense against pathogens, and cell elongation (Figure 8). Their transcriptional regulation and activity can be modified in accordance with external and internal cues to aid the plant in meeting its demands under stressful conditions (Passardi et al. 2005). Several class III peroxidases have been identified for their significant roles in providing tolerance to plants against abiotic stresses. Salt tolerance has been positively correlated with the activity of peroxidases due to their role in detoxifying the accumulated ROS (Shahzad et al. 2019). For instance, the overexpression of AtPrx03 improved salt tolerance in transgenic lines [START_REF] Llorente | A novel cold-inducible gene from Arabidopsis, RCI3, encodes a peroxidase that constitutes a component for stress tolerance[END_REF].

Similarly, numerous studies indicated subsets of the peroxidase genes as actors in cold acclimation.

To exemplify, the overexpression of AtPrx22, AtPrx39, and AtPrx69 enhances the cold tolerance by increasing the ROS production (Kim et al. 2012). Likewise, the expression of a barley class III peroxidase in transgenic apple Malus domestica results in altered growth, xylem formation, and tolerance to heat stress [START_REF] Vicuna Requesens | Expression of a barley peroxidase in transgenic apple (Malus domestica L.) results in altered growth, xylem formation and tolerance to heat stress[END_REF].

In fact, countless findings have further pointed towards the roles of class III peroxidases in the response to abiotic constraints. Although some functions associated with class III peroxidases appear to be either redundant or even paradoxical, yet it is evident that these proteins play fundamental roles in the ROS regulatory system and in the plant acclimation to environmental stress (Passardi et al. 2005).

Thesis Objectives

The thesis objective is to evaluate the plant response to thermal and saline stresses by multidimensional approaches integrating ecological, genomic, transcriptomic, and phenotypic data.

For this aim, novel natural populations of Arabidopsis thaliana have been exploited to study their intra-specific diversity and contrasted responses to various growth conditions. The studied populations were previously gathered from different locations in the Pyrenees, the mountainous physical barrier separating the Iberian Peninsula from France. These populations fill a gap in the geographic distribution of A. thaliana and could serve as a valuable tool to understand the genetic variation between Iberian Peninsula and the rest of Europe as well as the plant adaptation to abiotic stress.

In fact, the project focuses on studying the root development under different environmental conditions in the A. thaliana populations. Indeed, roots are of particular interest due to their fundamental roles and their enormous phenotypic plasticity. This project complements the previous study of the phenotypic variations in the aerial parts of the A. thaliana Pyrenean collection under optimal and suboptimal growth conditions (Duruflé et al. 2019).

Therefore, the first part of this thesis will provide a comprehensive review of the role of reactive oxygen species (ROS) during root development. In fact, root development is a highly organized and complex process which is regulated by a myriad of molecular actors. In this context, ROS have been recognized as growth regulators during the plant root development. In this review, recent findings about how ROS are involved in multiple stages of root development during cell proliferation, elongation, and differentiation have been elaborated (Eljebbawi et al. 2021).

The second part of this thesis details the state-of-art experiments on the A. thaliana Pyrenean populations to study their responses to thermal and saline stresses. These experiments entail the 2 Chapter I: Root Development

Preface

In A. thaliana, root development has been thoroughly investigated due to its simplicity and tractability. A magnitude of molecular pathways regulating root development has been identified in different processes such as radial growth, cellular specification, tissue patterning, and root elongation and differentiation.

ROS have been identified for their roles in controlling the development and proper patterning of A.

thaliana root. In the review entitled "Highlighting ROS as multitaskers in root development", the roles of ROS in choreographing root development depicted in around 140 references (>80% from the last decade) have been illustrated. In fact, ROS do not act in isolation but rather as part of a large and complex redox signaling network.

Review: Highlighting Reactive Oxygen Species as Multitaskers in Root Development

"Highlighting reactive oxygen species as multitaskers in root development" (Eljebbawi et al. 2021) is depicted under this heading.

▪ ROS are signaling molecules that choreograph root structures and anatomies ▪ MYB36 acts in lateral root development, by manipulating the ROS balance ▪ ROS do not act in isolation but rather as part of a large and complex redox signaling ▪ ROS-producing or ROS-scavenging machineries are co-present simultaneously within cells

SUMMARY

Reactive oxygen species (ROS) are naturally produced by several redox reactions during plant regular metabolism such as photosynthesis and respiration. Due to their chemical properties and high reactivity, ROS were initially described as detrimental for cells during oxidative stress. However, they have been further recognized as key players in numerous developmental and physiological processes throughout the plant life cycle. Recent studies report the important role of ROS as growth regulators during plant root developmental processes such as in meristem maintenance, in root elongation, and in lateral root, root hair, endodermis, and vascular tissue differentiation. All involve multifaceted interplays between steady-state levels of ROS with transcriptional regulators, phytohormones, and nutrients. In this review, we attempt to summarize recent findings about how ROS are involved in multiple stages of plant root development during cell proliferation, elongation, and differentiation.

INTRODUCTION

Reactive oxygen species

The emergence of complex multicellular life was interconnected with the buildup of oxygen on Earth. Oxygen accumulation resulted from the emergence of oxygenic photosynthesis and consequently enabled the evolution of aerobic life. This evolving era is characterized by high-energy yielding metabolic pathways [START_REF] Ward | Follow the oxygen: comparative histories of planetary oxygenation and opportunities for aerobic life[END_REF] such as aerobic respiration and oxidative phosphorylation. These pathways, where oxygen serves as the final acceptor of electrons, are more thermodynamically efficient in the evolving complexity than other nonaerobic pathways with nonoxygenic oxidants. This denotes oxygen as the most energetic oxidant in biological life [START_REF] Reinhard | Earth's oxygen cycle and the evolution of animal life[END_REF]. The reduction of oxygen by the ATP-producing electron transport chains, in addition to other metabolic pathways in which molecular oxygen is the ultimate oxidizing agent, can generate various levels of reactive oxygen species (ROS) (see Box 1). Therefore, ROS are constitutive products of aerobic metabolism [START_REF] Singh | Reactive oxygen species (ROS): beneficial companions of plants' developmental processes[END_REF][START_REF] Rabinovitch | AMPK maintains cellular metabolic homeostasis through regulation of mitochondrial reactive oxygen species[END_REF], and it is definite that the emergence and permanence of aerobic life was never ''ROS-free'' [START_REF] Mittler | ROS are good[END_REF].

ROS homeostasis

Earlier on, our understanding to ROS was restricted to the lethal manifestations of the disparity between ROS production and scavenging (Sies, 1986[START_REF] Sies | Oxidative stress: oxidants and antioxidants[END_REF]. This disparity leads to oxidative damage to different molecules and cellular components as nucleic acids, proteins, and membranes and cell death [START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF][START_REF] Anjum | Lipids and proteins-major targets of oxidative modifications in abiotic stressed plants[END_REF]. Therefore, as a part of their evolutionary adaptations, plants have developed important ROS-detoxifying machineries (see Box 1). In planta, a large battery of antioxidative enzymes was identified in addition to various antioxidants that form together a double-armed ROS-scavenging mechanism [START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF]. Together, they forage ROS and counterattack the elevations in their concentrations, preventing oxidative bursts and the consequent detrimental manifestations [START_REF] Mittler | Reactive oxygen gene network of plants[END_REF] and maintaining a threshold boundary between redox potential and cytotoxicity, referred to as ROS homeostasis (Saini et al., 2018). In Arabidopsis thaliana, there exists a highly dynamic and complementary network of more than 150 genes that have been identified and correlated to ROS homeostasis [START_REF] Miller | The plant NADPH oxidase RBOHD mediates rapid systemic signaling in response to diverse stimuli[END_REF]. Few examples related to root development are listed in Table 1.

On another side, ROS have been lately recognized for playing fundamental roles as signaling molecules engaged in plant development. They are currently considered as key actors that control cell proliferation, patterning, and differentiation during plant growth [START_REF] Schippers | Redox regulation in shoot growth, SAM maintenance and flowering[END_REF][START_REF] Tsukagoshi | Control of root growth and development by reactive oxygen species[END_REF]Tognetti et al., 2017). They are also involved in the perception of environmental signals, their transduction, and their (Miller et al., 2010;[START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF]Saini et al., 2018). These modifications derive from the association between ROS homeostasis and subsequent adjustments of gene expression. Hence, being fundamental in plant growth and development, ROS detection in time and space is required to better understand their roles and regulations. This triggered the development of several dyes, probes, and, recently, genetically encoded sensors to detect ROS, mostly as H 2 O 2 (see Box 2).

ROS production and scavenging

In plants, ROS are constitutively produced during different biochemical reactions located in various cellular compartments, i.e., chloroplast, mitochondria, and the peroxisome in addition to the apoplast. In the chloroplasts, ROS production is associated with the light-dependent reactions and is due to the leakage of electrons [START_REF] Ivanov | Formation mechanisms of superoxide radical and hydrogen peroxide in chloroplasts, and factors determining the signalling by hydrogen peroxide[END_REF]. Nevertheless, in the mitochondria, ROS production is relatively lower and is related to the respiratory chain [START_REF] Marchi | Mitochondria-Ros crosstalk in the control of cell death and aging[END_REF][START_REF] Kro ¨ller-Scho ¨n | Molecular mechanisms of the crosstalk between mitochondria and NADPH oxidase through reactive oxygen species -studies in white blood cells and in animal models[END_REF]. In addition, peroxisomes are also sites for hydrogen peroxide production during different processes as the glycolate oxidase Box 1. ROS homeostasis concepts

ROS homeostasis box

What are ROS? ROS are highly reactive molecules that originate from oxygen (O 2 ) where each has its distinct life space and chemical properties [START_REF] Ozcan | Biochemistry of reactive oxygen and nitrogen species[END_REF].

ROS molecules: ROS are in various forms among which are the radicals having free electrons such as superoxide

(O 2 .
-), hydroxyl radical (OH), peroxyl (RO 2 -), and alkoxyl (RO -); others are nonradicals as hypochlorous acid (HOCl), ozone (O 3 ), singlet oxygen ( 1 O 2 ), and hydrogen peroxide (H 2 O 2 ) [START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF]. Each type of ROS molecule has distinct chemical properties: singlet oxygen can oxidize lipids, proteins, and guanidine residues of DNA; superoxide like singlet oxygen has a half-life time of 1-4 ms and reacts with Fe-S proteins; and hydroxyl radicals are extremely reactive and unstable with a half-life time of 1 ns [START_REF] Mittler | ROS are good[END_REF][START_REF] Waszczak | Reactive oxygen species in plant signaling[END_REF]. In contrast, hydrogen peroxide is the most stable ROS (more than 1 ms) and, therefore, is the predominant ROS involved in cellular signaling.

ROS homeostasis is controlled by the delicate balance between ROS production and scavenging, maintaining a threshold boundary between redox potential and cytotoxicity (Saini et al., 2018).

ROS in the organelles. ROS are produced in the mitochondria by mitochondrial respiration, in the chloroplasts during photosynthesis, in the peroxisome-localized photorespiratory reactions, and in the apoplast by NADPH oxidases such as the respiratory burst oxidase homologs (RBOHs), peroxidases, and other oxidases.

ROS in the apoplast. Two enzymatic families contribute to the apoplastic ROS production. In addition, other families of enzymes are also able to modify the ROS homeostasis in the apoplast such as oxalate oxidases, polyamine oxidases, quinone oxidases, lipoxygenases, etc.

1. The NADPH oxidases also called respiratory burst oxidative homologs (RBOHs) [START_REF] Orman-Ligeza | RBOH-mediated ROS production facilitates lateral root emergence in Arabidopsis[END_REF] consist of transmembrane proteins which produce superoxide O 2 .

-. In Arabidopsis thaliana, ten genes have been asserted to encode RBOHs (RBOHA-RBOHJ) [START_REF] Marino | A burst of plant NADPH oxidases[END_REF].

2. The class III peroxidase family (PRX) consists of apoplastic proteins that oxidize various substrates by using H 2 O 2 as an electron acceptor but can also regulate the local concentration of H 2 O 2 or produce ROS (Francoz et al., 2015). In Arabidopsis thaliana, 73 members of this family have been found (Tognolli et al., 2002), but only few of them have been characterized.

Apoplastic ROS can be channeled into the cytoplasm by multiple aquaporin of the PIP-type [START_REF] Tian | Plant aquaporin AtPIP1;4 links apoplastic H2O2 induction to disease immunity pathways[END_REF].

ROS scavenging is a two-armed mechanism:

1. The first arm consists of the antioxidative enzymes as the superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APx), monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), glutathione reductase (GR), glutathione peroxidase (GPx), and class III peroxidase (PRX) [START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF]Choudhary et al., 2020). (Francoz et al., 2015).

ROS released in the chloroplast during photosynthesis represent the biggest pool of ROS among the different compartments. These ROS are implicated in signaling processes such as the regulation programmed cell death (PCD) [START_REF] Shapiguzov | ROS-talk -how the apoplast, the chloroplast, and the nucleus get the message through[END_REF]. In addition, ROS produced in mitochondria during oxidative phosphorylation are associated to roles in redox signaling, retrograde signaling, plant hormone action, and PCD during pathogen attacks [START_REF] Huang | The roles of mitochondrial reactive oxygen species in cellular signaling and stress response in plants[END_REF]. First, these ROS may possibly adjust protein functions in the mitochondrial matrix by oxidizing specific protein thiols as for alternative oxidases (AOXs) [START_REF] Yoshida | Systematic exploration of thioredoxin target proteins in plant mitochondria[END_REF] and for several tricarboxylic acid cycle (TCA) enzymes [START_REF] Daloso | Thioredoxin, a master regulator of the tricarboxylic acid cycle in plant mitochondria[END_REF]. Second, they are probably involved in the mitochondrial retrograde regulation (MRR) where the mitochondria communicate back their functional status to the nucleus. The observation of MRR responses shows remarkable overlaps with transcriptional responses to different ROS triggers and abiotic stress, and the induction of MRR with complex III inhibitor antimycin A increased ROS production [START_REF] Van Aken | Mitochondrial and chloroplast stress responses are modulated in distinct touch and chemical inhibition phases[END_REF]. Moreover, the interaction between hormonal signaling that regulates all layers of plant development and cellular functions and mitochondrial signaling, including mitochondrial ROS signaling, has been recently reviewed [START_REF] Berkowitz | Interaction between hormonal and mitochondrial signalling during growth, development and in plant defence responses[END_REF]. Lastly, these ROS trigger the execution of PCD during pathogen attacks, where various mutants in mitochondrial functions have been reported to have diverse PCD or pathogen defense responses [START_REF] Huang | The roles of mitochondrial reactive oxygen species in cellular signaling and stress response in plants[END_REF]. To exemplify, Arabidopsis mosaic death 1, MOD1, codes for an enoyl-acyl carrier protein (ACP) reductase essential for fatty acid biosynthesis in the chloroplast and negatively regulates PCD in Arabidopsis. Recently, a study demonstrated that mitochondrial complex I is responsible for the ROS production that leads to PCD in the mod1 mutant [START_REF] Wu | Deficient plastidic fatty acid synthesis triggers cell death by modulating mitochondrial reactive oxygen species[END_REF]. Furthermore, a comprehensive chloroplast-mitochondria communication pathway that regulates the generation of mitochondrial ROS and triggers PCD has been elucidated [START_REF] Zhao | Malate transported from chloroplast to mitochondrion triggers production of ROS and PCD in Arabidopsis thaliana[END_REF]. In turn, apoplastic ROS are engaged in plant development and responses to extrinsic signals. These ROS regulate plant cell division and cell elongation rate, and hence the whole plant growth [START_REF] Podgo ´rska | Extra-cellular but extra-ordinarily important for cells: apoplastic reactive oxygen species metabolism[END_REF]; they are also implicated in regulating stomatal closure, cell wall lignification, and callose deposition in response to external signals [START_REF] Podgo ´rska | Extra-cellular but extra-ordinarily important for cells: apoplastic reactive oxygen species metabolism[END_REF]Qi et al., 2017;[START_REF] Janku | On the origin and fate of reactive oxygen species in plant cell compartments[END_REF][START_REF] Farvardin | The apoplast: a key player in plant survival[END_REF]. Obviously, ROS signaling encompasses several pathways within and between various organelles and cellular compartments. An elaborated understanding of all these pathways and their interconnections is still lacking, and their investigation remains a big challenge for plant biology research.

To sum up, in plants, ROS production is an inevitable part of the basal metabolism and occurs in various cellular compartments. Remarkably, ROS production may be suddenly enhanced in response to iScience Review environmental cues; this is defined as the ''oxidative burst'' (Choudhary et al., 2020). The oxidative burst is one of the earliest and most important physiological responses to stresses (Saini et al., 2018); it fires various signaling pathways leading to transcriptional changes in the stress-related genes, resulting in a defensive response (Baxter et al., 2014;Sewelam et al., 2016;Zhang et al., 2016). ROS overproduction may lead to an irreversible oxidative damage as the degradation of biomolecules such as lipids, proteins, nucleic acids, and carbohydrates [START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF]. This may lead to physiological disruption or even cellular death [START_REF] Anjum | Lipids and proteins-major targets of oxidative modifications in abiotic stressed plants[END_REF]Choudhary et al., 2020). Therefore, the normal cellular homeostasis requires maintaining the delicate balance between ROS production and scavenging [START_REF] Mittler | ROS are good[END_REF]. ROS scavenging is a two-armed mechanism [START_REF] Eltayeb | Overexpression of monodehydroascorbate reductase in transgenic tobacco confers enhanced tolerance to ozone, salt and polyethylene glycol stresses[END_REF] that shields the various cellular compartments against any provisional oxidative damage. Furthermore, many actors in ROS scavenging are also implicated in plant growth and development by taking part in processes such as mitosis, elongation, senescence, and PCD [START_REF] Noctor | ROS-related redox regulation and signaling in plants[END_REF].

ROS sensing

Understanding how plants sense ROS and translate their signals into physiological responses was thoroughly investigated. One mechanism to sense ROS is the oxidative post-translational modification (Ox-PTM) of proteins, which was recently reviewed [START_REF] Waszczak | Oxidative post-translational modifications of cysteine residues in plant signal transduction[END_REF]. Numerous proteins with Cys residues have been identified and reviewed as targets of Ox-PTMs such as enzymes of the Calvin cycle or signal transduction enzymes such as transcription factors, kinases, phosphatases, and RNA-binding proteins [START_REF] Dietz | Redox regulation of transcription factors in plant stress acclimation and development[END_REF][START_REF] Waszczak | Oxidative post-translational modifications of cysteine residues in plant signal transduction[END_REF][START_REF] Mittler | ROS are good[END_REF][START_REF] Sies | Oxidative stress[END_REF]. Apoplastic H 2 O 2 is sufficiently stable to penetrate into the cytoplasm via aquaporin membrane proteins where it covalently modifies proteins. However, a recent breakthrough discovery characterized a cell surface ROS sensor, the HPCA1 (HYDROGEN PEROXIDE-INDUCED Ca 2+ INCREASES 1) identified as the first known cell-surface-specific sensor for H 2 O 2 in plants [START_REF] Wu | Hydrogen peroxide sensor HPCA1 is an LRR receptor kinase in Arabidopsis[END_REF]. HPCA1 encodes a leucine-rich-repeat receptor kinase (LRR-RK) that contains two special pairs of Cys residues in its extracellular domain. [START_REF] Rhee | Methods for detection and measurement of hydrogen peroxide inside and outside of cells[END_REF][START_REF] Deng | Down-regulation of free riboflavin content induces hydrogen peroxide and a pathogen defense in Arabidopsis[END_REF][START_REF] Sang | Apoplastic and cytoplasmic location of harpin protein Hpa1 Xoo plays different roles in H2O2 generation and pathogen resistance in Arabidopsis[END_REF][START_REF] Chakraborty | Differential fineregulation of enzyme driven ROS detoxification network imparts salt tolerance in contrasting peanut genotypes[END_REF][START_REF] Tian | Plant aquaporin AtPIP1;4 links apoplastic H2O2 induction to disease immunity pathways[END_REF].

Genetically encoded probes. Genetically encoded sensors have been engineered to measure H 2 O 2 which have several advantages over the dyes because they are noninvasive, can be targeted in time and space (at tissues and cellular level), and are stable over time. To name some of the most widely used in plant cells are roGFP1 [START_REF] Schwarzla ¨nder | Confocal imaging of glutathione redox potential in living plant cells[END_REF], roGFP-GSH [START_REF] Bratt | Organelle redox autonomy during environmental stress[END_REF], GRX1-roGFP2 [START_REF] Gutscher | Real-time imaging of the intracellular glutathione redox potential[END_REF][START_REF] Schwarzla ¨nder | Confocal imaging of glutathione redox potential in living plant cells[END_REF], roGFP-Orp1 [START_REF] Dagda | Techniques to investigate mitochondrial function in neurons[END_REF], and HyPer [START_REF] Costa | H2O2 in plant peroxisomes: an in vivo analysis uncovers a Ca2+-dependent scavenging system[END_REF][START_REF] Herna ´ndez-Barrera | Hyper, a hydrogen peroxide sensor, indicates the sensitivity of the Arabidopsis root elongation zone to aluminum treatment[END_REF][START_REF] Mullineaux | ROSdependent signalling pathways in plants and algae exposed to high light: comparisons with other eukaryotes[END_REF].

Several tools have been developed for the detection and visualization of ROS in plant tissues. For more details on limitation and controls to be included for their correct use, please see [START_REF] Noctor | Intracellular redox compartmentation and ROS-related communication in regulation and signaling[END_REF]Mhamdi and Van Breusegem, 2018a;[START_REF] Fichman | Whole-plant live imaging of reactive oxygen species[END_REF].

H 2 O 2 sensing. More importantly, this covalent modification leads to the activation of HPCA1 intracellular kinase activity by its autophosphorylation, which subsequently triggers through unknown mechanisms Ca 2+ -channel gating and Ca 2+ influx, followed by activation of downstream signaling pathways (Wu et al., 2020). Remarkably, the extracellular H 2 O 2 sensing mechanism by HPCA1 does not resemble any H 2 O 2 receptors or sensors previously reported for other eukaryotic organisms, highlighting that plants have evolved a unique manner to deal with ROS. Since H 2 O 2 is also produced in several organelles, other H 2 O 2 sensors may act together with HPCA1 to transmit organelle-specific redox messages to the nucleus, along with messages arising from the apoplastic face of the plasma membrane. On another hand, HPCA1 was recently identified to be involved in quinone sensing which triggers defense-related gene expression by elevating cytoplasmic Ca 2+ and activating MAPKs (mitogen-activated protein kinase) signaling pathway named as CARD1 (CANNOT RESPOND TO DMBQ 1) [START_REF] Laohavisit | Quinone perception in plants via leucine-richrepeat receptor-like kinases[END_REF]. The recognition of quinone molecules by CARD1 is also based on Cys residues in its apoplastic ectodomain. Yet, it is still unclear how extracellular quinone and H 2 O 2 sensing are related to each other in the HPCA1/CARD1 proteins.

ROS recap

During the past years, several reviews recapped the recent findings about ROS as signaling molecules during natural metabolism or in response to exogenous factors. In 2004, the mechanisms of generation and removal of ROS during development and under biotic and abiotic stresses were reported, in addition to new insights into their complexity and roles from genetic analyses of ROS-detoxifying and ROS-signaling mutants [START_REF] Apel | Reactive oxygen species: metabolism, oxidative stress, and signal transduction[END_REF]. Moreover, the important role of ROS waves as signaling molecules in and across different cells, the dynamics and specificity of these signals, and their cross talk with other networks were thoroughly interpreted [START_REF] Mittler | ROS signaling: the new wave?[END_REF]. Furthermore, upon zooming into the ROS gene network, the RBOHs were identified as a key protein at the center of this ROS signaling network. In fact, RBOHs demonstrated important functions in the cellular biological processes as integrating calcium signaling and protein phosphorylation necessary for controlled ROS production [START_REF] Suzuki | Respiratory burst oxidases: the engines of ROS signaling[END_REF]. In 2012, the influence of apoplastic and chloroplastic ROS on nuclear gene regulation and transcriptional reprogramming was pinpointed [START_REF] Shapiguzov | ROS-talk -how the apoplast, the chloroplast, and the nucleus get the message through[END_REF]. Also, the oxidative burst after pathogen recognition and the consequent metabolic and proteomic fluxes during plant defense were described [START_REF] O'brien | Reactive oxygen species and their role in plant defence and cell wall metabolism[END_REF]. Soon after came the findings that stress responses in plants are mediated by a spatiotemporal coordination between ROS and other signals to confer systemic acquired resistance or systemic acquired acclimation (Baxter et al., 2014). Additionally, numerous updates conferred the role of ROS during abiotic stresses, such as drought [START_REF] Noctor | The roles of reactive oxygen metabolism in drought: not so cut and dried[END_REF], salinity (Bose et al., 2014), and anoxia [START_REF] Gonzali | Universal stress protein HRU1 mediates ROS homeostasis under anoxia[END_REF]. Further advancement in understanding the signaling aspect of ROS has been made in the past five years [START_REF] Dietz | Recent progress in understanding the role of reactive oxygen species in plant cell signaling[END_REF]Sewelam et al., 2016;[START_REF] Mittler | ROS are good[END_REF]Qi et al., 2017;[START_REF] Waszczak | Reactive oxygen species in plant signaling[END_REF]. Recently, the regulatory actions of ROS during plant development have also been extensively studied, yet many are still not well known. In fact, ROS have been shown to be involved in cell proliferation and differentiation, PCD, seed germination, organ growth, flower and pollen tube development, and leaf senescence [START_REF] Singh | Reactive oxygen species (ROS): beneficial companions of plants' developmental processes[END_REF]Mhamdi and Van Breusegem, 2018a).

ROS & roots

However, less is known about the involvement of ROS in roots growth and development despite the knowledge of their fundamentality. As roots grow into dark heterogeneous soils, their investigation by researchers is indeed challenging and limited, although these obstacles are being surpassed, thanks to the developing root imaging technologies [START_REF] Mooney | Developing X-ray computed tomography to non-invasively image 3-D root systems architecture in soil[END_REF][START_REF] Mairhofer | Recovering complete plant root system architectures from soil via X-ray m-Computed Tomography[END_REF][START_REF] Rella ´n-A ´lvarez | GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems[END_REF]. In A. thaliana, the plant root architecture is established by the cross talk between two key players: the genetic background and the environmental signals (Wachsman et al., 2015). Similar to the aerial part of the plant, the primary development and formatting follow genetically programmed intrinsic patterns (Novoplansky, 2019), but the fate of root morphology is strongly adjusted by extrinsic environmental signals.

These adjustments by exogenous cues reflect the phenotypic plasticity of plants, which allow them to cope with the fact that they are sessile organisms existing in a continuously changing environment (Simard, 2018). In A. thaliana, the root consists of three major zones: the meristematic zone (MZ), the elongation zone (EZ), and the differentiation zone (DZ). The root morphology is set up by highly orchestrated and dynamic balances between these zones. In fact, during this establishment of root architecture, ROS are involved as signaling molecules that choreograph root structures and anatomies [START_REF] Tsukagoshi | Control of root growth and development by reactive oxygen species[END_REF] through various developmental processes [START_REF] Czarnocka | Friend or foe? Reactive oxygen species production, scavenging and signaling in plant response to environmental stresses[END_REF]. Several other molecules have been characterized for their role in establishing and maintaining such balances as phytohormones and nutrients [START_REF] Majda | The role of auxin in cell wall expansion[END_REF][START_REF] Mangano | How does pH fit in with oscillating polar growth[END_REF][START_REF] Noctor | ROS-related redox regulation and signaling in plants[END_REF]Choudhary et al., 2020). Additionally, roots represent a perfect model for studying plant growth since all the developmental stages that a cell goes through are present. In fact, the stem cell phase is present at the root tip where cell proliferation occurs. Stem cells and their derived cells divide and shift away from a mitotically inactive quiescent center (QC). Afterward, the proliferative phase ceases and cells start to elongate and differentiate until the fully differentiated phase in the DZ [START_REF] Street | Cytokinin acts through the auxin influx carrier AUX1 to regulate cell elongation in the root[END_REF]. Therefore, this review aims to address the multiple roles of ROS during plant root development, elongation, and differentiation, focusing on the recently uncovered molecular mechanisms.

ROLE OF ROS BALANCES IN THE MERISTEMATIC AND ELONGATION ROOT ZONES DURING PROLIFERATION AND ELONGATION ROS & progression of cell cycle

Root growth and development result from the constant generation of cells in its MZ [START_REF] De | The ins and outs of the plant cell cycle[END_REF]. Afterward, these dividing cells acquire specialized functions during differentiation where they undergo orchestrated modifications. A cell cycle controls the number of dividing cells and the duration of these divisions which determines the growth rate of the root. A proper cell cycle is hence highly important for a proper root growth because it maintains the MZ size and prevents the premature differentiation (Gonza ´lez-Garcı ´a et al., 2011). In fact, the molecular mechanisms that coordinate the phase-to-phase transitions in the cell cycle have been thoroughly studied. The roles of cyclins (CYCs) and cyclin-dependent kinases (CDKs) as key actors in these transitions have been highlighted [START_REF] Hamdoun | Differential roles of two homologous cyclin-dependent kinase inhibitor genes in regulating cell cycle and innate immunity in arabidopsis1[OPEN[END_REF][START_REF] Tamirisa | A cyclin dependent kinase regulatory subunit (CKS) gene of pigeonpea imparts abiotic stress tolerance and regulates plant growth and development in Arabidopsis[END_REF]. In addition, ROS have been found to influence these actors and govern the interphasic transition in the cell cycle [START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF]. First, the cell cycle stops owing to changes in the redox homeostasis. CYCs expression is controlled by the transcription factor TEOSINTE BRANCHED1-CYCLOIDEA-PROLIFERATING CELL FACTOR1 (TCP), which contains a redoxsensitive cysteine residue that determines its activity. When ROS levels increase, a disulfide bond is formed, preventing the binding of TCP on the CYC promoters [START_REF] Viola | Redox-dependent modulation of anthocyanin biosynthesis by the TCP transcription factor TCP15 during exposure to high light intensity conditions in arabidopsis1 [OPEN[END_REF]. Moreover, CYCs and CDKs expression patterns have been correlated with the ascorbate:glutathione (ASC:GSH) cycle and their redox status (Figure 1). Several glutathione-deficit mutants revealed a cell cycle arrest as in root meristem less 1 (rml1) [START_REF] Schnaubelt | Low glutathione regulates gene expression and the redox potentials of the nucleus and cytosol in Arabidopsis thaliana[END_REF]. The concentrations of ROS, glutathione, and ascorbate in various organelles were found synchronized with transition events in the cell cycle. Accordingly, ascorbate-deficit mutants had slower cell cycles than the wild-type (WT) ones (Tognetti et al., 2017;[START_REF] Ortiz-Espı ´n | The role of ascorbate in plant growth and development[END_REF]. In addition, further studies reveal imperative roles of ROS in the cell plate synthesis during cytokinesis, the last stage of the cell cycle. During this process, the key to a proper patterning of the plant cell wall (PCW) is held by a dynamic network of filamentous structures, i.e., the cytoskeleton [START_REF] Szymanski | The actin cytoskeleton: functional arrays for cytoplasmic organization and cell shape control[END_REF]. ROS have been shown as actors during this morphogenesis. Modification of ROS homeostasis disturbed the cytoskeleton structure and formed many atypical tubulin polymers [START_REF] Livanos | Disturbance of reactive oxygen species homeostasis induces atypical tubulin polymer formation and affects mitosis in root-tip cells of Triticum turgidum and Arabidopsis thaliana[END_REF]. This aberrant formation negatively affected the cytokinesis and the cell plate synthesis. Similarly, Arabidopsis mutated for RBOHs, ROS-producing enzymes, develop disorganized cytoskeletal tubulin and hence the cytokinesis is disturbed [START_REF] Foreman | Reactive oxygen species produced by NADPH oxidase regulate plant cell growth[END_REF][START_REF] Livanos | ROS homeostasis as a prerequisite for the accomplishment of plant cytokinesis[END_REF]. Therefore, ROS are essential regulators of the cell cycle, hence contributing to the regulation of MZ size and progressive root growth.

ROS & maintenance of stem cell niche

ROS are involved in maintaining the stem cell identity in the root apical meristem (RAM) and regulating the organogenesis [START_REF] Wany | Nitrate, NO and ROS signaling in stem cell homeostasis[END_REF]. For this aim, they form extensive networks with other signaling molecules as nitric oxide (NO) in addition to several phytohormones (auxin, cytokinin, ethylene, etc.) and their associated signaling pathways [START_REF] Wany | Nitrate, NO and ROS signaling in stem cell homeostasis[END_REF]. As well, ROS fine-tunes the stem cell fate in the RAM (Yang et al., 2018). PROHIBITIN3 (PHB3) maintains the root stem cell niche maintenance. In phb3 mutants, the transcript of the cell cycle inhibitor retinoblastoma RBR is higher than the WT. However, both KNOLLE, a member of SYP11 syntaxin gene family, and cyclin-dependent protein kinase (CYCB1) which are markers of the cell cycle are downregulated. These results confirm the role of PHB3 in the RAM size maintenance. Moreover, phb3 mutants show an increased division rate in the quiescent center (QC) (>80%) compared with the WT ($5%) which indicates the role of PHB3 in the QC identity maintenance. In fact, this PHB3 regulation is in cross talk with the redox status since hydrogen peroxide and superoxide overaccumulate in the phb3 plants [START_REF] Kong | PHB3 maintains root stem cell niche identity through ROS-responsive AP2/ERF transcription factors in arabidopsis[END_REF]. In the RAM, ROS production is regulated according to the nutrient availability in the soil. Under nitrate deficiency, ROS production is induced and subsequently inhibits PHB3 expression. This triggers ROS-responsive factors (ERF109, ERF114, and ERF115) leading to cellular proliferation and differentiation (Figure 1). On the contrary, nitrate sufficiency promotes the production of glutathione antioxidant which reduces ROS concentrations. Therefore, PHB3 becomes active and inhibits the underlying ETHYLENE RESPONSE FACTOR 115 (ERF115), thus maintaining the pluripotency of the QC (Figure 1) [START_REF] Kong | PHB3 maintains root stem cell niche identity through ROS-responsive AP2/ERF transcription factors in arabidopsis[END_REF]. Simultaneously, ETHYLENE RESPONSE FACTOR 109 and 114 (ERF109 and ERF114) are induced to promote cellular elongation and differentiation in the elongation and differentiation zones, respectively [START_REF] Wany | Nitrate, NO and ROS signaling in stem cell homeostasis[END_REF]. Moreover, PHB3 plays a role in preserving redox homeostasis in the mitochondria. In Arabidopsis phb3 mutants, genes implicated in ROS production and signaling such as alternative oxidases (AOXs), ALTERNATIVE NAD(P)H DEHYDROGENASE 1 (NDA1), and NAD(P)H DEHYDROGENASE B2 (NDB2) showed higher expression [START_REF] Kong | PHB3 maintains root stem cell niche identity through ROS-responsive AP2/ERF transcription factors in arabidopsis[END_REF]. These studies suggest a vital role for ROS in conserving the stem cell niche, which enables a continued growth of the root.

ROS & cell elongation

The dividing cells enter a new phase of cellular elongation in the EZ. This elongation is mostly dependent on the structure and plasticity of the primary cell walls (PCWs). The dynamics of the PCW are associated with the properties of its components, polysaccharides and proteins [START_REF] Schmidt | Role of reactive oxygen species during cell expansion in leaves[END_REF]. In our scope, Review numerous studies reported the role of apoplastic compounds in controlling this cellular expansion in the EZ. Cellular expansion rates are tightly related to the balance between cell wall stiffening and loosening, where both are controlled by ROS homeostasis (Francoz et al., 2015). Primarily, during their peroxidative cycle, PRXs oxidize several PCW components and consequently enhance PCW stiffening by directly affecting its components' cross-links [START_REF] Dunand | Distribution of superoxide and hydrogen peroxide in Arabidopsis root and their influence on root development: possible interaction with peroxidases[END_REF][START_REF] Marzol | Class III peroxidases PRX01, PRX44, and PRX73 potentially target extensins during root hair growth in Arabidopsis thaliana[END_REF]. PRXs indeed catalyze the formation of cross-links between phenolics and extensins. In this sense, the cell wall stiffens, and hence the cellular elongation capacity is reduced (Francoz et al., 2015). Thus, on the one hand, elevated levels of H 2 O 2 in the apoplast were found to increase cell wall rigidity. However, in their hydroxylic cycle, PRXs produce ROS which enhance the nonenzymatic PCW loosening and thus promote cellular elongation. In this sense, auxin-induced RBOHs produce O 2 .

-into the PCW. There, these short-living molecules are rapidly dismutated into H 2 O 2 . Then, H 2 O 2 is utilized by PRXs to produce OH À- [START_REF] Majda | The role of auxin in cell wall expansion[END_REF][START_REF] Marzol | Class III peroxidases PRX01, PRX44, and PRX73 potentially target extensins during root hair growth in Arabidopsis thaliana[END_REF]. In fact, the produced OH À catalyzes the oxidative cleavage of xyloglucan and other pectins, which loosens the PCW and promotes cellular expansion [START_REF] Schmidt | Role of reactive oxygen species during cell expansion in leaves[END_REF]. These contrasted findings suggest that ROS have a dual role in determining the cell wall status and reveal the effects of hydroxyl:peroxide (OH À :H 2 O 2 ) balance in the apoplast [START_REF] Schmidt | Role of reactive oxygen species during cell expansion in leaves[END_REF]). Yet, it is unclear how these opposite effects on cell wall polymers are coordinated during cell elongation [START_REF] Lee | A lignin molecular brace controls precision processing of cell walls critical for surface integrity in arabidopsis[END_REF][START_REF] Francoz | Pectin demethylesterification generates platforms that anchor peroxidases to remodel plant cell wall domains[END_REF].

In addition, a transcription factor of the MYB family, MYB30, which regulates the expression of several genes involved in the transport of very-long-chain fatty acids (VLCFAs), has been identified to regulate cellular expansion in the root in response to ROS [START_REF] Mabuchi | MYB30 links ROS signaling, root cell elongation, and plant immune responses[END_REF]. The transfer DNA insertion line myb30-1, which has reduced levels of MYB30, showed a higher root elongation rate than the WT upon H 2 O 2 treatment. By counting the number and measuring the length of cortical cells in the MZ and EZ, it was proved that this increase in elongation rate is due to longer cells in the EZ and not to an increase in cells number [START_REF] Mabuchi | MYB30 links ROS signaling, root cell elongation, and plant immune responses[END_REF]. Also, the overexpression of MYB30 in myb30 mutants resulted in shorter roots under control conditions. These results suggested that MYB30 is sufficient to inhibit root elongation. The observation of MYB30 expression by transcriptional and translational fusions revealed that MYB30 is induced by H 2 O 2 and expressed in the MZ and EZ [START_REF] Mabuchi | MYB30 links ROS signaling, root cell elongation, and plant immune responses[END_REF].

ROS at the interface between proliferation and differentiation

An additional complexity in the redox regulation of the developmental processes is presented at the transition zone (TZ) of the primary root at the interface between the MZ and the EZ [START_REF] Singh | Reactive oxygen species (ROS): beneficial companions of plants' developmental processes[END_REF]. At the root TZ, UPBEAT1 (UPB1), a bHLH TF, regulates the ROS homeostasis between two ROS species, i.e., superoxide (O 2 .-) and peroxide (H 2 O 2 ), to direct growth either toward proliferation in the MZ or toward differentiation in the upper zones (Figure 1). It was detected that a high (O [START_REF] Tsukagoshi | Transcriptional regulation of ROS controls transition from proliferation to differentiation in the root[END_REF]. The upb1 mutant shows a significant increase in the number of cortical cells, indicating enlargement of the meristem. An overexpression of UPB1 showed reduced root length and a decrease in the cortex cell number in the MZ [START_REF] Tsukagoshi | Transcriptional regulation of ROS controls transition from proliferation to differentiation in the root[END_REF]. UPB1 acts as a regulator of root growth through modulation of the transition from cell proliferation to elongation as well as plays a role in controlling cell size. UPB1 has 166 putative direct target genes, among which are several TFs. It also inhibits expression of several peroxidase genes (PRX39, PRX40, and PRX57), where PRX57 is of higher importance in this context as it is colocalized at the TZ (Figure 1). This inhibition of PRX expression leads to an accumulation of H 2 O 2 , changing the redox homeostasis in favor of differentiation rather than proliferation. Hence, upb1 mutants develop longer roots than the WT [START_REF] Tsukagoshi | Transcriptional regulation of ROS controls transition from proliferation to differentiation in the root[END_REF].

ROS & differential elongation

ROS are required to establish the gravitropic curvature response of plant roots. This response is an asymmetrical cellular elongation, where gravity stimulates the arrest of elongation at the lower flank of the root [START_REF] Singh | Reactive oxygen species (ROS): beneficial companions of plants' developmental processes[END_REF]. In fact, gravitropism is a versatile and multistep process. First, gravity sensing begins in specialized columella cells containing statoliths, i.e., plastids rich in starch, in the root cap [START_REF] Blancaflor | Mapping the functional roles of cap cells in the response of arabidopsis primary roots to gravity[END_REF][START_REF] Leitz | Statolith sedimentation kinetics and force transduction to the cortical endoplasmic reticulum in gravity-sensing Arabidopsis columella cells[END_REF]. Afterward, an auxin-dependent complex signaling pathway [START_REF] Zhang | Auxin guides roots to avoid obstacles during gravitropic growth[END_REF], which also involves calcium (Ca 2+ ), translocates this message into the EZ, where the curvature response occurs [START_REF] Su | Molecular mechanisms of root gravitropism[END_REF]. ROS are required to establish the root elongation in response to gravitropism [START_REF] Swarup | Root gravitropism. In Plant Roots: The Hidden Half[END_REF]. In Zea mays roots, gravistimulation induces higher ROS production in the apex and the lower cortex than in the upper zones. A prolonged stimulation leads to consequent ROS accumulation in the upper zones, particularly in the EZ. This asymmetric distribution of ROS suggests that ROS are actors in developing the gravitropic response of roots. In fact, the gravity-dependent redistribution of auxin triggers the root bending responses by stimulating ROS generation [START_REF] Joo | Role of auxin-induced reactive oxygen species in[END_REF]. Auxin via iScience Review phosphatidylinositol 3-kinase (PI3K)-dependent pathway activates transmembrane RBOHs and triggers subsequent ROS production at the bending region [START_REF] Krieger | Reactive oxygen species tune root tropic responses[END_REF]. The produced ROS inhibit cellular elongation by modulating the cell wall stiffening.

ROLE OF ROS DURING ROOT DIFFERENTIATION

ROS & tracheary elements

ROS are implicated in the differentiation of the tracheary elements, particularly in their lignification process. In A. thaliana, vasculature is arranged into a central stele, where xylem and phloem are interspersed with undifferentiated procambial cells and surrounded by the pericycle. These longitudinal vessels transport water and nutrients through the roots to the upper plant parts. Accordingly, they develop reinforcing and lignified secondary wall thickenings to cope with the negative water potential and prevent cellular collapse [START_REF] Seagull | The Plant Cytoskeleton, Reference Module in Food Science[END_REF]. Lignin formation has been extensively studied as part of xylem differentiation. Lignin is a polyphenolic polymer generated by the radical coupling of aromatic monolignol, which is oxidized by ROS-dependent PRXs (PRX72 and PRX17) and laccases (LAC4) [START_REF] Tsukagoshi | Control of root growth and development by reactive oxygen species[END_REF][START_REF] Fujita | SCHENGEN receptor module drives localized ROS production and lignification in plant roots[END_REF]Hoffmann et al., 2020). In addition, a putative role of ROS as a lignification regulator is derived from the roles of these PRXs acting during xylem development. The cationic peroxidase from Zinnia elegans (ZePRX) catalyzes the last step of lignification in Zinnia elegans. The ortholog in A. thaliana, PRX72, is upregulated in the xylem vessel elements, suggesting a role in xylem formation. In prx72 mutants, lignin levels were 40% less than in the WT. It has been observed that PRX72 expression is increased in the lac4 lac11 lac17 triple mutants, implying a possible functional linkage between PRXs and LACs during monolignol coupling [START_REF] Zhao | LACCASE is necessary and nonredundant with PEROXIDASE for lignin polymerization during vascular development in Arabidopsis[END_REF]. However, increased PRX72 expression is not sufficient to rescue the lignin defect in the triple mutant, indicating that LACs and PRXs can still have distinct or complementary roles during monolignol assembly (Rojas-Murcia et al., 2020). Moreover, PRX17 is also involved in lignified tissue formation (Figure 2) and, more precisely, in regulating the kinetics of lignified wall formation [START_REF] Herrero | Bioinformatic and functional characterization of the basic peroxidase 72 from Arabidopsis thaliana involved in lignin biosynthesis[END_REF]Hoffmann et al., 2020). Its corresponding lossof-function mutant, prx17, has lower lignin content in most organs, whereas xylans were overaccumulated in the PRX17 overexpressor compared with the WT. Additionally, three MYBPLANT motifs have been localized in the PRX17 promoter; MYBPLANT-binding sites specify the expression of genes in lignifying cells (Cosio et al., 2017). However, it remains puzzling whether PRX17 acts directly in vessel lignification or indirectly via ROS signaling.

ROS & root endodermis

Root endodermis is the innermost cortical layer that surrounds the vascular stele in the root that resembles a polarized epithelium and functions in nutrient uptake and stress resistance. The development and differentiation of this layer are triggered by both intrinsic and extrinsic cues such as abiotic stresses, nutritional signals, and abscisic acid (ABA)-dependent metabolism (Lee et al., 2013). Its primary function is to form a selective barrier that filters the passage of the soil-absorbed water, solutes, and nutrients into the plant's transporting vessels. This vital role is acknowledged to the hydrophobic coating of lignified Casparian strips (CSs) and its suberin lamellae [START_REF] Cohen | SUBERMAN regulates developmental suberization of the Arabidopsis root endodermis[END_REF]. CSs have belt-like structures middling the anticlinal cell walls of the endodermal cells. They seal the extracellular spaces by tying the cell walls between adjacent cells [START_REF] Franke | Caspary's conductor[END_REF]. CS formation is tightly regulated by ROS and their mediated enzymes RBOHs and PRXs (Figure 3). Nevertheless, the regulatory mechanisms underlying the endodermal selectivity are still under investigation.

In Arabidopsis, CS formation sites are determined by the localization of the transmembrane protein family, CS membrane domain proteins (CASPs). CASPs are explicitly expressed in the endodermis (Li et al., 2018a[START_REF] Li | Spatial expression and functional analysis of casparian strip regulatory genes in endodermis reveals the conserved mechanism in tomato[END_REF] and localize specifically at the Casparian strip membrane domain (CSD) [START_REF] Barbosa | The Casparian strip-one ring to bring cell biology to lignification?[END_REF], where CASP1 guides CS-specific localization by interacting with two receptor-like kinases SCHENGEN1 (SGN1) and SCHENGEN3 (SGN3) [START_REF] Alassimone | Polarly localized kinase SGN1 is required for Casparian strip integrity and positioning[END_REF]. CASPs act as a transmembrane scaffold [START_REF] Barbosa | The Casparian strip-one ring to bring cell biology to lignification?[END_REF] and coordinate the proper localization of the different actors of the lignin-polymerizing machinery: RBOHF, PRX64, and ENHANCED SUBERIN 1 (ESB1) at the CSD (Li et al., 2018a (Lee et al., 2013;[START_REF] Franke | Caspary's conductor[END_REF].

Moreover, MYB36 has been revealed to regulate the expression of CASPs, PRX64, and ESB1 [START_REF] Kamiya | The MYB36 transcription factor orchestrates Casparian strip formation[END_REF]. Loss-of-function mutants, myb36, show deficit CS and hence lose the apoplastic barrier in this region of the root. Beforehand, during the endodermal differentiation, MYB36 expression is driven by the interaction of two upstream TFs, SHORTROOT (SHR) and SCARECROW (SCR). SHR and SCR are responsible for the initial specification of endodermal cell identity [START_REF] Liberman | MYB36 regulates the transition from proliferation to differentiation in the Arabidopsis root[END_REF][START_REF] Li | Spatial expression and functional analysis of casparian strip regulatory genes in endodermis reveals the conserved mechanism in tomato[END_REF] the overall lignin content was reduced in both lac and prx mutants [START_REF] Pfister | A receptor-like kinase mutant with absent endodermal diffusion barrier displays selective nutrient homeostasis defects[END_REF][START_REF] Von Wangenheim | Plant biology: building barriers in roots[END_REF][START_REF] Wunderling | A molecular framework to study periderm formation in Arabidopsis[END_REF]. However, the role of LACs in the endodermis and whether some cell types preferentially use LACs and others PRXs were addressed recently (Rojas-Murcia et al., 2020). In fact, the CS was devoid in the quintuple mutant prx03 prx09 prx39 prx72 prx64, while it showed no difference in the lac1 3 5 7 8 9 12 13 16 nonuple mutant compared with the WT. Together, these findings suggest that PRXs play very specific roles in various contexts, and LACs are redundant for lignification of primary cell walls but are required for lignification of secondary cell walls (Rojas-Murcia et al., 2020). Additionally, other RBOH and PRX enzymes are also known to be involved in ROS homeostasis and cell wall remodeling in the endodermis, including apoplastic RBOHD, PRX37, and PRX72. PRX37 participates in phenolic "cross-linking" activity during lignin deposition [START_REF] Pedreira | The overexpression of AtPrx37, an apoplastic peroxidase, reduces growth in Arabidopsis[END_REF], and PRX72 is involved in lignin biosynthesis when plant growth has ceased (Figure 2) [START_REF] Kim | A peroxidase contributes to ros production during Arabidopsis root response to potassium deficiency[END_REF][START_REF] Ferna ´ndez-Pe ´rez | The suppression of AtPrx52 affects fibers but not xylem lignification in Arabidopsis by altering the proportion of syringyl units[END_REF]Tognetti et al., 2017;[START_REF] Fujita | SCHENGEN receptor module drives localized ROS production and lignification in plant roots[END_REF].

ROS & root hair

Presence of root hairs marks the DZ of the primary root and is among its exhaustively studied features. In fact, root hairs are tube-like extensions projecting from single specialized epidermal cells. They massively increase the surface area of the root and hence improve its absorption potential of water and soil-borne nutrients. ROS play a critical role in root hair development [START_REF] Sundaravelpandian | PFT1-controlled ROS balance is critical for multiple stages of root hair development in Arabidopsis[END_REF][START_REF] Zhao | The LIKE SEX FOUR2 regulates root development by modulating reactive oxygen species homeostasis in Arabidopsis[END_REF][START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF]Choudhary et al., 2020). In Arabidopsis, RBOHC is the key enzyme responsible for root hair elongation under ROS regulation although RBOHH and RBOHJ also contribute to a much lower extent [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF]. RBOHC actively produces superoxide, and the hydroxyl radicals formed downstream of superoxide are the specific ROS that stimulates root hair elongation [START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF], and expectedly, rbohc mutants has much shorter root hairs than the WT [START_REF] Foreman | Reactive oxygen species produced by NADPH oxidase regulate plant cell growth[END_REF]. ROS stimulate ROS-dependent calcium gates, creating a Ca 2+ gradient from the tip inward. This gradient drives the apical elongation of the root hair [START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF]. RBOHC trafficking, transport to its correct subcellular compartment, and localization are complex processes regulated by the receptor-like kinase FERONIA (FER) and members of the Rho family of plant GTPases (ROP) [START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF]. The FER extracellular domain binds to the pectin components of the cell wall and activates Ca 2+ channels that maintain the integrity of the cell wall during growth. fer and rbohc mutants possess similar phenotypes, with short root hairs and decreased ROS accumulation. Pull-down assays that map protein-protein interactions suggest that FER interacts with ROP2, promoting radical hair growth upstream of RBOHC [START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF]. Another actor on the ROS homeostasis during root hair development is the LIKE SEX FOUR 2 (LSF2) gene encoding a phosphatase. This gene was identified for its novel role in redox regulation [START_REF] Zhao | The LIKE SEX FOUR2 regulates root development by modulating reactive oxygen species homeostasis in Arabidopsis[END_REF]. lsf2 Arabidopsis mutants showed lower superoxide generation rate but higher levels of hydrogen peroxide upon oxidative stress treatments. LSF2 interacts with the mitogen-activated protein kinase 8 (MPK8) which regulates the cytosolic redox balance [START_REF] Zhao | The LIKE SEX FOUR2 regulates root development by modulating reactive oxygen species homeostasis in Arabidopsis[END_REF]. Besides RBOHC, another component of ROS signaling in growing root hair is the OXIDATIVE BURST INDUCIBLE1 (OXI1) kinase. OXI1 is a Ser-Thr kinase, which plays a role in elongation of root hairs. It was proposed that RBOHC-mediated ROS lead to the activation of a MAPK cascade through OXI1 during cell elongation of root hairs (Figure 3) [START_REF] Rentel | OXI1 kinase is necessary for oxidative burst-mediated signalling in Arabidopsis[END_REF].

Moreover, auxin triggers a higher ROS level in the root hairs and enhances their growth by ROOT HAIR DEFECTIVE SIX LIKE4 (RSL4) activation [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF]. RSL4 encoding a bHLH TF has been identified as a vital regulator of root hair development [START_REF] Yi | A basic helix-loop-helix transcription factor controls cell growth and size in root hairs[END_REF][START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF][START_REF] Pires | Recruitment and remodeling of an ancient gene regulatory network during land plant evolution[END_REF]. Furthermore, it is known that the expression of RSL4 is controlled by several auxin response factors (ARFs), including ARF5, ARF7, ARF8, and ARF19; this ARF-RSL network can induce localized ROS synthesis (Figure 3), promoting the development of root hairs [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF][START_REF] Mangano | How does pH fit in with oscillating polar growth[END_REF][START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF]. Moreover, in addition to RBOHC, the key enzyme involved in root hair growth RBOHH and RBOHJ have been identified as important enzymes in this process. These RBOHs have root hair cis-elements (RHE) in their genes' promoters highly similar to the RSL4 response elements (RSL-RE). It was suggested that RSL4 binds at least one RHE region in the RBOHC and RBOHJ promoters and hence directly regulates their expression [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF]. In parallel, among the thirty-four putative targets of RSL4, PRX07 has been identified which codes the PRXs required for root hair elongation (Vijayakumar et al., 2016). PRX regulatory regions include several putative RHE motifs. Chromatin immunoprecipitation (ChIP) experiment indicated that RSL4 can bind to the RHE in the regulatory region of PRX01, PRX44, PRX60, and PRX73. Consistently, PRX01 and PRX73 were upregulated in the overexpressors of RSL4 and downregulated in rsl4 mutants [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF]. It is proposed that the phenotypes observed for peroxidase null mutants, especially prx01, prx44, and prx73, are due to their participation in root hair growth and ROS homeostasis (Figure 3) [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF]. These three genes in turn are highly coexpressed with other root hair-specific genes such as extensins and glycoproteins, which jointly participate in the expansion of the cell wall [START_REF] Mangano | How does pH fit in with oscillating polar growth[END_REF][START_REF] Marzol | Class III peroxidases PRX01, PRX44, and PRX73 potentially target extensins during root hair growth in Arabidopsis thaliana[END_REF]. Double mutants prx44 prx73, prx01 prx44, and prx01 prx73, as well as the triple null mutant, prx01 prx44 prx73, showed shorter root hairs, possibly due to the high accumulation of H 2 O 2 in the apoplast, affecting ROS homeostasis, the root hair growth, and the thickness of the cell wall [START_REF] Marzol | Class III peroxidases PRX01, PRX44, and PRX73 potentially target extensins during root hair growth in Arabidopsis thaliana[END_REF]. ROOT HAIR DEFECTIVE SIX LIKE 2 (RSL2), a close relative of RSL4, is also involved in root hair growth in an ROS-dependent manner involving PRXs and RBOHC enzymes, suggesting that RSL2-RSL4 may act together to regulate ROS homeostasis [START_REF] Mangano | Molecular link between auxin and ROS-mediated polar growth[END_REF][START_REF] Mangano | How does pH fit in with oscillating polar growth[END_REF]. In addition, the subunit of the mediator complex PHYTOCHROME AND FLOWERING TIME1 (PFT1)/MED25 triggers H 2 O 2 production by the upregulation of a subset of PRX expression and regulates the equilibrium between H 2 O 2 and during root hair differentiation and cell elongation [START_REF] Sundaravelpandian | PFT1-controlled ROS balance is critical for multiple stages of root hair development in Arabidopsis[END_REF].

ROS & lateral roots

Plants have the capacity of the de novo development of new organs in which new cells are enrolled in the formation of primordia organs [START_REF] Ferna ´ndez-Marcos | Control of Arabidopsis lateral root primordium boundaries by MYB36[END_REF]. Lateral roots (LRs) serve as an example of this feature and choreograph the dynamic architecture of the root system. LRs enhance the absorption of water and nutrients from the neighboring soil environment. They also contribute to the root acclimation to various biotic and abiotic constraints. LRs are intrinsically diverse as they have contrasted morphologies and anatomies, such as having different lengths and orientations [START_REF] Muller | Lateral roots: random diversity in adversity[END_REF]. LRs are initiated when pericycle founder cells undergo several rounds of anticlinal divisions to create one-layered primordia of about ten equal cells; this is termed stage I. Next, the cells divide periclinally, forming an inner and an iScience Review outer layer denoting stage II. Further anticlinal and periclinal divisions create dome-shaped primordia (stages III-VII) that eventually emerge at stage VIII from the parental root [START_REF] Malamy | Organization and cell differentiation in lateral roots of Arabidopsis thaliana[END_REF][START_REF] Pe ´ret | Arabidopsis lateral root development: an emerging story[END_REF][START_REF] Banda | Lateral root formation in arabidopsis: a well-ordered LRexit[END_REF]. In fact, the establishment of lateral root primordia (LRP) from the root pericycle is auxin dependent. These LRPs further develop into LRs by orchestrated divisions of the lateral root founder cells (Ferna ´ndez-Marcos et al., 2017).

Redox signaling is notably involved in LR development by a complex genetic network that has been thoroughly studied [START_REF] Manzano | The emerging role of reactive oxygen species signaling during lateral root development[END_REF][START_REF] Reyt | Iron-and ferritin-dependent reactive oxygen species distribution: impact on arabidopsis root system architecture[END_REF][START_REF] Orman-Ligeza | RBOH-mediated ROS production facilitates lateral root emergence in Arabidopsis[END_REF]. First, SKP2B (S-phase kinase-associated protein2), a marker for LR development, is coexpressed with many ROS-related genes.

UPB1 is transcriptionally enriched during the early stages of LRPs, and ROS significantly accumulate in the emerging LR. In addition, plants overexpressing UPB1 have more LRPs in stages IV and V. However, in stage VIII, when LRPs emerge from the epidermis, their number was significantly reduced in the UPB1 overexpressors. Coherently, upb1 mutants had more emerging LRs than WT [START_REF] Manzano | The emerging role of reactive oxygen species signaling during lateral root development[END_REF]. UPB1 controls the expression of a subset of PRX genes that manipulate the ROS balance (Figure 3). Altogether, this suggests that ROS play a role in the early development of LRPs. Moreover, a potassium cyanide treatment, which inhibits PRX activity, reduced LR emergence. Diaminobenzidine and nitro blue tetrazolium staining revealed, respectively, that H 2 O 2 and superoxide are present in all the developmental stages of LRs [START_REF] Manzano | The emerging role of reactive oxygen species signaling during lateral root development[END_REF].

In addition, auxin plays an important role in LR formation and consequently in choreographing the root system architecture (Petricka et al., 2012). To exemplify, modifying auxin distribution by nutrient availability, as iron (Fe), influences the LR elongation [START_REF] Giehl | Localized iron supply triggers lateral root elongation in Arabidopsis by altering the AUX1mediated auxin distribution[END_REF]. Also, Fe and ROS homeostasis are intimately linked, with ferritins as major actors in this interaction, which suggests a cross talk between ROS homeostasis and auxin distribution during LR development [START_REF] Reyt | Iron-and ferritin-dependent reactive oxygen species distribution: impact on arabidopsis root system architecture[END_REF]. Moreover, LR development is dependent on the interaction between auxin with other phytohormones, especially with ABA (Singh et al., 2016). Auxin and ABA functions antagonistically where the former triggers cellular expansion; however, the latter maintains a balance between proliferation and differentiation in the LRPs. Both hormones trigger ROS production by promoting cell expansion of growing roots. When indole acetic acid (IAA) is degraded by peroxidases, the formation of LRs is inhibited (Cosio et al., 2009;Choudhary et al., 2020). Furthermore, gpx mutants develop larger LRM, indicating that the GPx family plays a role in regulating root architecture, especially GPX01 and GPX07 that regulate LR development and formation (Figure 2) (Choudhary et al., 2020). Furthermore, two RBOHs from Arabidopsis, RBOHD and RBOHF, are suggested to negatively regulate LRP formation and LR emergence, which may be explained by the decrease in peroxidase activity (Li et al., 2014). Initially, these two RBOH genes are known to be expressed in the vascular cylinder and LRP in primary roots. LR number and density significantly increase in their corresponding loss-of-function double mutant rbohd/f [START_REF] Li | AtrbohD and AtrbohF negatively regulate lateral root development by changing the localized accumulation of superoxide in primary roots of Arabidopsis[END_REF]. In fact, this mutant has lower H 2 O 2 concentration and generation rate in the root cap, MZ, EZ, and DZ than the WT. Similarly, it has lower O 2 .

-concentration and generation rate in the root cap, MZ, and EZ, but not in the DZ. Surprisingly, it produces more superoxide than the WT in the DZ, which enhances the LR density. This increase in LR density in the mutant is credited to the enhanced peroxidase activity in the DZ of the rbohd/f mutant. In fact, the peroxidase activity in rbohd1/f1 and rbohd2/f2 were higher than in the WT [START_REF] Li | AtrbohD and AtrbohF negatively regulate lateral root development by changing the localized accumulation of superoxide in primary roots of Arabidopsis[END_REF]. In addition, it was observed that an rbohe loss-of-function mutant delays the development of the LR. Through the use of the b-glucuronidase (GUS) reporter gene staining, an accumulation of RBOHE is observed at the starting site of the LR, showing the possible participation of this enzyme in its development (Figure 2) [START_REF] Chapman | RBOH-dependent ROS synthesis and ROS scavenging by plant specialized Metabolites to modulate plant development and stress responses[END_REF].

Additionally, MYB36, a previously identified advocate in CS formation during endodermal differentiation [START_REF] Kamiya | The MYB36 transcription factor orchestrates Casparian strip formation[END_REF][START_REF] Liberman | MYB36 regulates the transition from proliferation to differentiation in the Arabidopsis root[END_REF], was also identified as an actor in LR development [START_REF] Ferna ´ndez-Marcos | Control of Arabidopsis lateral root primordium boundaries by MYB36[END_REF]. Initially, MYB36 protein was revealed to accumulate in the root endodermis. Its overexpression leads to shorter primary roots, whereas three allelic myb36 mutants develop longer roots [START_REF] Ferna ´ndez-Marcos | Control of Arabidopsis lateral root primordium boundaries by MYB36[END_REF]. This phenotype results from the increase in the number of cells in the meristem, where ROS balance is known to regulate the meristematic boundaries [START_REF] Kamiya | The MYB36 transcription factor orchestrates Casparian strip formation[END_REF][START_REF] Liberman | MYB36 regulates the transition from proliferation to differentiation in the Arabidopsis root[END_REF]. The new role of MYB36 in LR development was first discovered in 2017 [START_REF] Ferna ´ndez-Marcos | Control of Arabidopsis lateral root primordium boundaries by MYB36[END_REF]. Two allelic mutants of myb36 had less LRs than the WT. A spatiotemporal tracking of the expression pattern of this gene showed that it was not expressed in the endodermal cells adjacent to the LRPs. However, it was cell-autonomously enriched in the lateral root primordia boundary (LRPB) at stage V of the LR development. LRPs in the two mutants were flat, and they failed to form into domes and hence failed to penetrate the overlying cellular layers. Further spatiotemporal analyses of the expression pattern of iScience Review MYB36 and its corresponding PRX targets confirmed that MYB36 acts in stages V and VI of LR development, by manipulating the ROS balance via the regulation of at least PRX09 and PRX64 (Ferna ´ndez-Marcos et al., 2017). Finally, supplementary forward genetics approaches identified another ROS-related genetic basis affecting the LR phenotype. PRX07 and PRX57 were explicitly identified as the actors in LR growth among other peroxidases (Figure 2) since prx07 and prx57 mutants have lower LR density owing to changes of ROS balance in the initiation stage. Interestingly, despite that LRP establishment depends on auxin, PRX07 and PRX57 were detected to be auxin-independent [START_REF] Manzano | The emerging role of reactive oxygen species signaling during lateral root development[END_REF]. Together, all these studies highlight the importance of ROS homeostasis in shaping and growing LRs.

DECODING ROS SIGNAL

As demonstrated above, ROS production and scavenging naturally takes place in various cellular compartments and is surveilled by the profound ROS gene network to maintain their homeostasis [START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF][START_REF] Singh | Reactive oxygen species (ROS): beneficial companions of plants' developmental processes[END_REF][START_REF] Mittler | ROS are good[END_REF]. It is worth noting that ROS do not occur in isolation but rather as part of a large and complex redox signaling that involves many components. However, the different ROS levels in the different cellular compartments may be contemplated as ROS signatures in resemblance to the famous Ca 2+ signature. In fact, Ca 2+ signaling is implicated in countless cellular activities, where varying spatiotemporal distribution, vibration amplitude, and frequency of Ca 2+ determine a distinct signature. This specific signature, triggered by a particular stimulus, results in a precise adaptive response [START_REF] Yuan | Calcium signatures and signaling events orchestrate plant-microbe interactions[END_REF]. As for ROS, different natures and intensities of stimuli lead to the formation of ROS signatures, which are decoded by ROS sensors to generate a stimulus-specific signal, and consequently to customize an acclimation response in the plant cell. This signature varies in compliance with the cell type, developmental stage, and environmental status (Choudhury et al., 2017), and its decoding can alter protein structures or functions via PTMs. For instance, these alterations can affect TFs leading to modifications in their transcription [START_REF] Dietz | Recent progress in understanding the role of reactive oxygen species in plant cell signaling[END_REF].

This concept is exceptionally important, as it explains how plants are able to decrypt different ROS signals provoked by, chemically, the same molecules, and then elaborate a specific response to each particular signature (Choudhury et al., 2017). It is notable how these ROS-producing or ROS-scavenging machineries are copresent simultaneously within cells or even organelles in widely ranging proportions and activities.

What turns them on or off remains an intriguing question. They are surely dependent on the ambient O 2 concentration and on the exogenous environmental cues. Furthermore, they are also dependent on the cell type, localization, and status, which is subsequently depending on the gene expression pattern. Thus, an optimal pattern of oxidants and antioxidants exists for a given physiological condition [START_REF] Sies | Oxidative stress[END_REF].

CONCLUSION

Recent studies investigated the vital roles of ROS in plant root developmental processes. In summary, during cell proliferation, ROS concentrations regulate the cell cycle since oxidative bursts can block cyclin expression. In the MZ, ROS act to conserve the stem cell niche in the QC, hence allowing a sustained growth of the root. In the EZ, apoplastic ROS balances determine the elongation rates of cells in the root EZ. In fact, apoplastic ROS can promote either PCW stiffening or loosening, by catalyzing either the cross-links between PCW components or their oxidative cleavage, respectively. At the transition zone, ROS balances give preference to either proliferation or differentiation according to UPB1 regulation. These aforementioned mechanisms reveal a vital role of ROS during the plant root primary growth. Moreover, ROS are involved in modulating the differentiation stage of development at multiple levels. In the tracheary elements, ROS regulate xylem lignification by the functioning of the ROS-producing enzymes, PRX72 and PRX17. Similarly, PRX64 and RBOHF are essential for the proper formation of the CS in the root endodermis. In addition, in the epidermis, ROS trigger cell growth in root hairs. Last but not least, numerous ROS-related genes are implicated in LR formation. ROS production and scavenging are two co-occurring processes that are minutely adjusted to maintain the manifold ''ROS homeostasis'' [START_REF] Mittler | Reactive oxygen gene network of plants[END_REF][START_REF] Suzuki | ROS and redox signalling in the response of plants to abiotic stress[END_REF][START_REF] Mittler | ROS are good[END_REF][START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF]). This homeostasis is essential for regulating the multiple stages of plant root development and hence choreographing the final root architecture. Furthermore, this redox balance is central to life since redox practices encompass all fundamental processes, from bioenergetics to metabolism and life functions [START_REF] Sies | Oxidative stress[END_REF]. In our scope, ROS homeostasis has been shown as a requisite for proper root growth [START_REF] Tsukagoshi | Control of root growth and development by reactive oxygen species[END_REF]Choudhary et al., 2020), development [START_REF] Mhamdi | Reactive oxygen species in plant development[END_REF], and response to stimuli (Miller et al., 2010;Liu and He, 2016;Zhang et al., 2016). In view of the above, ROS of underground plant cells are multitaskers in root development.

FUTURE KEY ISSUES

a. Apoplastic ROS-sensing mechanism by cell surface receptors has been recently proposed to be mediated by HPCA1 [START_REF] Laohavisit | Quinone perception in plants via leucine-richrepeat receptor-like kinases[END_REF][START_REF] Wu | Hydrogen peroxide sensor HPCA1 is an LRR receptor kinase in Arabidopsis[END_REF]. The downstream post-translational modifications relative to the kinase domain of CARD1/HPCA1 were also described. However, the further detailed downstream signaling components still to be identified. [START_REF] Spagnoli | Detecting climate change at a regional scale: the case of France[END_REF]. Also, its mountainous nature represents a privileged research site as it extends up to 2000 m in altitude, which provides a natural gradient of climatic conditions such as temperature, precipitation, soil salinity, and radiation.

First, this chapter summarizes the previous studies performed on the Pyrenean collection of A.

thaliana. In fact, these populations were formerly characterized via integrative analysis combining genetic, phenotypic variation, and environmental datasets to study their acclimation in response to temperature changes, with a focus on their aerial parts (Duruflé et al. 2019).

Next, this chapter details the state-of-the-art experiments conducted to study the populations' responses to both thermal and saline stresses, with particular focus on their root development. In short, roots have displayed enormous plasticity between the various growth conditions and between the different populations. Furthermore, the transcriptional regulation behind the phenotypic variations has been thoroughly exploited, with particular focus on the cell wall and ROS gene regulatory networks comprising the class III peroxidase family.

Previous Work Recap

Geographical and Climatic Mapping

Thirty natural populations of A. thaliana were sampled from different sites in the French Pyrenees (Figure 10). A four-lettered acronym was asserted to each population corresponding to the closest location of its collection site. Their geographical and climatic distributions were determined using a geographic coordinate system. The latitude, longitude, and altitude of their collection sites were registered, and five climatic variables (annual minimum, annual maximum, and annual mean temperatures (°C), total annual precipitation (mm), and total annual UV radiations (kWh/m2)) were used to characterize their local environments (Table 2). Using principal component analysis, the altitude and the five climatic parameters were integrated into one principal component (Climate PC1) which retains 74% of the multivariate variance across the six variables. PC1 is majorly negatively correlated with the altitude but with numerous exceptions. For instance, Eaux has a lower climate PC1 (0.5) than other populations living at the same altitude such as Savi or Bier (1.5) due to the existence of lower temperatures at its location (Table 2).

Table 2:

The geographic localization of the studied Pyrenean A. thaliana populations and the climatic parameters of their collection sites calculated from the monthly data of the WorldClim project (annual minimum, mean, and maximum temperatures and annual precipitation). The annual UV radiation was obtained from the Photovoltaic Geographical Information System of the European Community. Climate PC1 values are the position of populations on the first principal component of the PCA of bioclimatic variables that allows to classify populations in function of their environmental conditions (Duruflé et al. 2019).

Phenotypic Variation of the Aerial Parts in Response to Cold Conditions

The rosettes, stems, and other physiological traits of the Pyrenean populations were phenotyped under different conditions. To illustrate, the number of leaves per rosette, the mass and the diameter of the rosettes, the time to reach bolting, the chlorophyll and anthocyanin contents, the number of cauline leaves, the length and the diameter of the stem, and the stem's growth speed were measured at optimal (22°C) and cold temperatures (15°C).

Generally, plants developed more leaves and heavier and larger rosettes at 15°C compared to 22°C.

Similarly, they faster developed longer and thicker stems with more cauline leaves at 15°C. However, these general phenotypes were different between populations, where several developed remarkable phenotypes. For instances, Bran had smaller rosette, and Pont had a lighter one at 15°C. Also, Hern and Prad had less cauline leaves, and Biel had shorter stems at 15°C rather than 22°C. Additionally, the chlorophyll content segregated the populations into two groups. Some populations such as Mere, Chau, Eget, Bran, and Biel had more chlorophyll at 15°C relative to 22°C, while others such as Cast, Hosp, Prad, Roch, and Hern displayed the opposite phenotype. Moreover, anthocyanin quantification, which is a stress-tolerance indicator, revealed that most populations accumulated more anthocyanin at 15°C, with remarkable increase in Eaux, Jaco, and Argu.

Altogether, these results reveal the phenotypic variations of A. thaliana Pyrenean populations in response to cold stress. They enrich our knowledge of how natural populations may adapt to abiotic constraints and highlight the fact that plant-environment interactions involve complex and interconnected processes. However, further analyses are yet to be done to decipher the underlying molecular regulations of such adaptational responses.

Materials and Methods

RNA sequencing

RNA sequencing (RNA-seq) was adopted as a high-throughput technique to study the whole transcriptome of selected samples. It combines high-throughput sequencing of complementary DNA (cDNA) libraries, which are reversely transcribed from isolated RNA, with computational methods to capture and quantify transcripts present in an RNA extract. RNA-seq is a multistep process involving reverse transcription, amplification, fragmentation, purification, adaptor ligation, and sequencing. With the availability of genomic sequence, transcripts can be identified by aligning the RNA-seq reads onto the genome. The read counts, which are the number of mapped reads on a particular genomic region, are then used to calculate the relative gene expression (Conesa et al. 2016). In this study, the RNA samples were prepared at the laboratory. Their quality control, library preparations, and sequencing were performed by GENEWIZ in Leipzig, Germany. The obtained data were delivered in FASTQ raw files and were analyzed in the laboratory.

Quality Control

The working pipeline begins with RNA extraction and purification. As RNA can be readily degraded by the ubiquitous ribonuclease enzymes, its integrity, quality, and quantity are to be assessed. Many techniques have been adopted to assess the RNA quality; however, the most automated and stringent quality control is done in high-tech laboratories via capillary electrophoresis (CE) using fragment analyzers (Qi et al. 2017) (Figure 11).

The outcome of the CE is summarized in an electropherogram that represents the size distribution of the RNA sample along its x-axis and the relative fluorescence unit (RFU) reflecting the RNA quantity along its y-axis. A lower marker (LM) is introduced to the samples as sizing reference. The LM peak is labeled on the graph, whereas the pink and blue peaks correspond to the 18S and 28S ribosomal subunits, respectively; also, further peaks are detected and marked by vertical red lines. All the detected peaks are characterized in the peak table by their size (nt), concentration (ng/µL), nucleotide length (From and to (nt)), and the relative molarity (nmole/L). Moreover, the total integrated concentration (TIC) measures the concentration (ng/µL) of all detected peaks; the total integrated molarity (TIM) measures the molarity of all detected peaks (nmole/L); the total concentration measures the total concentration of the sample (ng/µL); and the 28S/18S ratio measures the ratio of the pink and blue peaks. Moreover, the RNA integrity or quality number (RIN or RQN) has been adopted to measure the quality of RNA. It integrates the area before the 18S peak, the total area of the 18S and 28S peaks, and the ratio of the 28S and 18S peaks. A good RNA sample for sequencing has an RQN greater than 8 [START_REF] Wang | Measure transcript integrity using RNA-seq data[END_REF]) (Figure 12).

Library Preparation and Sequencing

RNA-seq experiments are usually conducted to study the expression of genes involved in various biological processes between different groups or treatments. However, the extracted total RNA contains >85% of ribosomal RNA (rRNA), and hence most of the resulting reads will be associated to rRNA. Accordingly, it is essential to enrich targeted classes of RNAs prior to sequencing. For instance, messenger RNA (mRNA) species can be fished by hybridizing their poly-A tails using oligo-dT baits [START_REF] Kraus | Efficient and specific oligo-based depletion of rRNA[END_REF].

To prepare cDNA libraries, the enriched RNA samples are reversely transcribed into double stranded complementary DNA (ds-cDNA) using reverse transcriptase enzymes. Then, sequencing adaptors containing many elements necessary for sequencing are ligated to the ds-cDNA; these adaptors provide amplification elements and primary sequencing priming sites necessary for the clonal amplification and the initiation of the sequencing reaction. Afterwards, the cDNA libraries are sequenced at a sufficient sequencing depth to ensure the coverage of scarce transcripts; in parallel, paired-end sequencing can be used to increase the transcript coverage [START_REF] Zhong | Highthroughput illumina strand-specific RNA sequencing library preparation[END_REF]).

Computational Analysis

Sequences Preparation

The initial step in RNA-seq analysis is to process the sequencing reads to enhance their quality. This is achieved by quality-based trimming of reads which determines which reads are retained for subsequent analysis. First, reads are trimmed according to their quality scores which measure the probability that a base is called incorrectly; a threshold of quality limit can be parameterized.

Second, ambiguous nucleotides (N), which define unknown nucleotides in the sequencing, are removed. Additionally, the ligated sequencing adaptors are also trimmed from the reads to avoid misleading results. The obtained trimmed reads can be further filtered by their lengths by which very short can be discarded [START_REF] Williams | Trimming of sequence reads alters RNA-Seq gene expression estimates[END_REF]).

Mapping and Alignment

Afterwards, the processed reads are mapped against a reference cDNA library. The alignment algorithm anticipates the biological events that occur to the nucleotide, which are conservation, substitution, deletion, and insertion. Conservations of nucleotides are scored as matches, substitutions as mismatches, while deletion and insertion as gaps. The adjustment of these cost scores can enhance the mapping of the reads to the reference cDNA library. Also, length and similarity fractions can be parameterized to set thresholds for the minimum percentage of the total alignment length that must match the reference sequence at the selected similarity fraction and for the minimum percentage identity between the aligned region of the read and the reference sequence, respectively. Moreover, the maximum number of hits for a read determines the number of distinct sites in the reference genome to which a matching read can map (Liu and Di 2020).

Expression Analyses Within-Sample

The count of mapped reads on a gene in the alignment reference reflects the level of expression of this gene. However, the read counts cannot be directly used to assess the gene expression prior to normalization because of the bias created by the sequencing depth, which is reflected on the coverage of mapped reads. To illustrate, if two genes are biologically equally expressed, but the reads corresponding to the first gene are sequenced at depth X while those of the other gene at depth 2X, then the second gene will be falsely detected as upregulated. Additionally, another layer of bias is added due to the differences in the gene lengths (number of base pairs constituting the gene sequence), where longer genes are expected to produce more reads than shorter genes [START_REF] Oshlack | From RNA-seq reads to differential expression results[END_REF]. Therefore, normalization of read counts is an indispensable step to represent realistic gene expression [START_REF] Evans | Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions[END_REF].

In fact, various variables have been developed to normalize gene expression within-sample such as RPKM (reads per kilobase million) and TPM (transcripts per million). To calculate the RPKM of a gene, the number of the total reads in a sample is divided by million to obtain the per-million scaling factor; then, the read counts are divided by the per-million scaling resulting in RPM (reads per million), and then RPMs are divided by the gene length, which normalize the sequencing depth and the gene length, respectively [START_REF] Mortazavi | Mapping and quantifying mammalian transcriptomes by RNA-Seq[END_REF].

In turn, the TPM is currently proposed as a more convenient alternative to RPKM as it facilitates the comparison of mapped reads in each sample. It designates that for every one-million RNA molecule, a certain number (TPM) originates from a certain gene. The same computation as in RPKM is performed in TPM but with reversed order, where the read counts are normalized for the gene length prior to the sequencing depth. To illustrate, the read counts are divided by the length of each gene resulting in RPK (reads per kilobase); then, the total RPKs are divided by million to obtain the per-million scaling factor; finally, the RPK values are divided by the per-million factor to obtain TPM [START_REF] Wagner | Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples[END_REF]).

Expression Analyses across Samples

The ultimate goal of RNA-seq experiments is to highlight the contrasted expression of genes between different groups or treatments. In fact, a flexible statistical framework has been established

to analyze the read counts and to perform multileveled comparisons in experiments involving manifold treatments and variables. In this context, the generalized linear model (GLM) has been widely adopted to analyze RNA-seq data, where read counts are assumed to follow a negative binominal distribution (McCarthy et al. 2012). Moreover, TMM (trimmed mean of m-values) is used as a normalization method for the library sizes across samples.

The statistical testing of differential gene expression across samples is estimated by fold change associated with p-values [START_REF] Robinson | A scaling normalization method for differential expression analysis of RNA-seq data[END_REF]. Also, volcano plots are common tools that allow rapid visualization of differentially expressed genes (DEGs) over a coordinate system, where the x-axis represents the magnitude of fold change, and the y-axis represents its statistical significance (Figure 13). An alternative method to visualize differential expression is by heat maps that cluster samples and genes together according to the similarities of their expression profiles. Over the past decade, numerous studies have highlighted the dynamics of CWs in response to abiotic stresses. To illustrate, diverse CW genes revealed differential expression in response to cold, heat, and thermal stresses. For instances, a heat treatment upregulated genes coding for xyloglucan endotransglucosylase/hydrolases (XTH), arabinogalactan proteins, β-glucosidases, cellulose synthases, expansins, extensins, glycosyl transferases, pectin esterases and xylosidases in the primary CW of Chinese cabbage [START_REF] Yang | Identification of cell wall genes modified by a permissive high temperature in Chinese cabbage[END_REF]). These genes may subsidize heat-tolerance by CW remodeling which increases its elasticity and hence maintains the cellular functions. Similarly, in the secondary CW, a heat treatment enhanced the expression of laccase-coding genes which are involved in lignification [START_REF] Xu | Differential gene expression in shoots and roots under heat stress for a geothermal and non-thermal Agrostis grass species contrasting in heat tolerance[END_REF].

Moreover, CWs are adjusted in response to cold stress by modulating their polysaccharidic composition and the activity of their modifying enzymes [START_REF] Baldwin | Structural alteration of cell wall pectins accompanies pea development in response to cold[END_REF]. Also, alterations in the lignin content were observed at low temperatures leading to cell wall strengthening (Moura et al. 2010). Additionally, families of CW proteins were identified to play key roles in salt and drought stress perception [START_REF] Zagorchev | The role of plant cell wall proteins in response to salt stress[END_REF]. Further aspects that characterize CW plasticity under abiotic constraints were elaborately reviewed (Gall et al. 2015).

In fact, a repertoire of A. thaliana genes consisting of 1347 genes encoding cell wall proteins (CWPs), 259 genes encoding proteins involved in the CW biosynthesis, and 176 genes encoding proteins involved in lignin biosynthesis (Duruflé et al. 2017) was used to analyze the differential gene expression in the A. thaliana Pyrenean populations when exposed to various combinations of abiotic stresses

Reactive Oxygen Species Gene Regulatory Network

Reactive oxygen species (ROS) are currently recognized for their fundamental regulatory roles during plant development. They regulate a myriad of developmental processes such as the tip growth of cells in root hairs and pollen tubes, where they modulate the cell wall stiffening and loosening to prevent tip bursting [START_REF] Swanson | ROS in plant development[END_REF]. Furthermore, ROS are dominantly involved in choreographing the root growth in the different concentric tissues (epidermis, cortex, endodermis, pericycle, and vascular stele) and developmental zones (meristematic, elongation, and differentiation zones) (Choudhary et al. 2020;[START_REF] Mase | Reactive Oxygen Species Link Gene Regulatory Networks During Arabidopsis Root Development[END_REF][START_REF] Zhou | Modulatory role of reactive oxygen species in root development in model plant of Arabidopsis thaliana[END_REF]). During such complex processes, ROS interplay with other signaling pathways such as auxin and cytokinin hormonal regulatory pathways (Tognetti et al. 2017). Additionally, ROS have been characterized as key players in response to abiotic stresses such as heat-shock, hypoxia, cold, and salinity. Acting as signaling molecules, they trigger signal transduction in response to those stresses. They may even lead to programmed cell death (PCD) and hence confer resistance to stress [START_REF] Huang | Mechanisms of ROS regulation of plant development and stress responses[END_REF].

In fact, a repertoire of 295 A. thaliana genes related to ROS homeostasis has been previously constructed (Duruflé et al. 2017). This repertoire of ROS-related genes will be implemented to highlight the differential expression of ROS-related genes under abiotic constraints in both stress tolerant and susceptible A. thaliana Pyrenean populations. Moreover, this ROS toolbox was constructed by data mining from the PeroxiBase database (http://peroxibase.toulouse.inra.fr/).

Since 2004, the PeroxiBase has been specialized and dedicated to the peroxidases families, which are involved in several important physiological and developmental processes [START_REF] Passardi | PeroxiBase: the peroxidase database[END_REF]).

In 2017, the PeroxiBase was expanded into RedoxiBase (https://peroxibase.toulouse.inra.fr/) to cover, in addition to heme and non-heme containing peroxidases, other oxidoreductases compiling information about their functions and transcriptional regulation [START_REF] Savelli | RedoxiBase: A database for ROS homeostasis regulated proteins[END_REF]. For instances, RedoxiBase currently covers several oxidoreductase families such as the glutathione reductase (GR), alternative oxidase (AOX), ferritin (Fer), glycolate oxidase (GOX), dehydroascorbate reductase (DHAR), monohydroascorbate reductase (MDAR), the glutaredoxin (Grx) family and its subclasses (4CxxC, CGFS, CGYC, CPF, and ROXY), the thioredoxin (Trx) family and its types (APR, Clot, CxxS, Lilium, NRX, TDX, TrxF, TrxH, TrxM, TrxO, TrxX, and TrxY), the blue copper protein family and its subclasses (early nodulin (ENODL), plastocyanin (PC), uclacyanin (UCC), plantacyanin (PNC), stellacyanin (STC), and cupredoxin protein (CRX)), and the superoxide dismutase (SOD) family and its subclasses (copper chaperone for SOD (CCS), Mn SOD (MSD), Fe SOD (FSD), Cu/Zn SOD (CSD), and SOD like (SDL))

Class III Peroxidases Gene Expression Map

Peroxidases (Prxs) are majorly categorized into two classes: heme and non-heme. Thiol Prxs, glutathione Prxs (GPx), NADH Prxs (NadPrx), and peroxiredoxins are the major subfamilies of the non-heme Prxs [START_REF] Passardi | PeroxiBase: the peroxidase database[END_REF]). However, heme Prxs, which are characterized by the presence of conserved amino acid residues necessary for heme binding, are majorly viewed as two superfamilies: animal and non-animal Prxs. Subsequently, the non-animal Prxs are divided into three classes (I, II, and III). Class I Prxs include ascorbate Prxs (APxs) which are key enzymes in peroxide detoxification in plants [START_REF] Zámocký | Evolution of structure and function of Class I peroxidases[END_REF]. While class II Prxs are fungal enzymes necessary for plant lignin degradation [START_REF] Mathé | In silico definition of new ligninolytic peroxidase sub-classes in fungi and putative relation to fungal lifestyle[END_REF], class III Prxs are plant specific proteins belonging to a large multigenic family as a result of the increased gene duplication in vascular plants (Passardi et al. 2005).

Class III Prxs play numerous functions during plant development and stress response. The presence of 73 members of Prxs in A. thaliana suggests that each protein isoform may be attributed to a specific function. In fact, the diversified sequences in the Prx promoters suggest that their transcription is subjected to different regulatory pathways. Also, their protein sequences contain both conserved residues and domains such as those dedicated for heme-binding, as well as highly variable domains certainly implicated in substrate binding and functional specificity (Cosio and Dunand 2009).

Moreover, the specificity of the class III Prxs functions may be attributed to the spatiotemporal patterns of their gene expression and protein distribution. These transcriptomic and proteomic patterns have been extensively characterized via organ-specific profiling, subcellular localization, and cell-specific micro-transcriptomic studies (Francoz et al. 2015). At the organ level, Prxs transcription and enzymatic activity were spotted all over the plant but most importantly in roots, via the Geneinvestigator database (https://www.genevestigator.com/) and WallProtDB database (www.polebio.lrsv.ups-tlse.fr/WallProtDB/), respectively.

Furthermore, the establishment of gene expression map for Arabidopsis root localized the expression of more than 22000 genes in 15 cell-, tissue-, and developmental stage-specific zones.

Among these genes, 44 Prxs were successfully detected to be expressed in different root tissues between different developmental stages [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. Altogether, these findings characterize the gene expression map of Prxs and highlight their importance and putative functions at the whole plant level but most importantly in the roots. [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. The 5 concentric tissues are: stele, endodermis (Endo), endodermis and cortex (Endo+cortex), epidermis (Epi), and lateral root cap (Lrc). The 3 developmental stages are in the meristematic zone ( 1), the elongation zone ( 2), and the differentiation zone (3) [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF].

Table 3: Heat-map summary of the expression of 44 class III peroxidases that were detected in any of the 5 different primary tissues (Stele, endodermis (Endo), endodermis and cortex (Endo + cortex), epidermis (Epi), or lateral root cap (Lrc) in at least 1 of the 3 root developmental zones. The color code represents the magnitude of expression of all detected genes in each developmental zone increasingly in green, yellow, and red [START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. Grey corresponds to missing data 76 99.72 214.64 190.01 178.65 393.91 177.92 108.36 95.93 90.19 198.87

Introduction

Plants are exposed to continuously fluctuating environments, where they experience a myriad of challenging conditions that vary between seasons or even within one day [START_REF] Akpinar | Plant abiotic stress signaling[END_REF]Cramer et al. 2011;[START_REF] Zhu | Abiotic stress signaling and responses in plants[END_REF]. For instances, abiotic stresses such as abrupt temperatures and salinity negatively influence their health and survival [START_REF] Suzuki | Abiotic and biotic stress combinations[END_REF]. Because plants are sessile, they have developed multiple adaptive mechanisms to respond rapidly to such abiotic constraints [START_REF] Urano | Omics' analyses of regulatory networks in plant abiotic stress responses[END_REF]. With the arising threats of climate change, plants are expected to cope with more intensified occurrence and severity of abiotic stresses that may drastically affect their growth and development [START_REF] Baier | Preparing plants for improved cold tolerance by priming[END_REF]Hassan et al. 2021;Yang and Guo 2018).

Roots, the hidden half of the plant body, play main roles in anchoring plants into the soil, absorbing and conducting water and nutrients, in addition to interacting with their surroundings such as with neighboring plants (e.g., competition) and microorganisms (e.g., mycorrhization) (Petricka et al. 2012). Being in direct contact with the soil, roots are particularly subjected to adverse abiotic constraints and are prone to even higher damage than shoots. Additionally, root development and patterning follow intrinsic genetically programmed signals (Novoplansky 2019), but the growth rate and morphology are continuously adjusted in response to extrinsic environmental cues. These adjustments delineate the phenotypic plasticity of roots, which allow them to cope with adverse abiotic constraints (Novoplansky 2019;Simard 2018). Root plasticity relies on multi-leveled and overlapping molecular networks that have been extensively studied (Wachsman et al. 2015).

Plant cell walls contribute to the root plasticity as they display high flexibility and diversity during root development. In fact, their characteristics determine the structural and functional diversity of the radial tissue layers and of the axial developmental zones [START_REF] Somssich | Cell wall heterogeneity in root development of Arabidopsis[END_REF]. To exemplify, cell wall remodeling in the elongation zone allows the rapid expansion of cells [START_REF] Passardi | Two cell wall associated peroxidases from Arabidopsis influence root elongation[END_REF]).

In addition, cell walls are adjusted in response to environmental constraints by stiffening, loosening, or producing secondary cell walls (Tenhaken 2015). For instance, the tolerance to cold and salt stresses has been correlated to increased lignification which is underpinned by the lignin biosynthesis signaling and metabolic pathways in roots (Moura et al. 2010).

Furthermore, reactive oxygen species (ROS) have been broadly recognized as key players during root growth, where they regulate various developmental processes in different tissues and zones (Eljebbawi et al. 2021). Indeed, ROS were formerly known for their cytotoxicity, but they have been lately characterized as signaling molecules that mediate the acclimation process to environmental constraints (Choudhury et al. 2017). For example, the oxidative burst due to rapid ROS generation is involved in conferring tolerance to thermal and saline stresses. ROS interplay with other molecular actors to deliver convenient adaptational modifications in the roots and hence contribute to their plasticity in response to abiotic conditions (Liu and He 2016).

In addition, class III peroxidases (CIII Prxs) are important players among genes necessary for ROS homeostasis regulation (also called ROS gene network or ROS toolbox). They encode apoplastic proteins which are highly expressed in roots. Thanks to their dual catalytic functions, CIII Prxs oxidize various substrates by using peroxide (H2O2) as an electron acceptor but can also regulate the local concentration of H2O2 or produce ROS (Francoz et al. 2015). They are detected in all Embryophytes but missing from Chlorophyceae. In Arabidopsis thaliana, 73 members of this family have been found (Tognolli et al. 2002). Due to their large number of substrates, they hypothetically contribute to numerous biological processes. Indeed, several CIII Prxs were found to be involved in auxin metabolism, lignin and suberin formation, cross-linking of cell wall components, defense against pathogens, and cell elongation. In fact, their expression and activity can be modified in accordance with external and internal cues to contribute to the plant's tolerance under stressful conditions (Passardi et al. 2005). In fact, several CIII Prxs have been identified for their significant roles in providing tolerance to plants against abiotic stresses (Shahzad et al. 2019).

Actually, plants can perceive abiotic stresses and produce appropriate responses with altered metabolism, growth, and development. These responses are basically reliant on modifications in gene expression which play important roles in promoting tolerance against abiotic stresses (Ohama et al. 2017;[START_REF] Shen | Transcriptomic profiling revealed an important role of cell wall remodeling and ethylene signaling pathway during salt acclimation in Arabidopsis[END_REF][START_REF] Urano | Omics' analyses of regulatory networks in plant abiotic stress responses[END_REF]. Notably, the transcriptional circuits are not linear pathways but are rather integrated networks involving multiple actors, where thousands of genes are differentially regulated under abiotic stresses (Ciarmiello et al. 2011).

Moreover, the intraspecific natural variation constitutes an innovative and powerful tool to discover how plants respond to their wavering environments (Duruflé et al. 2019). It is primarily defined as the inherent genetic diversity among individual organisms making up a population within a species.

It is primed by the accumulation and natural selection of spontaneous mutations that improve the fitness of their hosts to their environment (Alonso-Blanco et al. 2009). The enhanced fitness is casually reflected as preferential phenotypic variations that serve the adaptation of populations to their local living niche. In plants, the intraspecific natural variations have been extensively exploited to elucidate the molecular bases of their phenotypic differences related to their adaptation to diversified environments [START_REF] Dittberner | Natural variation in stomata size contributes to the local adaptation of water-use efficiency in Arabidopsis thaliana[END_REF][START_REF] Prinzenberg | Natural variation of photosynthetic efficiency in Arabidopsis thaliana accessions under low temperature conditions[END_REF]Ristova and Busch 2014;[START_REF] Suter | Gene regulatory variation mediates flowering responses to vernalization along an altitudinal gradient in Arabidopsis[END_REF][START_REF] Zuther | Natural variation in freezing tolerance and cold acclimation response in Arabidopsis thaliana and related species. Survival Strategies in Extreme Cold and Desiccation[END_REF].

A. thaliana has been adopted as a model to study natural variation [START_REF] Trontin | What does Arabidopsis natural variation teach us (and does not teach us) about adaptation in plants?[END_REF]. Its wide geographical distribution over Europe, Asia, and Africa as well as its broad environmental distribution over distinct climates are the bases of its intraspecific diversity (Hoffmann 2002). Also, its small genome and the availability of genetic and genomic resources have assisted its molecular analysis in the past decades (Baxter et al. 2010;[START_REF] Bloomer | Fine-tuning timing: natural variation informs the mechanistic basis of the switch to flowering in Arabidopsis thaliana[END_REF]Bouchabka et al. 2008). In this context, the 1001 Genomes Project has been initiated to understand the existing genetic variations between the populations leading to phenotypic variations and consequently to different interactions with the environment [START_REF] Weigel | The 1001 genomes project for Arabidopsis thaliana[END_REF]. Lately, a repertoire of A. thaliana genes related to cell wall development and ROS homeostasis has been constructed. As these genes are vividly implicated in choreographing the root development under abiotic constraints, their transcriptional regulations were thoroughly investigated in this study (Duruflé et al. 2017).

In this study, the intraspecific natural variation of 30 A. thaliana populations distributed along an altitudinal gradient in the French Pyrenees, not covered yet in the 1001 Genomes Project, in addition to the famous ecotypes Columbia (Col-0, 200 m, Poland) and Shahdara (Sha, 3400 m, Tajikistan) have been exploited to study the plant root response to abiotic stresses. The studied populations fill a gap in the geographic distribution of A. thaliana and could serve as a valuable tool to understand the genetic variation between the Iberian Peninsula and the rest of Europe as well as the plant adaptation to abiotic stress. In fact, the particularity of this sampling is derived from their close geographical distribution but in highly contrasted environments due to the mountainous nature of their collection sites. To illustrate, these populations span an altitudinal gradient, and hence they are exposed to variable climatic factors such as annual minimum, maximum, and mean temperatures (°C), in addition to annual precipitation (mm) and total annual UV radiations (kWh/m2). Such variations are believed to trigger their evolutionary divergence, the basis of their local adaptation to their microenvironments.

Accordingly, their root development has been phenotyped under contrasted growth conditions.

Stress-tolerant populations were selected for transcriptional analysis via RNA sequencing to interpret their gene regulation under environmental stress, with particular focus on the cell wall and ROS homeostasis toolboxes. The objective of this study was to provide a comprehensive view of the natural variation of gene expression in response to abiotic stress in A. thaliana Pyrenean populations.

3 Materials and Methods

Biological Material

Thirty A. thaliana natural populations were used in the study in addition to two popular ecotypes originating from contrasted altitudes (Duruflé, et. al 2019), Columbia (Col-0, 200 m, Poland) and Shahdara (Sha, 3400 m, Tajikistan). Plant individuals of the studied populations were previously gathered from different locations in the Pyrenees, the mountainous physical barrier separating the Iberian Peninsula from France. Their names, climatic data, and taxonomic relevance to A. thaliana were previously reported (Duruflé, et. al 2019). To minimize the impacts of maternal stress, seeds were amplified at once under controlled conditions to obtain homogenous batches of seeds prior to further experiments.

Macrophenotyping of root development

Experimental design

The lengths of the primary roots were measured over a timeline under six growth conditions. Plants were grown in vitro in vertical positions inside 12x12 cm square Petri-dishes at six contrasted conditions on half Murashige and Skoog basal medium (½ MS) with sucrose and agar (M9274-10L, Sigma-Aldrich), and with or without 50 mM NaCl (GUANAC0166, Eurobio). The seeds were sterilized by a bleach solution (69.9% water, 30% Javel water (9.6% Cl), and 0.1% Triton) followed by three successive washes with autoclaved water. For each biological replicate, 16 to 18 seeds per population were sown along two lanes with even spacing; each lane contained eight seeds from two populations to maximize homogeneity and randomness. Afterwards, a cold stratification treatment was performed at 4°C for 24 h in dark to synchronize and promote germination before transfer to long day (16 h light/8 h dark) growth chambers (light intensity = 150 µmol/m 2 ).

The growth conditions were experimentally designed as following: three different temperatures, 16°C (cold stress: "C"), 22°C (optimal: "O"), and 28°C (heat stress: "H"). At each temperature, plants were grown in the presence of 50 mM NaCl (salt stress: "S") and without salt (no salt: "NS "). The six conditions are hence encrypted as: CNS, CS, ONS, OS, HNS, or HS. The plants were scanned on a flatbed scanner (Epson Expression 12000XL) at 1200 dpi over a timeline adapted for each temperature.

The scanning time points were 0, 3, 6, 8, 10, and 14 days at 16°C; 0, 2, 3, 4, 6, 8, and 10 days at 22°C; and 0, 2, 3, 4, 6, and 8 days at 28°C.

Data analyses

The primary roots were measured using NeuronJ plug-in in ImageJ. The experiment was done in three to 12 replicates. Most data analyses were performed via R software (Version 1.2.1335). The root growth rates (RGRs (mm/day)) were computed as the slopes of the linear regression lines through the primary root lengths (PRLs (mm)) measurements as function of time (days). The arithmetic means and the standard errors of means (SEM=SD/√n) of the PRLs were calculated for the various ecotypes at the subsequent time points (days). The differences between the final PRLs recorded at the last day of growth were measured in percentage to evaluate their variation in relation to the genotype and to the treatment, and in reference to the ONS condition as a control.

The variations in PRLs and RGRs due to the different treatments were statistically tested using the analysis of variance, two-way ANOVA from the "multcomp" R package [START_REF] Hothorn | Simultaneous inference in general parametric models[END_REF]).

Germination test

The germination of seeds of selected populations was tested to determine the effects of the temperature and salt treatments. The germination rate was quantified between 24h and 144h.

Three stages were considered: no rupture of the seed envelope (NR), rupture of the external testa envelope (TR), and rupture of the internal endosperm envelope (ER) marked by the embryo's radicle protrusion. The statistical analyses were performed using the "germinationmetrics" R package (Aravind et al. 2021).

The germination test was performed in vitro inside 12x12 cm square Petri-dishes on ½ MS +/-50 mM NaCl. At least 100 sterilized seeds of each population were put on the medium surface, stratified for 48 h at 4°C, and then placed in a growth chamber (16 h light/8 h dark, light intensity = 150 µmol/m 2 ).

Col-0 was tested at the six designated growth conditions, Eaux at CNS, CS, and ONS, Herr at HNS, HS, and ONS, and finally Grip at ONS and OS. The quantification was performed using a binocular loupe (Perfex Sciences Zoom Pro 10.25). The experiment was done in triplicates. The selected populations for transcriptomic analysis were the reference population Col-0 grown at the six designed growth conditions, Eaux as cold-tolerant population grown at CNS, CS, and ONS, Herr as heat-tolerant population grown at HNS, HS, and ONS, and finally Grip as a salt-tolerant population grown at ONS and OS. The roots were harvested into microcentrifuge tubes containing metallic beads after 8, 10, or 14 days for plants grown at 28°C, 22°C, and 16°C, respectively and immediately frozen in liquid nitrogen.

RNA extraction and sequencing

The plants were grinded via RETSCH Mixer Mill MM 400 for 2 mins at 30 Hertz. The RNA was extracted using the Qiagen RNeasy Plant Mini kit according to the manufacturer's instructions and dissolved into 50 μL elution buffer. The yield of RNA was determined by taking spectrophotometric readings by a Denovix DS-11 Nanodrop spectrophotometer. RNA sequencing and the preparation of RNA libraries were performed at Genewiz in Leipzig, Germany.

Data analyses

Preparing sequencing data

The obtained data were treated using Qiagen CLC Genomics Workbench software (version 21.0.2).

First, the sequenced reads were trimmed prior to mapping using quality-scores based trimming (quality limit threshold = 0.5), trimming of ambiguous nucleotides (maximum number of ambiguities = 2), sequencing adaptors trimming (Read 1: 5'-AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC-3';

Read 2: 5'-AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT-3'), and length trimming by which short reads less than 50 nucleotides were discarded. Then, the trimmed reads were mapped against an A.

thaliana cDNA library (TAIR10_cdna_20101214_updated) in batches, one reference sequence per transcript. The mapping process was parameterized by a match score = 1, a mismatch score = 2, a linear gap cost with insertion and deletion costs = 3, length fraction = 0.95, a similarity fraction = 0.98 to maximize stringency, and a maximum number of hits per read = 10.

significantly slower their RGRs beyond the reduction under HNS (19% and 24%), where their RGRs under HS recorded 2.35 and 2.24 mm/day. Referentially, the RGRs of Col-0 and Sha were moderate under CS (cold and salt) (Ranks=9/32 and 12/32), yet it was among the greatest under OS (Rank=25/32 and 32/32) and HS (Ranks=29/31 and 28/31) (Figure 1 a, Supp. Figures 1→6,Supp.

Table 1).

Figure 1: Boxplots displaying (a) the root growth rates (mm/day) and (b) the primary root lengths (mm) at the last day of growth of Col-0 and Sha under the six growth conditions (CNS: cold no salt, ONS: optimal no salt, HNS: heat no salt, CS: cold and salt, OS: optimal and salt, HS: heat and salt). The letters correspond to the compact letter display (cld) of all the pairwise comparisons by Tukey's high significance test.

As for their PRLs, Col-0 and Sha developed their longest roots under ONS (28.14 and 28.97 mm), longer than those under CNS by 52% and 64% (13.55 and 10.57 mm), and under HNS by 32% and 25% (19.23 and 21.82 mm). Compared to the other tested populations, Col-0 roots were among the longest under CNS (Rank=31/32) and ONS (Rank=31/32) but moderate under HNS (Rank=14/31).

However, Sha had the longest roots under ONS (Rank=32/32), but moderate ones under CNS and HNS (Ranks=20/32 and 23/31).

Additionally, the PRLs of Col-0 and Sha were significantly reduced by salinity under OS (38% and 56%) and under CS (82% and 81%). In turn, Col-0 roots were reduced under HS but not beyond what was observed under HNS (33%), but Sha roots were further diminished by this treatment (38%). In fact, the PRL of Col-0 was among the shortest under CS (Rank=7/32; Therefore, Col-0 and Sha roots optimally grow at 22°C, and they are both sensitive to cold, heat, and salt abiotic stresses. Yet, Sha was found slightly more tolerant to salinity but more sensitive to cold than Col-0. However, no significant correlation was found between the observed phenotypes and the altitude or climatic characteristics of their geographic sites.

Overall view of the root development in the Pyrenean populations

Upon an overall view, significant differences in the RGRs and PRLs were observed due to the different treatments among the various accessions (Figure 2 a). The root growth of the Pyrenean A.

thaliana populations was accelerated with the increase of temperature but decelerated due to salinity. To illustrate, the RGRs were globally higher at higher temperatures (CNS<ONS<HNS), but they were lowered upon salt application (CS<CNS, OS<ONS, HS<HNS). For instances, they medialized at 2.09 mm/day under ONS, the optimal condition. Under CNS, their median was reduced by 63% (0.78 mm/day), but, under HNS, it increased by 7% (2.24 mm/day). However, the salt treatment (OS)

decreased the RGRs' median by 47% (1.11 mm/day). Furthermore, under the combined abiotic stresses, their medians were significantly lowered by 79% and 7% (0.44 and 1.95 mm/day) at CS and HS, respectively (Figure 2 b, Supp Table 1). As for the PRLs, they were significantly different among the three growth temperatures. To illustrate, the PRLs of the Pyrenean populations medialized at 20.61 mm under ONS. They were generally lowered under CNS by 50% (10.24 mm), and also under HNS by 3% (19.95 mm). Similarly, the salt treatment globally reduced the PRLs of the populations by 46% (11.15 mm) under OS.

Moreover, the application of salt stress combined to either cold (CS) or heat (HS) stress resulted in further reduction in the root lengths; they decreased by 69% and 23% (6.42 and 15.22 mm), respectively (Figure 2 b, Supp. Table 2). These results highlight that, generally, the diverse abiotic stresses (cold, heat, and salinity) reduce the root lengths of the populations and are hence limiting for the plant growth. The total root phenotypic data (RGRs & PRLs) of the populations under the six designed growth conditions were summarized using principal component analysis (PCA). In fact, PCA is an efficient tool to reduce the dimensionality of large data sets and to facilitate their visualization with minimal loss of accuracy. To illustrate, the principal component 1 (PC1) explained 45% of the multivariate variance across the twelve phenotypic variables, while PC2 explained 23%. The populations were differentially distributed along the PCA plot, and they mostly clustered apart from Col-0 and Sha, which highlighted their higher plasticity in response to abiotic stresses (Figure 3 a).

Moreover, the correlation circle revealed the correlations between the phenotypic variables and the PCs via coordinates, where PC1 pointed mostly towards the ONS treatment, whereas PC2 was positively correlated with the cold stress but negatively associated with the heat stress (Figure 3 b).

Consequently, populations such as Belc and Roch clustered with Col-0 were assumed to grow best under ONS contrasting Mari and Biel. Also, Eaux, Prad, and Lave, which clustered around positive PC2, were envisaged to be cold-tolerant populations; however, Herr and Urdo were forecasted as heat-tolerant populations since they were biased towards negative PC2. These results suggest that the Pyrenean populations differentially respond to the environmental cues owing to their natural variation.

Root development in the Pyrenean populations under different abiotic stresses

Zooming onto the populations, the development of their primary roots was tracked over 8 to 14 days, where it was contrasted in a genotype-dependent as well as treatment-dependent manner 3). To illustrate, under ONS, Roch, Belc, and Bedo had the longest roots (25.84, 24.51, and 24.18 mm) and the highest RGRs (2.64, 2.52, and 2.51 mm/day), while Mari, Pont, and Biel had the shortest ones (13.92, 15.43, and 15.67 mm) growing at the lowest rates (1.41, 1.60, and 1.60 mm/day) (Supp. Figure 1, Supp. Tables 12).

Under CNS, Eaux, Belc, and Roch grew the longest roots (13.98, 12.54, and 11.81) at the fastest rates (1.03, 0.97, and 0.88 mm/day), respectively, whereas, Mari, Biel, and Bedo developed the shortest ones (7.56, 7.89, and 7.95 mm) the most slowly (0.47, 0.61, and 0.62 mm/day), respectively.

Interestingly, certain populations such as Hosp and Mere had moderate PRLs (10.14 and 10.34 mm) but with faster growth rates (0.88 and 0.86 mm/day). This phenomenon is due to the slow rates of seed germination of these populations which delayed the root development initiation (Supp. Figure 2, Supp. Tables 12).

Also, under HNS, the most elongated roots and fastest growth rates were observed in Urdo,Jaco,and Herr (PRLs: 26.07,24.50,and 24.39 mm;RGRs: 3,3.05, and 3.17 mm/day); however, Biel, Mari and Hern had the least elongated roots (13.49, 14.18, and 15.91 mm) with slowest RGRs (1.7, 1.71, and 2.03 mm/day). These observations suggest that the temperature differentially affects the root growth of the studied populations, and that its effects are also influenced by the different genotypes (populations) (Supp. Figure 3, Supp. Tables 12).

Moreover, Hosp, Prad, and Guch developed the longest roots under OS (14.18, 13.86, and 13.56 mm) with higher growth rates of Hosp and Guch (1.46 and 1.40 mm/day), but a lower one for Prad (1.01 mm/day). Yet, the roots of Bier, Mere, and Mari were reduced due to salinity (PRLs: 7.54, 8.19, and 8.22 mm; RGRs: 0.82, 0.82, and 0.8 mm/day) (Supp. Figure 4, Supp. Tables 12). The variations in root growth between populations were similarly described under combined thermal and saline stresses (Supp. Figures 56, Supp. Tables 12). Altogether, these results allow identifying several populations as cold-, heat-, and/or tolerant/sensitive according to their observed root lengths and growth rates under the different treatments.

Highlighting stress-tolerant accessions from the Pyrenean populations

To further highlight the impact of the different treatments on the populations, the PRL of each population under each treatment was compared to the PRL under ONS. For instance, despite that CNS always decreased the PRLs of all the populations, yet the magnitude of these reductions was differential according to the genotype. To exemplify, Eaux, Hern, and Lave were the upper three most correlated accessions with the CNS, whereas Arag, Argu, and Bedo were the least correlated (Figure 4 a). In fact, the PRLs of Eaux, Hern, and Lave were the least reduced under CNS compared to Arag, Argu, and Bedo (Supp. Table 4). Accordingly, Eaux was selected as the best candidate to study cold tolerance, as its root was minimally suppressed under CNS compared to Col-0 (Figure 4 b).

Similarly, the effect of HNS on the PRLs was variable also dependent on the populations. To elaborate, numerous populations developed longer roots under HNS compared to ONS such as Herr, Urdo, and Jaco, while others developed shorter ones such as Col-0, Roch, and Hosp (Figure 4 c, Supp. Table 4). Herr was accordingly selected as a good candidate to study heat-tolerance, as its root growth was boosted by heat, in reference to Col-0 whose PRL was reduced under HNS (Figure 4 d). Furthermore, the salt treatments globally decreased the PRLs and RGRs; however, these reductions differed in genotype-and temperature-dependent. To exemplify, under OS, the PRLs were moderately diminished in populations such as Savi, Prad, and Grip compared to other severely reduced populations such as Gedr, Bier, and Mere (Figure 4 e, Supp. Table 4). Correspondingly, among many appropriate populations, Grip was chosen as a good candidate to study salt-tolerance as its root length was mildly reduced upon salt application in reference to Col-0 (Figure 4 f). instance, Bier's PRL was harshly reduced due to NaCl application at 22°C, but it was not significantly altered when NaCl was added at 28°C (Supp. Table 4).

To sum up, the root phenotyping showed that the populations had differential root growth under optimal conditions which can be related to their genetic architecture. Additionally, they unevenly responded to the applied treatments, as they developed relatively longer or shorter roots reflecting their phenotypic plasticity. Accordingly, the root phenotyping allowed identifying some populations that had fairly advanced root growth under heat (Herr), cold (Eaux), and salt (Grip) stresses compared to Col-0. Therefore, their seed germination was tested to benchmark the beginning of their root development, aiming at knowing if they developed longer roots because they formerly germinated earlier or because they are truthfully tolerant to the stresses.

Germination tests

Germination tests were performed on the cold-, salt-, and heat-tolerant populations (Eaux, Grip, and Herr, respectively) in addition to Col-0 under different combinations of treatments. These experiments highlighted the existing natural plasticity of this trait among the selected candidates and featured how cold, heat, and salt altered it. Also, it was essential to assess the germination rates of the populations to normalize the effects of any significant variations that may advance or delay the initiation of root growth. For this aim, the testa rupture (TR) and the endosperm rupture (ER)

were tracked over a time course (Supp. Table 5). The germination percentage (GP in %) and the median germination time (t50 in h) were computed (Supp. Table 6) [START_REF] Coolbear | The effect of low temperature pre-sowing treatment on the germination performance and membrane integrity of artificially aged tomato seeds[END_REF]).

Seed germination in the reference population Col-0

In Col-0, 100% of the seeds successfully germinated under the six conditions; however, the speed of their germination was dependent on both the temperature and the salt (Figure 5 a-b). To illustrate, the TR and ER t50s were 22.99 and 29.85 h at 22°C (ONS). Under cold stress (CNS), the TR and ER t50s increased respectively by 78% and 57%. However, under elevated temperature (HNS), they decreased by 29% and 33%. Furthermore, the salt treatment (OS) significantly delayed germination as the TR t50 increased by 23% and the ER t50 by 42% (Figure 5 c-d).

Additionally, the combination of cold and salt stresses (CS) further hampered germination, where the TR t50 was delayed by 105% and the ER t50 by 76%. Finally, the combination of heat and salt stresses (HS) mildly decreased the TR t50 (2%), but it increased the ER t50 (10%) (Figure 5 c-d).

These results suggest that the germination of Col-0 changed due to temperature and salinity, where it was accelerating with increasing temperatures, but it was slowed when salt was added to the growth media. Also, temperature had stronger impact on the germination of Col-0 compared to salinity. Moreover, the cold stress (CNS) affected the TR more than the ER; the heat stress (HNS) influenced the TR and ER almost equally, whereas the salt stress had higher effect on the ER rather than the TR. Eaux, where the TR t50 increased by 63% and the ER t50 by 79% (Supp. Figure 8 c-d).

Compared to Col-0, the germination of Eaux was constantly slower under the three tested conditions. To illustrate, the TR t50s of Eaux were prolonged by 20.47 h, 39.9 h, and 47.

Seed germination in the heat tolerant population (Herr)

Herr, the heat-tolerant population, entirely germinated under ONS and HNS, but not under HS with a GP of 36.96% (Supp. Figure 9 a-b). The TR and ER t50s recorded 51.67 and 65.03 h under ONS. The heat treatment (HNS) did not significantly decrease the TR t50 (6%), but it diminished the ER t50 by 16%. Furthermore, the heat and salt treatment combination (HS) strongly hindered the germination of Herr (GP = 36.96%). Also, the TR t50 increased by 89% and the ER t50 by 42% (Supp. Figure 9 c-d).

Seeds germination in the salt tolerant population (Grip)

Grip, the salt-tolerant population, completely germinated under ONS and OS although the salt stress delayed its germination (Supp. Figure 10 a-b). To illustrate, the TR t50s were 41.13 h and 49.15 h under ONS and OS, respectively. As for the ER, the t50s were 35.29 h and 58.09 h (Supp. Figure 10 c-d). In reference to Col-0, Grip had slower germination under both ONS and OS. To exemplify, during the TR, the t50s were prolonged by 18.14 h and 26.16 h under ONS and OS, respectively. The ER was also lagging in Grip, where its t50s were longer by 5.44 h and 28.24 h, respectively under ONS, HNS, and HS (Figure 8 a-b). Therefore, the performed tests showed that Eaux, Grip, and Herr had slower germination compared to Col-0 under optimal conditions. The delay in their germination was further extended under the different stressful treatments which correspond to the tested populations, causing a subsequent delay in their root development initiation. However, despite these delays, Eaux, Grip, and Herr developed longer roots compared to Col-0 under CNS, OS, and HNS respectively, validating their choice as good candidates to study cold-, salt-, and heat-tolerance.

Transcriptomic analysis

Gene expression (GE)

RNA-seq analyses were performed on the selected cold-, heat-, and salt-tolerant populations (Eaux, Herr, and Grip) in addition to Col-0. The global results were summarized in gene-level expression tracks (GEs) holding information about the expression values (TPMs) for each gene in the multiple accessions grown under different conditions (Supp. Table 7). The GE data for each population were summarized in two-dimensional heat maps that hierarchically clustered the A. thaliana genes and the samples from different treatments, each in biological replicates. In fact, the overall patterns of gene expression varied between genotypes and between treatments (Figure 9). The visual examination of the clustering highlighted various aspects of the gene regulation in response to cold, heat, and salt stresses and to the genetic diversity among the populations.

Primarily, a substantial number of genes were differentially expressed due to the various abiotic treatments in each population. Additionally, distinct expression patterns were observed between the populations owing to their genetic polymorphism. These results represent fundamental transcriptional modifications in plants triggered by environmental extrinsic cues as well as by genetic intrinsic cues. Besides, several genes had consistent responses to heat, cold, or salinity. Therefore, the differential expression of genes was analyzed to identify the sets of DEGs that were altered between different populations and under various treatments.

The differentially expressed genes (DEGs)

The differential gene expression was tested in two ways, first by the genotype effect (Supp. Table 8)

to highlight how the genetic variability impacted the transcriptional response to abiotic constraints between the selected stress-tolerant populations versus Col-0, and second by the treatment effect (Supp. Table 9) to highlight genes implicated in this response in each genotype.

DEGs by genotype and treatment effects

The DE analyses by the genotype effect highlighted 4508 genes (1664 upregulated and 2844 These results suggest that A. thaliana can respond to environmental stresses by modulating gene expression, and these regulations are highly contrasted between natural populations due to their innate genetic diversity. In fact, the genotype effect was generally more predominant on the differential expression than the treatment effect since more genes were differentially expressed by genotype-genotype comparisons. However, this claim remains to be validated since not only the number but also the function of the DEGs determine whether the genotype or the treatment effects were stronger.

DE under different treatments between A. thaliana populations

To further highlight the variation in gene expression in response to the different treatments between the studied populations, the differentially expressed genes by the treatment effect in each Lastly, the OS treatment of Grip and Col-0 resulted in 345 commonly differentially expressed genes (97 upregulated and 238 downregulated in the two populations, 5 upregulated in Grip but downregulated in Col-0, and 5 vice-versa), 983 (167 upregulated and 816 downregulated) and 879

(482 upregulated and 397 downregulated) (Figure 11 e). These results brightly reveal the variations in gene expression between populations, where each population had distinct sets of DEGs in response to the abiotic constraints. These sets of DEGs highlighted exclusive regulations in each population that defined its response to the abiotic constraint. Also, sets of mutual DEGs were detected, suggesting that there are common regulatory pathways conserved between the populations.

Accordingly, a focus was made on the DEGs coding for actors involved in cell wall development and ROS homeostasis due to their substantial roles during root development. Among many other functions, cell walls determine the root structure and response to abiotic stresses, and their remodeling allows the rapid expansion of cells during root elongation. Similarly, ROS have been broadly recognized as key players during root growth, where they regulate various developmental processes in different tissues and zones. Also, genes coding for actors in thermotolerance and anthocyanin biosynthesis (stress marker) were highlighted to provide a comprehensive view of gene regulation in response to abiotic stresses. proteins involved in the CW biosynthesis, 176 genes encoding proteins involved in lignin biosynthesis, 32 genes encoding proteins involved in anthocyanin biosynthesis, 186 genes encoding proteins possibly involved in lipid metabolism, 295 genes encoding proteins possibly involved in the ROS homeostasis, and 174 genes encoding proteins involved in thermotolerance.

Genes encoding cell wall proteins

The cell wall proteins (CWPs) toolbox consists of genes coding for proteins acting on cell wall polysaccharides (PACs), structural proteins (SPs), oxidoreductases (ORs), proteases (Ps), proteins possibly involved in signaling (PSs), miscellaneous proteins (MPs), proteins with interaction domains with proteins or polysaccharides (IDPs), and other proteins of unknown functions (UFPs).

The comparison of differential expression highlighted that, in Col-0, most genes from this toolbox were downregulated (108 out of 159 DEGs) under cold majorly those coding for PACs (such as the pectin methylesterases AtPME2, AtPME8, and AtPME48 and the xyloglucan endotransglucosylasehydrolases AtXTH17, AtXHT18, and AtXHT24) and PSs (such as LRR receptor like kinases), yet all DEGs coding for SPs were upregulated (such as the extensins AtEXT6, AtEXT18, and AtEXT19). However, the CS treatment repressed the genes coding for SPs, where only 3 genes were upregulated (AtPRP1, AtEXT9, and AtEXT6), and it also downregulated the genes coding for PACs (26 genes) and PSs ( 30genes). Similarly, the OS treatment majorly repressed the genes of the CWPs toolbox. To illustrate, only few genes coding for PACs (such as the alpha-expansins AtEXPA10 and AtEXPA17) and PSs (such as RAPID ALKALINIZATION FACTOR 32,AtRAF32) were upregulated, whereas most other genes were downregulated. Nevertheless, the HNS upregulated many genes coding for PACs (AtPME25 and AtXHT13), SPs (AtPRP1 and AtEXT6), and PSs (such as the arabinogalactan proteins AtAGP3 and AtAGP30). Lastly, the HS treatment repressed these genes, especially those corresponding to PACs, SPs, Ps, and PSs (Figure 12 a).

Moreover, in Eaux, less genes coding for PACs (24 genes) and PSs (25 genes) were downregulated, and more genes coding for SPs (14 genes) were upregulated under CNS. Additionally, under CS, more genes coding for PACs were upregulated (19 genes), and additional genes coding for PSs were downregulated (47 genes) (Figure 12 b). Furthermore, the OS treatment downregulated most of the CWPs toolbox genes in Grip (60 out of 73 DEGs). However, less genes coding for PSs (12 genes) were suppressed by salt compared to Col-0 (24 genes) (Figure 12 c). Moreover, in Herr, fewer genes were differentially expressed under HNS, where they were mostly upregulated. For instance, 13 genes coding for PSs and 4 genes coding for PACs were upregulated. Nevertheless, the combined heat and salt stresses (HS) repressed most CWPs genes in Herr. Most significantly, 22, 14, 7, and 42 genes coding for PACs, SPs, Ps, and PSs were downregulated (Figure 12 d). 10). expressed (seven upregulated and ten downregulated). Additionally, in Grip, 14 CW biosynthesis genes were upregulated under OS compared to Col-0. However, in Herr, only six DEGs were highlighted (two upregulated and four downregulated) under HNS. The number of DEGs increased to 17 under HS (three upregulated and 14 downregulated) (Figure 14 b, Supp. Table 11).

These results suggest that abiotic stresses repress the genes involved in cell wall biosynthesis in Col-0, majorly due to abruptions in temperatures or due to combination of heat and salt stresses (e.g., cellulose synthases AtCesA4 and AtCesA7). Yet, the cold-tolerant population had enhanced expression of these genes when exposed to low temperature (e.g., AtCslC12, and AtCslA9). Finally, only few genes were upregulated in the salt-and heat-tolerant populations (e.g., AtGOLS4).

Genes encoding proteins involved in lignin biosynthesis

The lignin biosynthesis toolbox comprises genes coding for proteins involved in the phenylpropanoid metabolism, oxidoreductases (ORs), and miscellaneous proteins (MPs). The cold treatment in Col-0 downregulated most of these genes especially those coding for ORs (23 genes). However, under CS, less ORs but more lignin metabolism coding genes were downregulated (14 and five genes).

Similarly, under OS, the ORs coding genes were mostly suppressed (17 genes). However, under HNS, many ORs and lignin metabolism related genes were upregulated (14 and seven genes).

Nevertheless, the combination of both heat and salt stresses repressed the genes coding for ORs (20 downregulated), but not those coding for lignin metabolism (Figure 15 a).

In Eaux, more genes related to lignin metabolism and ORs were upregulated under CNS (7 and 10 genes), but 22 genes coding for ORs were downregulated under cold and salt stresses (CS) (Figure 15 b). Also, Grip had less DEGs from this toolbox under OS, where only 11 coding for ORs were downregulated (Figure 15 c). Similarly, only 6 genes in Herr were differentially expressed under HNS (3 upregulated and 3 downregulated). However, under HS, numerous ORs coding genes were downregulated (12 genes) (Figure 15 d). Furthermore, Eaux under CNS had more upregulated lignin biosynthesis genes compared to Col-0.

For instances, 9 and 19 genes related to lignin metabolism and ORs had higher expression (Figure 16 a). However, the CS treatment suppressed the ORs coding genes but not the lignin metabolism in Eaux (Figure 16 b). Additionally, Grip had 45 DEGs under OS compared to Col-0 (20 upregulated and 25 downregulated), where genes coding for lignin metabolism and ORs were mostly upregulated (Figure 16 c). Moreover, Herr had more downregulated lignin biosynthesis genes under heat stress (HNS) and combined heat and salt stresses (HS) compared to Col-0 (Figure 16 d-e, Supp. Table 12).

These results show that lignin biosynthesis genes are repressed under cold and salt stresses especially those regulating the redox status, yet they are triggered by heat in Col-0 (e.g., laccases (AtLAC2) and caffeic acid O-methyltransferase (AtCOMT-like1)). The cold-tolerant population could upregulate more of these genes under cold conditions, especially those implicated in lignin monomer biosynthesis (AtCOMT-like4 and AtCOMT-like6). Furthermore, the expression of these genes was less importantly modulated in the salt-and heat-tolerant populations under saline and heat stresses. Furthermore, the comparison of differential expression by the genotype effect showed that Eaux had more upregulated cold-regulated genes but more downregulated genes coding for heat-stress transcription factors compared to Col-0 under CNS (Figure 20 a). Moreover, the genes coding for small heat-shock proteins were downregulated in Herr under HNS, whereas other genes coding for diverse proteins involved in thermotolerance were upregulated (Figure 20 c, Supp. Table 15).

These results suggest that, in Col-0, numerous cold-related genes were upregulated at low temperature (e.g., AtCOR15B and AtCOR78), and more genes related to thermotolerance were upregulated due to heat (e.g., AtHsp70 and AtHsp23). Moreover, these genes were not importantly enhanced in the cold-and heat-tolerant populations when exposed to either cold or hot conditions.

Yet, these tolerant populations displayed higher expression of these genes when compared to Col-0.

Genes encoding proteins possibly involved in the ROS homeostasis

The ROS homeostasis genes were differentially expressed in Col-0 under all stresses, most importantly under heat stress. To illustrate, 45, 39, 27, 65, and 61 genes were differentially expressed under CNS, CS, OS, HNS, and HS, among which 19, 20, 11, 26, and 29 were upregulated.

Similarly, these genes where differentially expressed in Eaux under CNS and more importantly under CS where 39 genes were downregulated. Also, in Grip, 23 genes related to the ROS homeostasis were downregulated. However, in Herr, only few genes were differentially expressed under HNS, but more DEGs were detected under HS, and they were mostly downregulated (Figure 21 16). These results suggest that the ROS gene regulatory network is involved in the responses to abiotic stresses, and their roles may vary between different populations and conditions. Additionally, in the heat-tolerant population, this network was not importantly modified which hypothesizes that the applied treatment did not trigger an oxidative burst in Herr.

A focus on class III peroxidases genes

To achieve a more precise view on the ROS homeostasis toolbox, the differential expression of class III Prxs was thoroughly studied. In Col-0, 2, 8, 4, 11, and 6 Prx genes were upregulated under CNS, CS, OS, HNS, and HS, and 15, 7, 12, 11, and 17 were downregulated. However, in Eaux, 9 and 6 genes were upregulated, and 10 and 16 were downregulated under CNS and CS. Additionally, in Grip, the salt stress suppressed the expression of 10 Prx genes but enhanced it for 3 genes. Lastly, under HNS and HS, Herr had 1 and 3 upregulated as well as 1 and 10 downregulated genes. These results suggest that Prx expression varies under multiple stresses and between populations. Yet, similar expression patterns of Prx members were found between populations (e.g., AtPrx15 was downregulated in both Eaux and Col-0 under CNS). Moreover, fewer Prxs were downregulated under CNS and HNS respectively in Eaux, the cold-tolerant population, and in Herr, the heat-tolerant population.

Comparing between the genotypes, Eaux had more upregulated Prxs under CNS in reference to Col-0 (17 genes), nonetheless it had more downregulated ones under CS (11 genes). Moreover, there were 11 upregulated and 14 downregulated genes in Grip under OS. Lastly, in Herr, 10 and 11 genes were upregulated and 17 and 14 were repressed under HNS and HS compared to Col-0. Again, these results validate that the genetic makeup of the populations is involved in regulating Prx genes under the various treatments. Accordingly, Prx coding genes are implemented in the response to various abiotic constraints. This response is dependent on both the genetic makeup of the population and on the applied treatment (Supp. Table 17).

Peroxidase activity

Total enzymatic activity

Following the gene expression analysis of class III Prxs, the total peroxidase activity (PA) was assayed using guaiacol/H2O2 [START_REF] Cosio | Transcriptome analysis of various flower and silique development stages indicates a set of class III peroxidase genes potentially involved in pod shattering in Arabidopsis thaliana[END_REF] for the selected populations under the designated treatments. In Col-0, the PA at optimal condition (ONS) was 93.92 nkat/mg. It maximally increased under HNS (168 nkat/mg); however, a slight but insignificant increase was observed under CNS (107.26 nkat/mg). Additionally, no significant difference in PA was observed upon the salt application under OS (99.47 nkat/mg) nor under the combined cold and salt stress CS (98.57 nkat/mg), yet it was increasing under HS (158.22 nkat/mg) compared to ONS but not to HNS.

In Eaux, the cold tolerant population, the PA was 81.71 nkat/mg under ONS, slightly lower than that in Col-0 (Figure 22 a). It increased significantly under CNS (107.33 nkat/mg) compared to the optimal; nevertheless, no significant change was depicted under CS (86.67 nkat/mg). As for Herr, the heat tolerant population, the PA was 80.29 nkat/mg under ONS mildly less than that in Col-0.

However, contrasting Col-0, the PA in Herr did not considerably increase under heat stress (85.2 nkat/mg) nor under HS (73.18 nkat/mg) (Figure 22 b). Moreover, Grip had the highest PA under ONS (119.85 nkat/mg); its PA did not significantly decrease due to the salt stress (109.7 nkat/mg) (Figure 22 c).

These results suggest that peroxidase enzymatic activity is importantly enhanced by heat stress but insignificantly by salt or cold in Col-0. Additionally, in the cold-tolerant population, the low temperature induced the enzymatic activity of peroxidases. However, it did not increase in Herr, the heat-tolerant population when exposed to elevated temperatures.

Correlation of peroxidase activity with gene expression

Under cold stress, the expression of CIII Prxs was contrasted between Col-0 and Eaux. To illustrate, comparing CNS to ONS in each population showed that out of 17 DEGs in Col-0, only 2 were upregulated, while 9 out of 19 DEGs in Eaux were upregulated under CNS (Figure 22 d). Coherently, a significant increase in peroxidase enzymatic activity was observed in Eaux under CNS, whereas, in Col-0, the PA was not triggered by cold.

Moreover, Col-0 and Grip had similar expression patterns of the CIII Prxs under OS. To exemplify, 16 and 13 genes (among which 8 were mutual) were differentially expressed (4 and 3 were upregulated, and 12 and 10 were downregulated). Consistently, the two populations had similar patterns of enzymatic activities under OS (Figure 22 e).

Besides, the heat stress significantly changed the expression of 22 genes in Col-0 but only of 2 genes in Herr. These changes were further reflected on the PA. In fact, a significant increase in the Prx activity was detected in Col-0 under HNS compared to ONS, yet no change was detected in Herr (Figure 22 f). 5 Discussion

The root phenotyping

Over an evolutionary scale, plants can adapt to their local environments by the selection of genes that enhance their fitness [START_REF] Sork | Genomic studies of local adaptation in natural plant populations[END_REF]. The enhanced fitness of plants to their environments may be achieved via their phenotypic plasticity, by which they alter their morphologies to match the requirements of their living habitats [START_REF] Chevin | Evolution of phenotypic plasticity in extreme environments[END_REF]. Additionally, the local adaptation choreographs the genetic architecture of populations, and it relies on the already existing genetic diversity and on novel variations generated by mutations or allele migration [START_REF] Frachon | Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time[END_REF].

The diversity of adaptive evolutionary trajectories between populations is the basis of the intraspecific natural variation [START_REF] Montesinos | Demographic and genetic patterns of variation among populations of Arabidopsis thaliana from contrasting native environments[END_REF]. Such adaptive mechanisms have been widely characterized in A. thaliana, where numerous genomic maps of climate adaptations have been established for populations at macro and micro geographic scales [START_REF] Frachon | A genomic map of climate adaptation in Arabidopsis thaliana at a micro-geographic scale[END_REF]).

In the Pyrenees Mountains, the local environmental conditions are highly contrasted, where temperature, precipitation, and UV radiation patterns are correlated with the altitude. Previously, the genetic structure of the populations was established, by which they were segregated into 3 clusters, and specific genetic lineages were detected among them. This was translated into contrasted phenotypes of these populations when exposed to suboptimal temperatures (Duruflé et al. 2019).

In response to different abiotic stresses, the root phenotype was also contrasted between the Pyrenean populations. In fact, roots play fundamental roles in the plant by foraging underground resources such as minerals and water. They are known for their enormous plasticity by which they can respond to extrinsic cues via modulating their growth [START_REF] Shekhar | The role of plant root systems in evolutionary adaptation[END_REF]). However, when root growth is tackled by abiotic constraints, the whole plant will be susceptible to this stress.

In this study, the primary root length and growth rate were used as indices to estimate the variation in stress-tolerance revealed at the root level among the populations. To illustrate, the studied populations revealed differential root lengths and growth rates between each other and under different treatments. The multivariate analyses of the phenotypic data clustered the populations into cold-, heat-, and/or salt-tolerant and/or sensitive. For instances, populations such as Arag and Bedo developed tiny roots at the low temperature and were accordingly considered as cold-sensitive populations. Whereas Eaux and Lave had relatively long and fast-growing roots when exposed to cold conditions, and they were hence considered as cold-tolerant populations. Coherently, these cold-sensitive and tolerant populations were formerly characterized to respectively accumulate low and high anthocyanin contents in their rosettes under cold stress (Duruflé et. al 2019).

Therefore, the performed root phenotyping provided further characterization of the phenotypic plasticity displayed by the Pyrenean populations. Despite that no direct correlation could be established between the populations' root lengths or growth rates with the altitude itself, yet the measured variables were impacted by climatic conditions which are in turn associated with the altitude. Also, the root phenotyping allowed the identification of populations as candidates to further analyze stress-tolerance molecular regulations.

The seed germination

Seed germination is a crucial event that marks the beginning of the plant's life cycle and ensures its survival [START_REF] Yang | The Arabidopsis circadian clock protein PRR5 interacts with and stimulates ABI5 to modulate abscisic acid signaling during seed germination[END_REF]. It is regulated by both internal (phytohormones such as gibberellic and abscisic acids) and external signals (temperature, precipitation, and light spectrum) [START_REF] Oh | Light activates the degradation of PIL5 protein to promote seed germination through gibberellin in Arabidopsis[END_REF][START_REF] Xu | A molecular signal integration network underpinning Arabidopsis seed germination[END_REF]. Different abiotic stresses can restrain the proper germination of seeds, which may impact the early seedling establishment and even later processes such as delaying the bolting stage [START_REF] Toorop | Co-adaptation of seed dormancy and flowering time in the arable weed Capsella bursa-pastoris (shepherd's purse)[END_REF]. Relative to the environmental conditions, seeds may germinate faster so the plant can grow under preferential conditions, or they may slower their germination pending for future favorable conditions [START_REF] Kong | Identification of quantitative trait loci controlling ethylene production in germinating seeds in maize (Zea mays L.)[END_REF].

Despite that the studied populations fully germinated under all tested conditions (except for Herr under HS), their germination speed was variable in genotype-and treatment-dependent manners.

These observations mark again the phenotypic plasticity of the Pyrenean populations originating from their genetic diversity, which was vividly reflected in the transcriptional variation. Also, it was prescribed to perform this study since the germination speed benchmarks the beginning of root growth.

5.3

The transcriptomic analyses

Variation of gene expression between Pyrenean populations

RNA-seq has been widely adopted as a high-throughput technique to study the whole transcriptome of an organism at once (Conesa et al. 2016). Transcriptomic studies underscore the activities of genes in different biotic and abiotic conditions by measuring their expression values. Accordingly, they can associate these activities with physiological responses to environmental stresses, or even uncover novel genes involved in such responses [START_REF] Dong | Transcriptomic analysis of two endophytes involved in enhancing salt stress ability of Arabidopsis thaliana[END_REF][START_REF] Henríquez-Valencia | Integrative transcriptomic analysis uncovers novel gene modules that underlie the sulfate response in Arabidopsis thaliana[END_REF].

The global comparisons of the transcriptomic data vividly demonstrated the variation in gene expression between the Pyrenean populations. This variation can be attributed to their underlying genetic architectures which are diversified throughout the evolutionary local adaptations.

Additionally, the differential expression of genes was huge between different treatments, which validates that the responses to abiotic stress involve massive and interconnected transcriptomic regulations.

Regulation of genes involved in cell wall development and ROS homeostasis

Moreover, as the stress response is dependent on many factors such as its application timing and intensity as well as on the genotype, it is difficult to identify common patterns of stress response in cell wall genes transcription [START_REF] Minic | Transcriptomic analysis of Arabidopsis developing stems: a close-up on cell wall genes[END_REF]. In this study, the genes coding for cell wall proteins were generally repressed by cold but triggered by high temperatures. Also, many genes coding for cell wall structural proteins and for proteins involved in signaling were correlated to tolerance against cold and salt stresses. Additionally, the cell wall biosynthesis coding genes were inactivated by abiotic stresses, but their expression was enhanced in the cold-tolerant population. In fact, these cell-wall related genes were not importantly impacted in the heat-tolerant population, suggesting that the applied stress may not be strong enough to induce major changes in this population. AtPrx71 was detected to be upregulated in Col-0 under cold stress. It is involved in the lignification of the secondary cell walls (Hoffmann et al. 2020). Also, AtPrx07, AtPrx44, AtPrx56, AtPrx57, AtPrx60, and AtPrx73 were upregulated in the cold-tolerant population. Beforehand, AtPrx07 was found as a putative target of the ROOT HAIR DEFECTIVE SIX-LIKE4 (RSL4) gene regulating root hair development (Vijayakumar et al. 2016). Also, AtPrx57 increased the accumulation of ROS and permeability of leaf cuticle enhancing the defense response [START_REF] Survila | Peroxidase-generated apoplastic ROS impair cuticle integrity and contribute to DAMPelicited defenses[END_REF]). In addition, AtPrx60 is involved in polar growth in the pollen tubes [START_REF] He | SMALL AUXIN UP RNA62/75 are required for the translation of transcripts essential for pollen tube growth[END_REF]) and the trichoblasts of the root epidermis (Bruex et al. 2012). Lastly, AtPrx73 contributes to the polar growth in the root hair cells (Bruex et al. 2012).

Additionally, AtPrx01, AtPrx08, AtPrx17, AtPrx35, AtPrx39, AtPrx53, AtPrx58, AtPrx60, and AtPrx65 may be linked to heat tolerance due to their enhanced expression under HNS in Col-0 or Herr. First, AtPrx01 was linked to pathogenesis and cold tolerance [START_REF] Kaur | In-silico analysis of cis-acting regulatory elements of pathogenesis-related proteins of Arabidopsis thaliana and Oryza sativa[END_REF]Kim et al. 2012). Second, AtPrx08 is involved in the differentiation of root epidermal cells (Bruex et al. 2012). Third, AtPrx17 is a direct target of the AGAMOUS-LIKE15 transcription factor and contributes to lignification (Cosio et al. 2017). Fourth, AtPrx35 is highly expressed in the trichoblasts and is hence associated with root hair formation (Bruex et al. 2012) al. 2014). Seventh, AtPrx58 is involved in the pollen tube polar growth [START_REF] He | SMALL AUXIN UP RNA62/75 are required for the translation of transcripts essential for pollen tube growth[END_REF]. Finally, AtPrx60 contributes to the differentiation of root epidermal cells (Bruex et al. 2012).

Under salt stress, AtPrx10 and AtPrx52 were upregulated in Col-0 and AtPrx15, AtPrx49, and AtPrx62

in Grip, and are hence related to salt tolerance. Primarily, AtPrx10 was identified for its roles in root cellular elongation and responses to drought stress [START_REF] Markakis | Identification of genes involved in the ACC-mediated control of root cell elongation in Arabidopsis thaliana[END_REF][START_REF] Qin | Regulation and functional analysis of ZmDREB2A in response to drought and heat stresses in Zea mays L[END_REF]). Secondly, AtPrx52 regulates the functions of lignin biosynthesis enzymes (Hoffmann et al. 2020). Thirdly, AtPrx49 is involved in the abscisic acid early signaling in Arabidopsis [START_REF] Osakabe | Leucine-rich repeat receptor-like kinase1 is a key membrane-bound regulator of abscisic acid early signaling in Arabidopsis[END_REF]. Lastly, AtPrx62 contributes to seed germination as it is expressed in the micropylar endosperm [START_REF] Jemmat | Coordination of five class III peroxidase-encoding genes for early germination events of Arabidopsis thaliana[END_REF], and it was recently characterized to be also involved in regulation root hair elongation in cold (https://www.biorxiv.org/content /10.1101/2021.08.20.456256v1).

Conclusion

This study highlights the phenotypic plasticity displayed by plant roots in the A. thaliana Pyrenean populations. The populations developed contrasted phenotypic responses to a combination of thermal and saline stresses and allowed the identification of stress-tolerant populations. Afterwards, the underlying transcriptional regulation of the displayed phenotypes was analyzed. As expected, a myriad of genes had altered expression between the tested genotypes as well as between the different treatments. This variation was attributed to the genetic architecture of the studied populations in parallel to the extrinsic environmental cues. The relied focus on gene toolboxes related to the observed phenotypes also revealed similar variations in gene expression between treatments and between stress-tolerant and sensitive genotypes. In fact, tolerant genotypes had higher expression of genes coding for cell wall, lignin, and anthocyanin biosynthesis, for lipid metabolism, and for cold and heat tolerance. Additionally, the ROS gene regulatory network was highly associated with the abiotic stresses. An expression map for CIII Prxs was built revealing their differential expression between all tested conditions (genotype and treatment effects).

Altogether, these results describe the variation of gene expressions in response to abiotic stress in A.

thaliana Pyrenean populations. Additionally, they highlighted new genes that were exclusively expressed in stress-tolerant populations. Accordingly, they opened future perspectives to perform further examinations of several candidate genes that are involved in tolerance mechanisms.

However, such mechanisms rely on complex and interconnected regulatory pathways, and hence it is difficult to identify common patterns of stress response in plants. In fact, any attempt to understand biology will remain incomplete because it requires the integration of all aspects and scales from the molecule to the organism.

Conclusion 4 Conclusion and Perspectives

To sum up, this study spotted the lights on the factual manifestations of climate change. Indeed, the elevation and fluctuation of temperatures accompanied with the increasing salinity of soils pose drastic threats on wild and cultivated plants leading to the degradation of our living niche. These occurring phenomena urge global, cooperative, and sustainable act to face the upcoming challenges.

In this context, plant science has a pivotal role to explore the plant-environmental interactions as a foundation to come up with sustainable solutions.

Primarily, this study focused on roots which were relatively neglected due to technical limitations despite the knowledge of their fundamentality. Although root development is guided via genetically determined patterns, yet it is highly modulated by external environmental cues. Accordingly, this study contributed to summarizing the acquired knowledge in the past decade about the molecular regulations of root development. For instance, reactive oxygen species (ROS), that had been formerly characterized as toxic byproducts of the primary metabolism, were found to play a myriad of functions throughout the plant's lifecycle. Due to their roles in signaling, ROS were highlighted as multitaskers during root development. They are involved in many regulatory pathways that control the cellular division, elongation, and differentiation in roots.

To further investigate the regulation of root development under abiotic constraints, this study benefitted from the existing intraspecific natural variation in A. thaliana natural populations to explore the plant's responses to thermal and saline stresses. The studied populations are located in the French Pyrenees, a physical barrier that separates the Iberian Peninsula from France. These local populations constitute a unique collection which fills a gap in the geographic distribution of A.

thaliana populations and could help understanding the adaptation of plants to contrasting environment.

Therefore, the root development of the studied populations was phenotyped under six growth conditions combining cold, heat, and/or salt stresses. The obtained results highlighted an enormous plasticity in the root phenotypes, and they allowed the identification of populations that were relatively less impacted by the abiotic constraints (also called stress-tolerant). Whole-genome transcriptional analyses were performed on these selected populations to study their gene expression regulation in response to abiotic constraints. The obtained results revealed a huge variation in the expression patterns between the Pyrenean populations due to their genetic architecture as well as in response to different treatments.

Additionally, a focus was relayed on genes coding for cell wall and ROS related proteins. In fact, the thermal and saline stresses are known to negatively affect the development, productivity, and survival of both the aerial and the root parts. To exemplify, they induce changes in the cell wall polysaccharidic composition and structure as well as on the cell wall-modifying enzymes. Thus, regulating plant growth under stressful conditions require cell wall loosening and stiffening which are both dependent on ROS. Consistently, ROS production is observed in response to various stress conditions including temperature and salt stresses. To control the ROS homeostasis, plants possess a large battery of proteins (such as class III peroxidases, superoxide dismutases, and catalases) able to produce or scavenge ROS generated in constitutive (photosynthesis and respiration) or controlled manners. These proteins are part of the so-called ROS gene network.

The obtained results characterized the expression patterns of these sets of genes under contrasted treatments and in different populations. The differential gene expression in selected populations allowed the identification of novel actors that may be involved in the response to stress. For instance, several class III peroxidases were detected to be upregulated in stress-tolerant populations, suggesting that they may contribute to tolerance.

Furthermore, this study generated massive phenotypic, genomic, and transcriptomic datasets that can open wide future perspectives. For instance, compiling the phenotypic and genomic datasets, GWAS can be performed to highlight SNPs associated with the observed phenotypes and hence to characterize and functionally validate novel genes that are implicated in stress-tolerance. Also, the transcriptomic dataset can provide a basis for further depiction of stress-responsive genes.

Overlaying this dataset with other datasets allow the identification of genes functions at the whole plant level. As well, the comparison of gene expression patterns under single and combined abiotic stresses can be exploited to illustrate the crosstalk and interconnections between stress-specific regulatory pathways.

"Biology is the study of complicated things that give the appearance of having been designed for a purpose." Dawkins, R. (1996). The blind watchmaker: Why the evidence of evolution reveals a universe without design. WW Norton & Company.

Figure 1 :

 1 Figure 1: The temperature anomalies in August 2020 according to Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) (Vera-Valdés 2021) ..........................................

Figure 2 :

 2 Figure 2: Models of potential vegetation (a) under observed climate between 1961 and 1990 and (b) under projected climate between 2071 and 2100. Biomes from pole to equator are: ice (IC), tundra and alpine (UA), boreal conifer forest (BC), temperate conifer forest (TC), temperate broadleaf forest (TB), temperate mixed forest (TM), temperate shrubland (TS), temperate grassland (TG), desert (DE), tropical grassland (RG), tropical woodland (RW), tropical deciduous broadleaf forest (RD), tropical evergreen broadleaf forest (RE) (Gonzalez et al. 2010). ...............

Figure 3 :

 3 Figure 3: Life cycle of (A) Columbia (Col-0) at different stages of its life cycle, from seed (bottom left) to seedling (11 days), to vegetative growth (39 days), and to reproductive growth (45 days). Photographs of (B) a flower, (C) a pollen grain (scanning electron micrograph), and (D) mature siliques (seed pods; left: closed; right: open with a few remaining unshattered seeds) (Krämer 2015). ............................................................................................................................................

Figure 4 :

 4 Figure 4: Map of A. thaliana worldwide distribution. Areas colored in red correspond to the continuous distribution of A. thaliana; red circles mark additional sites (Krämer 2015). ............

Figure 5 :

 5 Figure 5: Intraspecific morphology variation in the rosettes of A. thaliana Pyrenean populations grown at 22°C (Duruflé et al. 2019). .............................................................................................

Figure 6 :

 6 Figure 6: The A. thaliana root apex. (A) The apex of the seedling root divided into meristematic zone, elongation zone and maturation zone. (B) Schematic representation of the cell types in longitudinal and radial cross-sections of the Arabidopsis root apical meristem (Bargmann et al. 2013). ............................................................................................................................................

Figure 7 :

 7 Figure 7: The role of reactive oxygen species (ROS) in abiotic stress acclimation. The two major sources of ROS during abiotic stress, metabolic and signaling ROS, are shown to interact and form a ROS signature that controls plant acclimation to stress through redox reactions that regulate transcription and translation of stress acclimation proteins and enzymes (Choudhury et al. 2017). .......................................................................................................................................

Figure 8 :

 8 Figure 8: The diverse functions and roles of class III peroxidases (Cosio and Dunand 2009) ..............

Figure 9 :

 9 Figure 9: Graphical Abstract..................................................................................................................

Figure 10 :

 10 Figure 10: The geographic distribution of the studied A. thaliana natural populations in the French Pyrenees. The color scale represents the altitude in meters (m) above sea level. ......................

Figure 11 :

 11 Figure 11: The gel image of the capillary electrophoresis performed on extracted RNA from different A. thaliana populations (Col-0, Eaux, Grip, and Herr) grown under different temperatures (16°C, 22°C, or 28°C) and salt concentrations (0 mM or 50 mM of NaCl) in 3 biological replicates (R1, R2, and R3). The sharp bands correspond to the 28S and 18S rRNA subunits. .......................

Figure 12 :

 12 Figure 12: The electropherogram of an RNA sample extracted from Col-0 grown at 22°C. The x-axis represents its size distribution, and the y-axis measures the relative fluorescence unit (RFU) reflecting the RNA quantity. The LM is the lower marker; the pink and blue peaks correspond to the 18S and 28S ribosomal subunits, respectively. ......................................................................

Figure 13 :

 13 Figure 13: A volcano plot that displays the differential expression of genes between cold and optimal treatments in Col-0. ......................................................................................................................

Figure 15 :

 15 Figure15: Expression profiling of 5 distinct root tissues at 3 developmental stages[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. The 5 concentric tissues are: stele, endodermis (Endo), endodermis and cortex (Endo+cortex), epidermis (Epi), and lateral root cap (Lrc). The 3 developmental stages are in the meristematic zone (1), the elongation zone (2), and the differentiation zone (3)[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. ............................................................................................................................................

  Figure15: Expression profiling of 5 distinct root tissues at 3 developmental stages[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. The 5 concentric tissues are: stele, endodermis (Endo), endodermis and cortex (Endo+cortex), epidermis (Epi), and lateral root cap (Lrc). The 3 developmental stages are in the meristematic zone (1), the elongation zone (2), and the differentiation zone (3)[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. ............................................................................................................................................

  . .................................................................. 55

Figure 1 :

 1 Figure 1: The temperature anomalies in August 2020 according to Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) (Vera-Valdés 2021)

Figure 2 :

 2 Figure 2: Models of potential vegetation (a) under observed climate between 1961 and 1990 and (b) under projected climate between 2071 and 2100. Biomes from pole to equator are: ice (IC), tundra and alpine (UA), boreal conifer forest (BC), temperate conifer forest (TC), temperate broadleaf forest (TB), temperate mixed forest (TM), temperate shrubland (TS), temperate grassland (TG), desert (DE), tropical grassland (RG), tropical woodland (RW), tropical deciduous broadleaf forest (RD), tropical evergreen broadleaf forest (RE) (Gonzalez et al. 2010).

Figure 3 :

 3 Figure 3: Life cycle of (A) Columbia (Col-0) at different stages of its life cycle, from seed (bottom left) to seedling (11 days), to vegetative growth (39 days), and to reproductive growth (45 days). Photographs of (B) a flower, (C) a pollen grain (scanning electron micrograph), and (D) mature siliques (seed pods; left: closed; right: open with a few remaining unshattered seeds) (Krämer 2015).

Figure 4 :

 4 Figure 4: Map of A. thaliana worldwide distribution. Areas colored in red correspond to the continuous distribution of A. thaliana; red circles mark additional sites (Krämer 2015).

Figure 5 :

 5 Figure 5: Intraspecific morphology variation in the rosettes of A. thaliana Pyrenean populations grown at 22°C (Duruflé et al. 2019).

Figure 6 :

 6 Figure 6: The A. thaliana root apex. (A) The apex of the seedling root divided into meristematic zone, elongation zone and maturation zone. (B) Schematic representation of the cell types in longitudinal and radial cross-sections of the Arabidopsis root apical meristem (Bargmann et al. 2013).

Figure 7 :

 7 Figure 7: The role of reactive oxygen species (ROS) in abiotic stress acclimation. The two major sources of ROS during abiotic stress, metabolic and signaling ROS, are shown to interact and form a ROS signature that controls plant acclimation

Figure 8 :

 8 Figure 8: The diverse functions and roles of class III peroxidases(Cosio and Dunand 2009)

Figure 9 :

 9 Figure 9: Graphical Abstract

  or indirectly via ROS signaling. Loss-offunction mutant, prx17, has lower lignin content in most organs(Cosio et al., 2017;[START_REF] Herrero | Bioinformatic and functional characterization of the basic peroxidase 72 from Arabidopsis thaliana involved in lignin biosynthesis[END_REF] Hoffmann et al., 2020) prx57 have lower LR density and number due to changes of ROS balance in the initiation stage[START_REF] Manzano | The emerging role of reactive oxygen species signaling during lateral root development[END_REF] Vijayakumar et al., 2016) (Continued on next page)

H 2 O

 2 2 via covalent modification of extracellular cysteine residues, which leads to autophosphorylation of HPCA1. HPCA1 encodes an LRR-RK that contains sites for extracelular peroxide sensing. This leads to the activation of intracellular kinase activity leading to calcium influx and hence activation of downstream signaling pathways. Root meristem, primary and lateral root tips. Also present in leaves and pollen. In root tips, is preferentially expressed in QC cells, cortex/endodermis stem cells and endodermal and stele cells of root meristems Promote cellular division in the RAM. KO mutants, rrg-1 and rrg-2 revealed a short-root phenotype compared to the WT. Required for the maintenance of mitochondrial structure. Positive regulator of cell division and but negative regulator of cell expansion in the postembryonic root meristem (Zhou et al., 2011) Prohibitin3 (PHB3) (AT5G40770) Expressed in proliferative tissues, vasculature, stems, leaves, and roots. Preserves redox homeostasis in the mitochondria Inhibits the cell cycle. Maintains the stem cell niche in QC and activate the cellular division in the proximal meristem. ROS production is induced and subsequently inhibits PHB3 expression. In phb3 mutants, genes implicated in ROS production showed higher expression (i.e. AOX1 and NA (Kong et al., 2018) precise localization at the CSs development site. CASP1 guides this localization by interacting with SGN1 and SGN3 (Alassimone et al., 2016; Li et al., 2018a) (Continued on next page)

Figure 1 .

 1 Figure 1. ROS control the equilibrium between cell proliferation and differentiation in rootsThe transcription factor UPBEAT1 (UPB1) modulates the balance between cell proliferation and differentiation by directly regulating the expression of a subset of peroxidases (PRXs; PRX39, PRX40, and PRX57). These PRXs are highly expressed at the boundary of the meristematic and elongation zone. In Col-0 root tips, O 2 -accumulates in the meristem (yellow area), whereas H 2 O 2 accumulates in the elongation zone (blue area) and UPB1 represses expression of PRXs in the elongation zone. In mutants upb1-1, there is a major production of O 2 -owing to upregulated expression of the PRXs, so the transition zone shifts in favor of the proliferation zone, while in UPB1 overexpressors, the PRXs are downregulated, so with less PRXs, H 2 O 2 cannot be catalyzed and the differentiation zone expands. PROHIBITIN3 (PHB3) maintains the root stem cell niche maintenance: under nitrate deficiency, ROS production is induced and subsequently inhibits PHB3 expression. This triggers ROS-responsive factors (ERF109, ERF114, and ERF115) leading to cellular proliferation and differentiation. On the contrary, nitrate sufficiency reduces ROS concentrations. Therefore, PHB3 becomes active and inhibits the underlying ETHYLENE RESPONSE FACTOR 115 (ERF115), thus maintaining the pluripotency of the QC. Simultaneously, ETHYLENE RESPONSE FACTOR 109 (ERF109) and ETHYLENE RESPONSE FACTOR 114 (ERF114) are induced to promote cellular elongation and differentiation in the elongation and differentiation zones, respectively. Cyclins (CYCs) and cyclin-dependent kinases (CDKs) and CYCs regulate the size of MZ, controlling the cell cycle. The cell cycle stops owing to changes in the redox homeostasis. CYCs are controlled by the transcription factor TEOSINTE BRANCHED1-CYCLOIDEA-PROLIFERATING CELL FACTOR1 (TCP). When ROS levels increase owing to an oxidative burst, a disulfide bond is formed preventing the binding of TCP on the CYC promoters. Moreover, CYC and CDK expression patterns have been correlated with the ASC:GSH cycle and their redox status. ASC: ascorbic acid; EZ: elongation zone; GSH: reduced glutathione; RAM: root apical meristem; QC: quiescent centre; TZ: transition zone

Figure 2 .

 2 Figure 2. RBOHs and PRXs are important molecular players in several ROS-mediated developmental processes in roots (A) RBOHE accumulates at the initiation site of the LR, while LR development in the loss-of-function mutant rbohe is delayed.GPXs are also expressed in the LR. gpx mutants develop larger lateral root primordia, indicating that the GPX family plays a role in regulating root architecture, especially GPX1 and GPX7, having a critical role in the development and formation of the lateral root. PRX07 and PRX57 control LR growth by maintaining ROS balance during the initiation stage in an auxin-independent manner. prx07 and prx57 have lower LR density and number. DZ: differentiation zone; EZ: elongation zone, LR: lateral root; MZ: meristematic zone; RC: root cap; RH: root hair. (B) Localization of expression of various peroxidases. PRX17 is expressed in the xylem and root endodermis and participates in the lignin polymerization. prx17 mutants have lower lignin content in most organs. PRX37 is expressed in the root endodermis, and it participates in the phenolic cross-linking activity during lignin deposition in the cell wall. The overexpression of PRX17 results in a dwarf phenotype with small plants and delayed development. PRX64 is expressed in the root endodermis; it utilizes peroxide for a monolignol oxidation during lignin formation. PRX72 is expressed in the root endodermis and the xylem. Its expression is upregulated when the xylem is actively forming. The lignin levels in prx72 mutants are 40% less compared with those in the WT. (C) RBOHC and PRX01, PRX07, PRX44, and PRX73 are expressed in the trichoblast cells in the epidermis. They are key enzymes responsible for root hair elongation by controlling the ROS homeostasis at the tip of the root hair cell. RBOHD and RBOHF are active in the mature root region especially in the vascular cylinder and LRP. RBOHD is expressed in the endodermis and procambium; the number and density of LR is higher in rbohd mutants than in the WT. RBOHF is required during CS formation in the endodermis, where its localization is coordinated by several CASPs and participates in lignin polymerization.

Figure 3 .

 3 Figure 3. Selected examples of ROS-mediated root developmental process (A) In lateral roots (LRs), UPBEAT1, a basic helix-loop-helix TF expressed at the TZ, directly regulates peroxidases that alter the distribution of ROS. Cell proliferation requires high levels of O 2 , whereas high H 2 O 2 induces differentiation. UPB1 is transcriptionally enriched during the early stages of lateral root primordia (LRP) when ROS significantly accumulate in the emerging LR. UPB1 overexpressors have more LRPs. upb1 has more emerging LRs than WT. UPB1 controls the expression of a subset of PRXs genes that manipulate the ROS balance. Besides, MYB36 acts in stages V and VI of LR development, by manipulating the ROS balance via the regulation of at least PRX09 and PRX64. (B) In growing root hairs, RBOHC is the key enzyme that produces ROS in the apoplast. RBOHC-mediated ROS leads to the activation of a MAPK cascade through OXI1 during cell elongation of root hairs. At the transcriptional level, RSL4, a bHLH transcription factor, regulates the expression of several class III PRXs (PRX01, PRX44, and PRX73), which participate in root hair growth and ROS homeostasis. In addition, PRX07 is also required for root hair elongation. (C) In inner root tissues, SHORTROOT (SHR) transcription factor (TF) moves from the stele to the endodermis where it interacts with another TF SCARECROW (SCR), and then the SHR:SCR complex specifies the endodermal cell identity and activates the transcription of MYB36. MYB36 regulates the biosynthetic apparatus for Casparian strips (CSs). It also plays role in the lateral root primordia differentiation and lateral root initiation. MYB36 regulates the expression of several underlying genes such as CASPS, PRX64, and ESB1 to trigger the proper endodermis development. CASP is responsible for the proper localization at the CS development site by the interaction with two receptor-like kinases SCHENGEN1 (SGN1) and SCHENGEN3 (SGN3). ESB1 stabilizes the CASP proteins scaffold. RBOHF generates superoxide that mutates into peroxide. PRX64 and LACs oxidize monolignols and catalyze lignin formation.

Figure 10 :

 10 Figure 10: The geographic distribution of the studied A. thaliana natural populations in the French Pyrenees. The color scale represents the altitude in meters (m) above sea level.

Figure 11 :

 11 Figure 11: The gel image of the capillary electrophoresis performed on extracted RNA from different A. thaliana populations (Col-0, Eaux, Grip, and Herr) grown under different temperatures (16°C, 22°C, or 28°C) and salt concentrations (0 mM or 50 mM of NaCl) in 3 biological replicates (R1, R2, and R3). The sharp bands correspond to the 28S and 18S rRNA subunits..

Figure 12 :

 12 Figure 12:The electropherogram of an RNA sample extracted from Col-0 grown at 22°C. The x-axis represents its size distribution, and the y-axis measures the relative fluorescence unit (RFU) reflecting the RNA quantity. The LM is the lower marker; the pink and blue peaks correspond to the 18S and 28S ribosomal subunits, respectively.

Figure 13 :

 13 Figure13: A volcano plot that displays the differential expression of genes between cold and optimal treatments in Col-0.

3. 4

 4 Genes Highlighted by the Study 3.4.1 Cell-Wall Related Genes Abiotic stresses negatively impact the plants' development and survival. The initial indicators of such deleterious effects are presented by the stunted growth of plants due to limitations of their cell walls extensibility. In fact, the cell wall (CW) determines the structures, sizes, and functions of plant cells and consequently the whole plant morphology. When exposed to environmental constraints, CWs contribute to the developed acclimation response via adjusting their architecture (Tenhaken 2015).

Figure 14 :

 14 Figure 14: Expression profiling of 5 distinct root tissues at 3 developmental stages[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF]. The 5 concentric tissues are: stele, endodermis (Endo), endodermis and cortex (Endo+cortex), epidermis (Epi), and lateral root cap (Lrc). The 3 developmental stages are in the meristematic zone(1), the elongation zone (2), and the differentiation zone (3)[START_REF] Birnbaum | A gene expression map of the Arabidopsis root[END_REF].

Figure 2 :

 2 Figure 2: (a) Two-way ANOVA has been run on the whole set of accessions showing the main effects of the "Treatments" and the "Populations" on the two measured parameters: "Root Growth Rate" and "Primary Root Length". (b) The boxplots display the root growth rates (mm/day) and the primary root lengths (mm) of the A. thaliana Pyrenean populations. The letters correspond to the compact letter display (cld) of all the pairwise comparisons by Tukey's high significance test.

Figure 3 :

 3 Figure 3: The PCA score plot (a) displays the A. thaliana Pyrenean populations spanning the principal components PC1 (45%) and PC2 (23%) that summarize the measure primary root lengths (PRLs) and root growth rates (RGRs) measured under the six treatments. (b) The correlation circle plot represents the contribution of the measured variables to the principal components (PC1 and PC2).

Figure 4 :

 4 Figure 4: A scatter plot by which the populations are distributed according to their primary root lengths (PRLs) under ONS and their PRLs under (a) CNS, (c) HNS, and (e) OS. The three most correlated populations with the different treatments (CNS, HNS, and OS) are labeled in green; the three least correlated are labeled in red. Col-0 and Sha are plotted in grey. (b)

Figure 5 :

 5 Figure 5: The line graphs show (a) the testa and (b) the endosperm ruptures over time (h) in Col-0 under the six designated treatments. The bar graphs reveal the median germination time t50 (h) in black bars scaled on the left y-axis, and the germination speed gsp (GS/hr-1) in scattered red dots scaled on the right y-axis of (c) the TR and (d) ER. The letters correspond to the compact letter display of the multiple pair-wise comparisons between treatments using Tukey's Honest Significant Difference (Tukey's HSD), in black relative to t50, and in red relative to gsp. The error bars correspond to the standard error of means (SEM).

4. 2 . 2

 22 Seed germination in the cold tolerant population (Eaux)The seeds of Eaux, the cold-tolerant population, fully germinated under the three tested conditions (CNS, CS, and ONS) (Supp. Figure8 a-b). Under ONS, the TR t50 recorded 43.46 h, and the ER t50 was 55.92 h. The cold treatment (CNS) increased the TR t50 by 45%; similarly, it extended the ER t50 by 56%. Additionally, the combined cold and salt treatment (CS) further hindered the germination of

  7 h under ONS, CNS, and CS, respectively, compared to those of Col-0 (Figure 6 a). Also, the ER was slower in Eaux versus Col-0, where its ER t50s were higher by 26.07 h, 57.61 h, and 70.5 h respectively under ONS, CNS, and CS (Figure 6 b).

Figure 6 :

 6 Figure 6: The bar graphs display the median germination time t50 (h) in black bars scaled on the left y-axis, and the germination speed gsp (GS/hr-1) in scattered red dots scaled on the right y-axis of (a) the TR and (b) ER in Eaux compared to Col-0 under ONS, CNS, and CS. The stars represent the significance level of the performed student's t-test between the

Figure 7 :

 7 Figure 7: The bar graphs display the median germination time t50 (h) in black bars scaled on the left y-axis, and the germination speed gsp (GS/hr-1) in scattered red dots scaled on the right y-axis of (a) the TR and (b) ER in Herr compared to Col-0 under ONS, HNS, and HS. The stars represent the significance level of the performed student's t-test between the two populations under each condition: (***) p-value <0.0001, (**) p-value <0.001, and (*) p-value <0.01, in black relative to t50, and in red relative to gsp. The error bars correspond to the standard error of means (SEM).

Figure 8 :

 8 Figure 8: The bar graphs display the median germination time t50 (h) in black bars scaled on the left y-axis, and the germination speed gsp (GS/hr-1) in scattered red dots scaled on the right y-axis of (a) the TR and (b) ER in Grip compared to Col-0 under ONS and OS. The stars represent the significance level of the performed student's t-test between the two populations under each condition: (***) p-value <0.0001, (**) p-value <0.001, and (*) p-value <0.01, in black relative to t50, and in red relative to gsp. The error bars correspond to the standard error of means (SEM).

Figure 9 :

 9 Figure 9:Heat-map visualizing the gene expression in multiple samples of Col-0 at different growth conditions. Euclidean distance and complete linkage were used for the hierarchal clustering of genes and samples with similar expression patterns. Each column represents a sample labeled above, and each raw corresponds to a gene from the A. thaliana genome. The left tree displays the gene clustering. The scale reflects the expression levels of genes (black<red). The expression value is computed by calculating the log CPM or "counts per million" for each gene using the effective sizes of the libraries generated by the TMM normalization, followed by normalizing the samples using Z-scores. (a) The upper tree

  downregulated) and 3004 genes (1510 upregulated and 1494 downregulated) differentially expressed between Eaux and Col-0 under CNS and CS. Also, 4910 DEGs (2468 upregulated and 2442 downregulated), 5291 DEGs (2376 upregulated and 2915 downregulated), and 4923 DEGs (2049 upregulated and 2874 downregulated) were obtained by respectively comparing Eaux, Grip and Herr to Col-0 under ONS. Also, 3958 DEGs (1299 upregulated and 2659 downregulated) were detected between Grip and Col-0 under OS. Lastly, in reference to Col-0, 2308 DEGs (1178 upregulated and 1130 downregulated) and 4141 DEGs (1645 upregulated and 2496 downregulated) were detected in Herr under HNS and HS, respectively (Figure 10). Moreover, the DE analyses by the treatment effect in Col-0 resulted in 2600 DEGs (1425 upregulated and 1175 downregulated) under CNS, 1836 DEGs (770 upregulated and 1066 downregulated) under CS, 1224 DEGs (584 upregulated and 640 downregulated) under OS, 4189 DEGs (1969 upregulated 2220 downregulated) under HNS, and 4687 DEGs (2138 upregulated and 2549 downregulated) under HS compared to ONS. In Eaux, the treatment effect highlighted 1551 DEGs (715 upregulated and 836 downregulated) under CNS and 2110 DEGs (963 upregulated and 1147 downregulated) under CS. Also, in Grip, the comparison by treatment delivered 1328 DEGs (269 upregulated and 1059 downregulated) under OS. Finally, 964 DEGs (625 upregulated and 339 downregulated) under HNS and 2914 DEGs (1422 upregulated and 1492 downregulated) under HS were detected in Herr (Figure 10).

Figure 10 :

 10 Figure 10:The number of differentially expressed genes (DEGs) (fold-change >1.5; False Discover Rate <0.05), upregulated (Up) and downregulated (Down) detected by the multiple comparisons of gene expression by the genotype effect under each treatment and by the treatment effect for each genotype. The heat-map is increasingly from green to red based on the number of detected DEGs.

Genotype

  population were compared to those of Col-0. In fact, the DE analyses under CNS of Eaux and Col-0 highlighted 638 mutual DEGs (289 upregulated and 312 downregulated in both populations, 3 upregulated in Eaux but downregulated in Col-0, and 34 downregulated in Eaux but upregulated in Col-0), and 913 (423 upregulated and 490 downregulated) and 1962 (1102 upregulated and 860 downregulated) unique DEGs to Eaux and Col-0, respectively. Also, their comparison by CS treatment resulted in 799 common DEGs (286 co-upregulated and 503 co-downregulated in both populations, 5 upregulated in Eaux but downregulated in Col-0, and 5 vice-versa), and 1311 (672 upregulated and 639 downregulated) and 1037 (479 upregulated and 558 downregulated) exclusive DEGs to Eaux and Col-0 (Figure 11 a-b). Additionally, comparing Herr and Col-0 by the HNS treatment highlighted 603 shared DEGs (332 upregulated and 253 downregulated in both populations, 16 upregulated in Herr but downregulated in Col-0, and 2 vice-versa), and 361 (277 upregulated and 84 downregulated) and 3589 (1635 upregulated and 1951 downregulated) unique DEGs to Herr and Col-0, respectively. Also, under HS, these two populations had 1848 mutual DEGs (817 upregulated and 1021 downregulated in both populations, 8 upregulated in Herr but downregulated in Col-0, and 2 vice-versa), and 1066 (597 upregulated and 469 downregulated) and 2839 (1319 upregulated and 1520 downregulated) DEGs corresponding to Herr and Col-0, exclusively (Figure 11 c-d).

Figure 11 :

 11 Figure 11: Venn-diagrams displaying the numbers of mutually or exclusively differentially expressed genes due to various treatments between populations.

Figure 12 :

 12 Figure 12: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated cell wall proteins coding genes detected by comparing the differential expression by the treatment effect in each population in reference to ONS: (a) Col-0, (b) Eaux, (c) Grip, and (d) Herr.

Figure 13 :

 13 Figure 13: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated cell wall proteins coding genes detected by comparing the differential expression by the genotype effect under each treatment in reference to Col-0: (a) CNS, (b) CS, (c) OS, (d) HNS, and (e) HS.

Figure 15 :

 15 Figure 15: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated lignin coding genes detected by comparing the differential expression by the treatment effect in each population in reference to ONS: (a) Col-0, (b) Eaux, (c) Grip, and (d) Herr.

Figure 16 :

 16 Figure 16: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated lignin coding genes detected by comparing the differential expression by the genotype effect under each treatment in reference to Col-0: (a) CNS, (b) CS, (c) OS, (d) HNS, and (e) HS.

Figure 19 :

 19 Figure 19: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated thermotolerance coding genes detected by comparing the differential expression by the treatment effect in each population in reference to ONS: (a) Col-0, (b) Eaux, (c) Grip, and (d) Herr.

Figure 20 :

 20 Figure 20: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated thermotolerance coding genes detected by comparing the differential expression by the genotype effect under each treatment in reference to Col-0: (a) CNS, (b) CS, (c) OS, (d) HNS, and (e) HS.

  a). Comparing the genotypes, Eaux had 72 and 55 DEGs under CNS and CS compared to Col-0, among which 35 and 31 were upregulated. Under OS, Grip had 50 DEGs in reference to Col-0, where 31 were downregulated. However, Herr had 46 and 49 DEGs under HNS and HS that were mostly upregulated (28 and 26 genes) (Figure 21 b, Supp. Table

Figure 21 :

 21 Figure 21: The number of significantly (|FC|≥1.5 and FDR≤0.05) upregulated and downregulated ROS homeostasis related genes detected by comparing the differential expression by (a) the treatment and (b) the genotype effect.

Figure 22 :

 22 Figure 22: The bar plots display the peroxidase activity (nkat/mg of proteins) in (a) Col-0 and Eaux under ONS and CNS, (b) in Col-0 and Herr under ONS and HNS, and (c) in Col-0 and Grip under ONS and OS. The error bars correspond to the standard error of means (SEM). The letters correspond to the compact letter display (cld) of the multiple pair-wise comparisons between populations under each treatment using Tukey's Honest Significant Difference (Tukey's HSD). The stars represent the significance level of the performed student's t-test between two conditions for each population (***) p-value <0.0001, (**) p-value <0.001, and (*) p-value <0.01. The scatter plots represent the distribution of class III peroxidases genes (x-axis) according to their expression fold change (y-axis) by the treatment effect for each population: (d) Col-0 and Eaux under CNS compared to ONS, (e) Col-0 and Herr under HNS compared to ONS, and (f) Col-0 and Grip under OS compared to ONS.

Figure 23 :

 23 Figure 23: The differential expression of CIII Prxs tested by the genotype effect in reference to Col-0 and by treatment effect in reference to ONS for the different populations. FC: fold change, FDR: False Discovery Rate

  used to estimate if the populations fit the neutral theory model via Tajima's D test. To illustrate, Tajima's D can differentiate between the random (neutral) mutations where SNPs do not impact the fitness of a population and the directed mutations that are under selection pressure[START_REF] Ross-Ibarra | Patterns of polymorphism and demographic history in natural populations of Arabidopsis lyrata[END_REF]).

  OnApril 25, 2018, "Emmanuel Macron", the President of the French Republic, addressed the Congress of the United States of America: "By polluting the oceans, not mitigating CO2 emissions, and destroying our biodiversity, we are killing our planet. Let us face it, there is no planet B."(https://www.elysee.fr/emmanuel-macron/2018/04/25/speech-by-the-president-of-the-republicemmanuel-macron-at-the-congress-of-the-united-states-of-america.en; visited onFebruary 22, 2021) Beforehand, at the United Nations Climate Change Summit on September 23, 2014, Barack Obama, the former USA President, remarked that: "We are the first generation to feel the impact of climate

	1 Introduction
	1.1 The Climate Change
	1.1.1 Preface
	change	and	the	last	generation	that	can	do	something	about	it."

. Grey corresponds to missing data ......................................................................................................... 66 (https://obamawhitehouse.archives.gov/the-press-office/2014/09/23/remarks-president-unclimate-change-summit; visited on

Table 1 :

 1 The phylogenetic classification of the model plant Arabidopsis thaliana

	Rank	Scientific and Common Names
	Kingdom	Plantae -Plants
	Subkingdom	Tracheobionta -Vascular plants
	Super-division Spermatophyta -Seed plants
	Division	Magnoliophyta -Flowering plants
	Class	Magnoliopsida -Dicotyledons
	Subclass	Dilleniidae
	Order	Capparales
	Family	Brassicaceae / Cruciferae -Mustard family
	Genus	Arabidopsis Heynh. -Rockcress
	Species	Arabidopsis thaliana (L.) Heynh. -Thale cress
	1.2.2.2 Botany

  Chiletranslation into physiological responses. In fact, changes in ROS homeostasis are signals that can trigger growth modifications

	1 Laboratoire de Recherche
	en Sciences Ve ´ge ´tales,
	CNRS, UPS, Universite ´de
	Toulouse, 31326 Castanet
	Tolosan, France
	2 Fundacio ´n Instituto Leloir
	and IIBBA-CONICET, Av.
	Patricias Argentinas 435,
	Buenos Aires, CP C1405BWE,
	Argentina

3 Centro de Biotecnologı ´a Vegetal (CBV), Facultad de Ciencias de la Vida (FCsV), Universidad Andres Bello and Millennium Institute for Integrative Biology (iBio), Santiago,

Table 1 .

 1 Selected examples of components that regulate ROS homeostasis: ROS scavengers, ROS producers, and an ROS sensor involved in root development processes

			Functional evidence, mutant
	Gene name/protein	Subcellular localization	analysis, phenotypes		References
	ROS scavengers
	Superoxide dismutase (SOD)	Chloroplast, mitochondria,	Defense against oxidative	(Saini et al., 2018)
		peroxisome, and cytosol	damage. It eradicates O 2	À by
			producing O 2 and H 2 O 2
	Catalase (CAT)	Peroxisome and mitochondria in	Removes H 2 O 2 and transforms it	(Das and Roychoudhury, 2014)
	CAT1, CAT2, CAT3	pollen and seeds; photosynthetic	into H 2 O and O 2 .
		tissues and roots
	Ascorbate peroxidase (APX)	Chloroplast and cytosol	Redundant to CAT. Transforms	(Sharma and Dubey, 2004)
			H 2 O 2 into H 2 O and
			dehydroascorbate (DHA)
	Monodehydroascorbate	Colocalized with APX in the	Replenishes the ascorbic acid (AA)	(Das and Roychoudhury, 2014)
	reductase (MDHAR)	peroxisome	reservoir
	Dehydroascorbate reductase	Intracellular and in the apoplast	Reduces DHA to AA using	(Eltayeb et al., 2007)
	(DHAR)		glutathione (GSH) as a reductant
	Glutathione reductase (GR)	Chloroplast, mitochondria and	Maintain a high cellular
		cytosol
					2011)
	RBOHC (AT5G51060)	In roots, is expressed in the	It is required for the production of	(Mhamdi and Van Breusegem,
		epidermis, TZ, EZ, DZ and in	reactive oxygen species that	2018a, 2018b; Foreman et al.,
		elongating root hairs. RBOHC	regulate cell expansion through	2003)
		actively produces OH À in the	the activation of Ca 2+ channels.
		apoplast at the tip of the root hair.	His expression is increased in
			potassium starvation. Participates
			in root hair elongation. rbohc
			mutants shows shorter root hairs

GSH:GSSG ratio, reducing glutathione disulfide (GSSG) into glutathione (GSH).

[START_REF] Das | Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants[END_REF]

Guaiacol peroxidase (GP) Active both intracellular and extracellular Remove of H 2 O 2 during either regular metabolism or oxidative burst. (Saini et al., 2018) RBOHs RBOHF (AT1G64060) RBOHD (AT5G47910) Roots: endodermis, lateral roots and vascular tissues; stems, seedlings, inflorescences, leaves and guard cells. RBOHF is phosphorylated by CIPK26, binding Ca +2 . Besides interacts with SRC2. It is upregulated by aba. RBOHD can interacts with BIK1 and PBL13 Atrbohf and Atrbohd control ROI spatial production Are required for CS formation, producing H 2 O 2 . The number and density of LR increase in the lossof-function mutants of rbohd and rbohf, also show lower H 2 O 2 and O 2 -concentration in the root cap, MZ and EZ as compared to the WT. But has and increase of O 2 -in the DZ increasing LR density in rbohd and rbohf. RBOHD and RBOHF negatively regulate LRP formation and LR emergence by downregulating the peroxidase activity (Lee et al., 2013; Li et al., 2014; Franke, 2015; Pedreira et al., RBOHE (AT1G19230) Expressed in roots: lateral root; inflorescences, leaves and stems. GUS reporter shows accumulation of RBOHE at the starting site of the lateral root Loss-of-function mutant rbohe delays the development of the lateral root (Chapman et al., 2019) (Continued on next page) ll OPEN ACCESS iScience 24, 101978, January 22, 2021 3 iScience Review

Table 1 .

 1 Continued

			Functional evidence, mutant
	Gene name/protein	Subcellular localization	analysis, phenotypes	References

iScience Review Table 1 .

 Review1 Continued

			Functional evidence, mutant
	Gene name/protein	Subcellular localization	analysis, phenotypes	References
	Glutathione peroxidase (GPX)	Lateral root	gpx mutants develop larger	(Choudhary et al., 2020)
	family		lateral root primordia, indicating
			that the GPX family plays a role in
			regulating root architecture,
			especially GPX1 and GPX7,
			having a critical role in
			development and formation of
			the lateral root
	ROS sensor
	HYDROGEN PEROXIDE-	HPCA1 is localized to the plasma
	INDUCED Ca 2+ INCREASES 1	membrane and is activated by
	(HPCA1) (AT5G49760)

iScience Review Table 1 .

 Review1 Continued

	ll
	OPEN ACCESS
			Functional evidence, mutant
	Gene name/protein	Subcellular localization	analysis, phenotypes	References
	MYB domain protein 36 (MYB36)	Leaves, roots endodermis, lateral	It promotes differentiation of the	(Cui et al., 2014; Kamiya et al.,
	(AT5G57620)	root and seedlings. Directly	endodermis during root	2015; Liberman et al., 2015;
		upregulated by SCR	development. Regulates the	Ferna ´ndez-Marcos et al., 2017)
			spatial expression of genes
			involved in positioning and build
			of CSs in the root endodermis (i.e.,
			CASPs, PRX64, and ESB1).
			Loss-of-function mutants, myb36,
			show deficit CS, with an abnormal
			distribution of lignin in
			endodermal cells. The mutant
			alleles myb36-5 and myb36-2 had
			less LRs verse the WT
	Like sex four 2 (LSF2)	Widely expressed, especially in	lsf2-1 KO mutants showed lower	(Zhao et al., 2016)
	(AT3G10940)	root hair	O2-generation rate but higher
			levels of H2O2 upon oxidative
			stress treatments. LSF2 interacts
			with MPK8, which regulates the
			cytosolic redox balance
	Feronia (FER) (AT3G51550)	Widely expressed, especially in	FER acts as an upstream regulator	(Chapman et al., 2019)
		root hairs. It is induced by	for the Rac/Rop-signaling
		brassinosteroids.	pathway that controls ROS-
			mediated root hair development.
			fer and rhd2 mutants shows short
			root hairs, and a decreased in ROS
			accumulation. FER interacts with
			ROP2, promoting radical hair
			growth upstream of RBOHC,
			interacts with RopGEF1, RALF1,
			ROP2 and BRL3
	Root hair defective six like4 (RSL4)	Root hair, leaves, and flowers.	RSL4 is involved in the regulation	(Mangano et al., 2017; Chapman
	(AT1G27740)	Promotes post mitotic cell growth	of root hair elongation. KO rsl4	et al., 2019)
		in root hair cells.	plants have no root hair. RSL4 is
		Induced by jasmonate (JA) and	controlled by ARFs, inducing
		low-phosphate conditions	localized ROS synthesis. Has
			targets genes that promotes root
			hair growth, like GBF2, EXO70A1,
			CPK11 and SAC1. RSL4 is a direct
			transcriptional target of RHD6.
			RSL4 can bind to the RHE in the
			regulatory region of PRX1, PRX44,
			PRX60, and PRX73
	Hypoxia responsive ERF	Lateral roots	KO mutants rap2, hre1, hre2, erf	(Shukla et al., 2019)
	genes(HRE1 and HRE2)		have more LRs compared to the
	Ethylene response factor genes		WT, these mutants affect the
	(ERF and RAP2)		delayed emergence in LR
			development
				(Continued on next page)

6 iScience 24, 101978, January 22, 2021 iScience Review reaction, fatty acid b-oxidation by acyl Co-A oxidase, and an enzymatic reaction of flavin oxidases. Furthermore, with reduced CO 2 availability during photosynthesis, RUBISCO binds O 2 and oxygenates ribulose-1,5-bisphosphate into glycolate. The latter is subsequently oxidized to glyoxylate in the peroxisome with concomitant production of hydrogen peroxide. Likewise, superoxide radicals are produced by xanthine oxidase in the peroxisomal matrix and by NADPH:ferricyanide reductase in the peroxisomal membrane (Del Rı ´o and Lo ´pez-Huertas, 2016). Moreover, two enzymatic families contribute to the apoplastic ROS production in a controlled manner: the respiratory burst oxidative homologs (RBOHs) (Orman-Ligeza et al., 2016) and the class III peroxidases (PRXs)

Table 1 .

 1 Continued

			Functional evidence, mutant
	Gene name/protein	Subcellular localization	analysis, phenotypes	References
	UPBEAT1 (UPB1) (AT2G47270)	Expressed in the root vascular	UPB1 manipulates the ROS	(Tsukagoshi et al., 2010; Manzano
		tissue and in root hairs and lateral	homeostasis, regulating cellular	et al., 2014)
		root caps. 35S:UPB1-3YFP,	division and differentiation. upb1
		showed reduced root length and a	KO mutants had more and longer
		decrease in cortex cell number in	emerging LRs compared to WT,
		the MZ	another mutant upb1-1, shows
			significant increase in the number
			of cortical cells, indicating
			enlargement of the meristem.
			UPB1 controls the expression of
			several peroxidases (PRX39, 40,
			and 57)

  Box 2. Tool examples for ROS detection in plant cellsTools for ROS detectionDiaminobenzidine (DAB) and nitro blue tetrazolium (NBT) staining. Both staining methods are used to visualize H 2 O 2 and superoxide radicals. DAB and NBT are not specific or direct measurements of both ROS, and color formation does not always reflect the levels of the desired ROS. NBT staining can reflect the presence of ascorbate or the activity of dehydrogenases, while DAB brownish color accumulates in the presence of higher peroxidase activity. Dihydroethidium (DHE) is also used to detect O 2 .-. Dichlorofluorescein (DCF)-derived fluorescent dyes. DCF is widely used for quantification of H 2 O 2 although it quantifies total ROS. This method is not very reliable and is not specific. Dichlorofluorescin (DCFH) does not react with H 2 O 2 or other ROS directly. ROS imaging can be further complicated by the presence of endogenous autofluorescent compounds. Other fluorescent dyes exist such as BES-H 2 O 2 -Ac to detect H 2 O 2 (Tsukagoshi et al., 2010). Amplex Red (AR) and Amplex Ultra Red (AUR) fluorescent dyes. AR is used for cytoplasmic H 2 O 2 , while AUR is employed for extracellular-apoplastic H 2 O 2 since it cannot go through the plasma membrane. Both, AU/AUR, undergoes one electron oxidation and yields the fluorescent product resorufin, a reaction with 1:1 (AR/AUR: H 2 O 2 ) stoichiometry, in which concentration of horseradish peroxidase and pH play important roles. These two dyes have been used to track H 2 O 2 levels in several plant tissues

The thiol groups of Cys residues are targets for oxidation to sulfenic acids by H 2 O 2 , and these sites are the place for extracellular

  b. ROS fluctuations are tightly connected with Ca 2+ signals (e.g. polar growing cells like root hairs). However, it is not clear how these two signals are interconnected. In this context, it is known that Ca 2+ activates RBOHs, but which Ca 2+ channels are activated by ROS (e.g. H 2 O 2 ) remain unknown. In addition, it is unknown if this process is direct and not mediated by other components (e.g. CARD1/HPCA1 or other kinases). c. How apoplastic ROS pool is coordinated with the ''cytoplasmic'' and ''organellar'' ROS pools in order to maintain a coherent ROS homeostasis in the plant cells along growth and development? The use of multiple genetically encoded ROS sensors targeted to different subcellular zones will allow us to get a high-resolution spatial map distribution of ROS species.

	iScience
	Review 3 Chapter II: Arabidopsis thaliana Pyrenean Populations under
	Abiotic Stresses
	3.1 Preface
	Climate change affects the development of plants by disrupting their optimal environments and
	hence exposing them to various abiotic stresses. For instances, plants are frequently facing thermal
	and saline constraints to which they must adapt to ensure their survival (Gray and Brady 2016; Piao
	et al. 2019; Yáñez-López et al. 2012). In this project, the adaptation of plants to environmental
	stresses has been studied using the existing intra-specific natural variation in 30 populations of the
	model plant Arabidopsis thaliana.
	Chapter II:
	Arabidopsis thaliana
	Pyrenean Populations
	under Abiotic Stresses

The studied A. thaliana populations have been gathered from the Pyrenees Mountains in southwest France. This region is particularly vulnerable to climate change as all the regional studies from Andorra, France, and Spain, and the general studies from the whole Pyrenees range indicate a clear increase in temperature at every moment of the year

[START_REF] López-Moreno | Effects of climate change on the intensity and frequency of heavy snowfall events in the Pyrenees[END_REF][START_REF] Marcer | Results of 50 years of climate reanalysis in the French Pyrenees (1958-2008) using the SAFRAN and CROCUS models[END_REF]

Figure 1 b, Supp. Figures 1→6, Supp. Table 2).

  5.09 mm), moderate at OS (Rank=22/32; 12.35 mm), and among the longest under HS (Rank=29/32; 18.79 mm), while the PRL of Sha were moderate under CS (Rank=12/32), and among longest at OS and HS (Ranks=32/32 and 28/32) (

  . Fifth, AtPrx39 acts in lignification at the level of the Casparian strip(Rojas-Murcia et al. 2020). Sixth, AtPrx53 contributes to the lignification in the stem(Shigeto et

									By Genotype																	By Treatment
		CNS_Eaux_Col0	CS_Eaux_Col0	ONS_Eaux_Col0	ONS_Grip_Col0	ONS_Herr_Col0	OS_Grip_Col0	HNS_Herr_Col0	HS_Herr_Col0	Col0_CNS_ONS	Col0_CS_ONS	Col0_OS_ONS	Col0_HNS_ONS	Col0_HS_ONS	Eaux_CNS_ONS	Eaux_CS_ONS	Grip_OS_ONS	Herr_HNS_ONS	Herr_HS_ONS
	Class III Prx	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR	FC	FDR
	AtPrx01	1.52	0.00	-1.90	0.02	NA	NA	NA	NA	1.50	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-5.63	0.00	2.24	0.00	-1.96	0.00 NA	NA	-2.03	0.00	-4.76	0.00 NA	NA	-2.01	0.00
	AtPrx02	NA	NA	NA	NA	NA	NA	NA	NA	3.93	0.02	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx03	NA	NA	NA	NA	-1.59	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx04	NA	NA	NA	NA	NA	NA	-1.87	0.00	-1.52	0.05	-2.44	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.93	0.00	-1.65	0.03 NA	NA	-2.69	0.00 NA	NA	NA	NA	NA	NA
	AtPrx05	NA	NA	NA	NA	NA	NA	-2.60	0.01	-2.71	0.01	-3.37	0.01	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-3.98	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx06	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx07	2.54	0.00	NA	NA	NA	NA	NA	NA	NA	NA	1.84	0.00	NA	NA	NA	NA	NA	NA	NA	NA	-3.25	0.00 NA	NA	-1.72	0.00	2.00	0.00 NA	NA	-1.92	0.00 NA	NA	-1.79	0.00
	AtPrx08	5.23	0.00	NA	NA	1.84	0.00	5.16	0.00	3.69	0.00	4.65	0.00	NA	NA	NA	NA	NA	NA	NA	NA	-4.04	0.00	4.22	0.00	3.03	0.00	2.06	0.01	-2.14	0.00	-4.58	0.00 NA	NA	NA	NA
	AtPrx09	NA	NA	NA	NA	NA	NA	-2.23	0.00	-2.94	0.00	-2.24	0.00	-2.31	0.02	-2.26	0.00 NA	NA	NA	NA	NA	NA	NA	NA	-1.51	0.00 NA	NA	1.52	0.02 NA	NA	NA	NA	NA	NA
	AtPrx10	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-5.06	0.00	NA	NA	NA	NA	4.33	0.00	18.44	0.00	15.87	0.00 NA	NA	NA	NA	NA	NA	5.40	0.00 NA	NA	NA	NA	NA	NA
	AtPrx11	NA	NA	-1.64	0.04	NA	NA	NA	NA	NA	NA	-1.52	0.01	NA	NA	NA	NA	NA	NA	1.98	0.00 NA	NA	NA	NA	NA	NA	NA	NA	1.59	0.01 NA	NA	NA	NA	NA	NA
	AtPrx12	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.57	0.01 NA	NA	NA	NA	-1.70	0.00 NA	NA	NA	NA
	AtPrx13	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx14	NA	NA	NA	NA	8.95	0.00	3.90	0.05	6.93	0.00	11.30	0.00	NA	NA	7.23	0.03 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx15	-1.61	0.02	-1.75	0.04	-1.62	0.01	-4.05	0.00	-2.37	0.00	NA	NA	NA	NA	NA	NA	-3.30	0.00	1.94	0.00 NA	NA	NA	NA	NA	NA	-3.23	0.00	1.79	0.00	2.72	0.00 NA	NA	NA	NA
	AtPrx16	1.60	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.54	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx17	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.82	0.00 NA	NA	NA	NA	1.64	0.00	1.56	0.01	-2.44	0.01 NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx18	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx19	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx20	NA	NA	NA	NA	NA	NA	-1.66	0.00	NA	NA	-1.67	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx21	NA	NA	NA	NA	NA	NA	-1.66	0.00	-2.21	0.00	NA	NA	-3.15	0.00	-2.63	0.00	-2.14	0.00	-2.47	0.00	-1.74	0.00	-1.50	0.01	-1.80	0.00	-2.09	0.00	-1.78	0.00 NA	NA	-2.15	0.03	-2.10	0.02
	AtPrx22	-1.78	0.00	NA	NA	NA	NA	-1.76	0.00	-3.04	0.00	NA	NA	-3.06	0.00	-5.75	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx23	-2.61	0.00	-2.07	0.00	-1.87	0.00	-1.78	0.00	-1.59	0.00	NA	NA	NA	NA	-1.78	0.00 NA	NA	1.53	0.02 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx24	2.12	0.00	NA	NA	NA	NA	NA	NA	1.50	0.00	NA	NA	NA	NA	NA	NA	-2.09	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.65	0.03 NA	NA	NA	NA	NA	NA
	AtPrx25 -11.18	0.00	-4.66	0.03	-1.98	0.00	5.18	0.00	3.81	0.00	4.09	0.00	3.52	0.00	4.50	0.00	-6.38	0.00	-3.25	0.00 NA	NA	NA	NA	NA	NA	-35.26	0.00	-7.69	0.00 NA	NA	NA	NA	NA	NA
	AtPrx26	-2.11	0.00	NA	NA	-2.38	0.00	-2.73	0.00	-2.86	0.00	NA	NA	NA	NA	NA	NA	-1.50	0.05 NA	NA	NA	NA	-2.09	0.00	-2.67	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx27	1.62	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.69	0.00 NA	NA	NA	NA	NA	NA	-1.69	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx28	NA	NA	NA	NA	22.75	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx29	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx30	-3.52	0.00	-5.34	0.00	-5.04	0.00	-3.64	0.00	-1.86	0.00	-4.08	0.00	-1.88	0.01	-1.91	0.00 NA	NA	-1.60	0.00 NA	NA	NA	NA	NA	NA	NA	NA	-1.71	0.00 NA	NA	NA	NA	NA	NA
	AtPrx31	NA	NA	-1.95	0.01	-1.58	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx32	-1.57	0.00	NA	NA	NA	NA	NA	NA	-1.56	0.00	NA	NA	-1.82	0.01	-2.02	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx33	NA	NA	NA	NA	3.18	0.00	6.13	0.00	NA	NA	5.73	0.02	10.46	0.00	20.80	0.00 NA	NA	NA	NA	NA	NA	-6.10	0.02	-12.43	0.00 NA	NA	-4.12	0.00 NA	NA	NA	NA	NA	NA
	AtPrx34	-2.45	0.00	-1.88	0.00	NA	NA	-2.50	0.00	-1.72	0.00	-1.64	0.00	-2.24	0.00	NA	NA	NA	NA	-1.89	0.00	-1.69	0.00 NA	NA	NA	NA	NA	NA	-2.56	0.00 NA	NA	NA	NA	NA	NA
	AtPrx35	-1.95	0.00	-3.25	0.00	-2.00	0.00	NA	NA	NA	NA	3.51	0.00	-2.32	0.00	NA	NA	NA	NA	NA	NA	-3.61	0.00	2.07	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx36	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx37	2.11	0.00	NA	NA	NA	NA	NA	NA	1.56	0.00	NA	NA	1.70	0.00	1.75	0.00	-1.76	0.00 NA	NA	NA	NA	-1.68	0.00	-2.02	0.00 NA	NA	NA	NA	NA	NA	NA	NA	-1.77	0.00
	AtPrx38	-3.60	0.00	NA	NA	NA	NA	-1.78	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.56	0.03	-2.54	0.00	-3.89	0.00	-1.89	0.05 NA	NA	NA	NA	-2.14	0.02
	AtPrx39	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-2.01	0.00	-1.63	0.00	-1.96	0.00	-1.85	0.00 NA	NA	1.63	0.00 NA	NA	NA	NA	-1.67	0.00 NA	NA	NA	NA	NA	NA
	AtPrx40	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1.60	0.05	NA	NA	NA	NA	-1.62	0.02 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx41	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx42	NA	NA	NA	NA	NA	NA	-2.06	0.00	-1.55	0.00	-1.92	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx43	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx44	2.72	0.00	NA	NA	NA	NA	1.61	0.00	NA	NA	2.27	0.00	NA	NA	NA	NA	NA	NA	NA	NA	-2.81	0.00 NA	NA	-2.06	0.00	2.11	0.00	-1.54	0.03	-1.98	0.00 NA	NA	-2.17	0.00
	AtPrx45	NA	NA	NA	NA	NA	NA	NA	NA	-1.52	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx46	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx47	1.54	0.00	NA	NA	NA	NA	-1.50	0.00	NA	NA	-1.65	0.00	NA	NA	NA	NA	-1.71	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1.51	0.04
	AtPrx48	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx49	-2.53	0.00	-1.77	0.03	NA	NA	-2.46	0.00	NA	NA	-1.70	0.00	NA	NA	NA	NA	-2.24	0.00	2.30	0.00	1.73	0.00 NA	NA	NA	NA	-4.36	0.00	1.65	0.00	2.53	0.00 NA	NA	NA	NA
	AtPrx50	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1.61	0.00	1.51	0.00	1.88	0.00 NA	NA	-1.79	0.00 NA	NA	NA	NA	1.62	0.01
	AtPrx51	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx52	NA	NA	NA	NA	33.58	0.00	NA	NA	4.51	0.04	-4.78	0.02	NA	NA	NA	NA	NA	NA	12.10	0.00	6.01	0.00 NA	NA	NA	NA	-7.10	0.02 NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx53	NA	NA	NA	NA	NA	NA	-3.19	0.00	-2.69	0.01	NA	NA	-3.30	0.01	NA	NA	NA	NA	NA	NA	NA	NA	2.36	0.00 NA	NA	-5.32	0.01	-4.16	0.01 NA	NA	NA	NA	NA	NA
	AtPrx54 -10.32	0.00	NA	NA	NA	NA	-5.48	0.00	-4.06	0.00	NA	NA	-2.60	0.03	NA	NA	NA	NA	NA	NA	-1.97	0.01 NA	NA	-1.65	0.04	-9.51	0.00 NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx55	NA	NA	NA	NA	NA	NA	1.66	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1.67	0.02 NA	NA	NA	NA	NA	NA	1.76	0.00	1.83	0.00 NA	NA	NA	NA	NA	NA
	AtPrx56	1.56	0.00	NA	NA	NA	NA	2.38	0.00	NA	NA	2.32	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1.67	0.00 NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx57	1.59	0.00	NA	NA	NA	NA	NA	NA	-1.55	0.00	NA	NA	-1.70	0.03	NA	NA	NA	NA	NA	NA	-1.81	0.00 NA	NA	-1.79	0.00	1.63	0.01 NA	NA	NA	NA	NA	NA	-1.60	0.03
	AtPrx58	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3.92	0.02	5.22	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx59	NA	NA	NA	NA	3.49	0.00	3.12	0.00	2.85	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx60	2.08	0.00	NA	NA	NA	NA	1.56	0.01	NA	NA	NA	NA	-1.85	0.04	NA	NA	NA	NA	NA	NA	-5.01	0.00	2.22	0.00 NA	NA	2.68	0.00 NA	NA	-4.30	0.00 NA	NA	NA	NA
	AtPrx61	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2.57	0.02	NA	NA	-1.66	0.04 NA	NA	NA	NA	-2.57	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx62	-2.61	0.00	-3.73	0.00	NA	NA	-3.30	0.00	NA	NA	-1.86	0.02	NA	NA	NA	NA	NA	NA	2.12	0.01 NA	NA	-1.72	0.00	-1.80	0.00 NA	NA	NA	NA	2.11	0.02 NA	NA	NA	NA
	AtPrx63	NA	NA	NA	NA	NA	NA	-2.01	0.00	NA	NA	-1.80	0.04	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx64	1.57	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx65	-7.40	0.00	NA	NA	NA	NA	NA	NA	-2.23	0.01	NA	NA	NA	NA	NA	NA	NA	NA	-3.51	0.01 NA	NA	3.93	0.00	1.90	0.01	-9.04	0.00	-3.51	0.01 NA	NA	4.09	0.00	4.57	0.00
	AtPrx66	1.56	0.01	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-1.55	0.00	-2.53	0.00	-1.84	0.00 NA	NA	NA	NA	1.64	0.00 NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx67	NA	NA	20.53	0.02	5.22	0.00	NA	NA	NA	NA	NA	NA	77.47	0.00	NA	NA	NA	NA	NA	NA	NA	NA	-50.84	0.00	-9.75	0.01 NA	NA	NA	NA	-62.68	0.00 NA	NA	-5.94	0.03
	AtPrx68	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx69	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx70	3.13	0.00	NA	NA	2.91	0.00	3.32	0.00	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-3.36	0.00	-3.39	0.00 NA	NA	NA	NA
	AtPrx71	3.58	0.00	4.64	0.00	3.99	0.00	2.92	0.00	2.38	0.00	3.37	0.00	3.54	0.00	4.56	0.00	1.79	0.00 NA	NA	-1.79	0.00	-1.73	0.00	-3.26	0.00	1.62	0.00 NA	NA	-1.55	0.00 NA	NA	-1.66	0.01
	AtPrx72	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
	AtPrx73	3.21	0.00	NA	NA	NA	NA	NA	NA	NA	NA	1.77	0.01	NA	NA	NA	NA	NA	NA	NA	NA	-4.13	0.00	1.99	0.00 NA	NA	2.97	0.00 NA	NA	-3.37	0.00 NA	NA	-1.83	0.00

The second arm comprises nonenzymatic antioxidants such as ascorbic acid (ASC), reduced glutathione (GSH), carotenoids, flavonoids, and proline[START_REF] Eltayeb | Overexpression of monodehydroascorbate reductase in transgenic tobacco confers enhanced tolerance to ozone, salt and polyethylene glycol stresses[END_REF].See also Table1for more details.

iScience 24, 101978, January 22, 2021

iScience 24, 101978,January 22, 2021

Acknowledgements

ACKNOWLEDGMENTS

The authors are thankful to Universite ´Paul Sabatier-Toulouse III (France) and CNRS for supporting their research work. This work was supported by the French Laboratory of Excellence project ''TULIP'' (ANR-10-LABX-41; ANR-11-IDEX-0002-02) and by grants from ANPCyT Argentina (PICT2016-0132 and PICT2017-0066) and Fondo Nacional de Desarrollo Cientı ´fico y Tecnolo ´gico (1200010) and Instituto Milenio iBio -Iniciativa Cientı ´fica Milenio, MINECON Chile to JME.

AUTHOR CONTRIBUTIONS

A.E. analyzed the bibliography, wrote the paper, and helped on the figures' design. Y.d.C.R.G. analyzed the bibliography and helped on the figures' design. A.E, J.M.E., and Ch.D. analyzed the bibliography, supervised the project, and wrote the paper. This manuscript has not been published and is not under consideration for publication elsewhere. All the authors have read the manuscript and have approved this submission.

DECLARATION OF INTERESTS

The authors declare no competing interests.

Gene expression analyses

TPM (Transcripts Per Million), a normalization method for RNA-seq, was selected as the expression value (TPM = RPKM × 10 6 ∑ RPKM ) to normalize the sequencing depth and gene length within the samples.

The RPKM (Reads Per Kilobase of transcript per Million mapped reads) scales by the gene length, assuming that longer transcripts would generate more sequencing reads, and it is hence computed accordingly (RPKM = total exon reads mapped reads (millions)×exon length (KB) ). The outcome of the RNA-seq analyses was presented by gene-level expression tracks (GEs) holding information about read counts and expression values for each gene in the different populations under the various treatments.

Gene expression visualization

Heat maps were used to visualize the GE in the different samples, in which the samples clustered in columns and the genes in rows. For each gene, logCPM or (Counts Per Million) were computed using the effective sizes of the libraries generated by the TMM (Trimmed Mean by M value) normalization, followed by a Z-score normalization across the samples. Euclidean distance and complete linkage were used to perform the hierarchical clustering. The hierarchical clustering of the samples or genes reflected the similarity in their expression profiles.

Differential gene expression analyses

The analyses of the genes differential expression (DE) were performed on the whole transcriptome using statistical differential expression tests for the set of expression tracks with the associated metadata by multi-factorial statistics based on a negative binomial linear model (GLM), while assuming that the read counts follow a negative binomial distribution (McCarthy et al. 2012). The effects of both the treatment and the genotype were tested for the DE analyses, as both factors contribute to the differential expression of genes between the populations under the different treatments. A threshold of absolute fold change (FC) greater than or equal to 1.5 and false discovery rate p-value (FDR) less than or equal to 0.05 were used to detect the significant differentially expressed genes (DEGs).

Peroxidase activity

The peroxidase activity was assayed using guaiacol/H2O2. The total proteins were extracted with 10 mM Tris Buffer (EU0011, Euromedex), containing 20 mM EDTA (EU0007, Euromedex), and 5% PVP (PVP40-50G, Sigma-Aldrich). The protein concentrations were measured following the Bradford's protein quantification assay in 96-well plates (260860, Thermo Fisher Scientific). After the addition of the diluted Bradford reagent (1X) (39222, SERVA), the optical densities of the samples were recorded at 590 nm. Formerly, the spectrophotometer (BioTek Elx 808) was calibrated using increasing quantities from 1 to 5 µg of bovine serum albumin (BSA) (1005-70, Euromedex). To estimate the peroxidase activity, an 8:1 ratio of 200 mM phosphate buffer pH 6 containing 0.125% guaiacol (50880, Sigma-Aldrich) was added to 11 mM H2O2 (412072, CARLO ERBA) and incubated immediately with the protein extracts. OD470 nm was successively registered at 1 and 2 minutes after the reaction started. The peroxidase specific activity was calculated (nanokatal/mg proteins). Twoway ANOVA tests for multiple independent samples were carried out to determine the effects of the different treatments and the populations on the peroxidase activity [START_REF] Hothorn | Simultaneous inference in general parametric models[END_REF]).

Results

The roots of the studied A. thaliana populations were measured under six growth conditions (CNS: cold no salt (16°C, 0 mM of NaCl), CS: cold and salt (16°C, 50 mM of NaCl), ONS: optimal no salt (22°C, 0 mM of NaCl), OS: optimal and salt (22°C, 50 mM of NaCl), HNS: heat no salt (28°C, 0 mM of NaCl), HS: heat and salt (28°C, 50 mM of NaCl). Additionally, their seed germination kinetics was observed to mark the initiation of their root development. Afterwards, a transcriptional study was performed on Col-0 and on selected Pyrenean populations that were found tolerant to the applied stresses to highlight genes involved in responses to abiotic stresses.

Root development

The objective of the performed phenotyping was to describe the primary root growth of the multiple populations under different growth conditions. For this aim, the RGRs (in mm/day) as well as the PRLs (in mm) were thoroughly analyzed. The aim was to highlight on one hand the natural plasticity of the root development in the different A. thaliana populations, and on another hand, the differential impacts of temperature and salt stresses on this trait among the studied populations.

Root development in Col-0 and Sha

Col-0 and Sha were respectively studied as reference populations to low-and high-altitude environments. In fact, Col-0 and Sha respectively displayed maximal RGRs of 2.88 and 2.95 mm/day under ONS, faster than those under CNS by 67% and 73% (0.96 and 0.78 mm/day), and under HNS by 17% and 24% (2.4 and 2.25 mm/day). In reference to the 32 phenotyped populations, the RGR of Col-0 was among the fastest under ONS (Rank=31/32) and CNS (Rank=30/32) but moderate under HNS (Rank=23/31). Similarly, the RGR of Sha was the highest under ONS (Rank=32/32) but moderate under both CNS and HNS (Ranks=17/32).

When salt was added to the growth media, Col-0 and Sha RGRs were significantly decelerated by 55% and 41% (1.31 and 1.75 mm/day) under OS. Additionally, the combination of cold and salt stresses further slowed their root growth by 87% (0.38 and 0.40 mm/day). However, HS did not These results suggest that the genes coding for CWPs were majorly repressed under salt and cold stresses (except for SPs genes) but induced under heat in Col-0 (e.g., pectin methyl-esterase inhibitors (AtPMEI4), xyloglucan endotransglucosylase-hydrolase (AtXTH17 and AtXTH24), and LRR receptor-like kinases). Also, CWPs genes such as those encoding the chitinases were downregulated under cold conditions but to fewer extents in the cold-tolerant population (Eaux). The salt stress also generally suppressed numerous genes in the salt-tolerant population Grip (e.g., extensins AtEXT13 and AtEXT18), but the genes involved in signaling were induced (e.g., the arabinogalactan protein family). Also, the heat stress slightly increased the expression of genes coding for LRR receptor-likekinases and wall-associated kinases in the heat tolerant population Herr. Additionally, the coldtolerant population had higher level of expression of genes coding for LRR receptor-like-kinases compared to Col-0. Also, the salt-tolerant population upregulated genes coding for structural proteins (e.g., extensins AtEXT6, AtEXT16, and AtEXT18) in response to saline conditions. Besides, less significant changes in gene expression were observed in the heat-tolerant population.

Genes encoding proteins involved in cell wall biosynthesis

The genes of the CW biosynthesis toolbox were also differentially expressed between populations and under the various treatments. In Col-0, most of these genes were downregulated under all applied stresses, most importantly under CNS (19 genes) and HS (33 genes). However, Eaux had more upregulated and less downregulated genes under CNS and CS compared to ONS. Also, Grip had few DEGs (five genes) from this toolbox under OS (one upregulated and five downregulated).

Similarly, only four genes were differentially expressed in Herr under HNS (two upregulated and two downregulated). However, the number of DEGs increased in Herr under HS (24 genes), and they were mostly downregulated (19 genes) (Figure 14 a). Upon comparing the stress-tolerant populations to Col-0, 44 DEGs were found in Eaux under CNS, and they were mostly upregulated (31 genes). However, under CS, only 17 genes were differentially

Genes encoding proteins involved in anthocyanin biosynthesis

The genes of the anthocyanin biosynthesis toolbox were upregulated in Col-0 under CNS and CS but downregulated under HNS and HS. However, under OS, only two genes were differentially expressed. Similarly, they were upregulated in Eaux under CNS and CS, and not highly regulated in Grip under OS. Furthermore, their expression in the heat tolerant population Herr did not importantly change, where only two and five genes were differentially expressed under HNS and HS (Figure 17 a).

Comparing the stress tolerant populations to Col-0 highlighted that all populations had more upregulated genes related to anthocyanin biosynthesis. For instances, Eaux had nine and five upregulated genes under CNS and CS. Likewise, Grip had nine upregulated and only two downregulated genes under OS. Also, Herr had more upregulated genes under HNS (ten genes) and HS (eight genes) (Figure 17 b, Supp. Table 13). These results suggest that anthocyanin biosynthesis coding genes are involved in the response to abiotic constraints, most importantly to cold stress. Additionally, the cold-, heat-, and salt-tolerant populations had higher expression of these genes compared to Col-0 (e.g., TT5 and AtFLS1).

Genes encoding cell wall proteins possibly involved in lipid metabolism

Testing the DE by the treatment effect highlighted that, in Col-0, the genes involved in lipid metabolism (LMPs) were downregulated moderately under CNS and CS, slightly under OS, and highly under HNS and HS. Tol illustrate, 12 genes had lower expression under CNS and CS, 4 under OS, and 25 and 28 under HNS and HS. In Eaux, only 12 genes were downregulated under CNS and CS.

However, in Grip, more genes were downregulated under OS (19 genes). As for Herr, it had mostly upregulated genes (8 genes) under HNS, but the combination of heat and salt stresses (HS) increased the number of downregulated genes (18 genes) (Figure 18 a).

Comparing by the genotypes, Eaux had more downregulated genes under CNS but more upregulated genes under CS compared to Col-0. Also, the salt stress in Grip suppressed more genes from this toolbox (14 genes). Finally, Herr, the heat-tolerant population, had more upregulated genes under HNS (18 genes) but more downregulated ones under HS in reference to Col-0 ((Figure 18 b, Supp. Table 14). These results display that lipid metabolism genes are suppressed due to abiotic stresses, most importantly due to elevated temperature in Col-0 (e.g., lipase acylhydrolases). The cold treatment decreased this repression in the tolerant population, but the salt application increased it in the salttolerant population. Lastly, these genes were more triggered in the heat-tolerant population.

Genes encoding proteins involved in thermotolerance

In Col-0, 22 genes of the thermotolerance toolbox were differentially expressed under CNS, where cold-regulated genes and genes correlated with cold and osmotic stresses were mostly upregulated, whereas small-heat shock proteins were downregulated. A similar expression pattern was obtained under CS. However, under HNS and HS, 44 and 41 genes were differential expressed, and they were mostly upregulated, especially those coding for small-heat shock proteins (Figure 19 a).

However, in Eaux, the cold-related genes were not upregulated (Figure 19 b). Similarly, in Herr, only 9 genes coding for small-heat shock proteins were upregulated under HNS, but the combined heat and salt stresses triggered the expression of these genes (17 upregulated) in addition to other genes coding for diverse proteins involved in thermotolerance (Figure 19 d). Indeed, the OS treatment slightly affected the expression of the thermotolerance genes (Figure 19 c).

Additionally, the lignin biosynthesis genes were found to be upregulated by heat in Col-0 as well as in the cold-tolerant population Eaux. In fact, lignification plays important roles in stress response as it increases the cell wall thickening by reinforcing it with a secondary cell wall (Le Gall et al. 2015). Also, the anthocyanin genes were upregulated by the applied stresses, most importantly by cold, and in all populations, especially in the stress-tolerant ones. Anthocyanin is a known stress marker, and it is involved in numerous responses such as ROS scavenging and signaling under abiotic constraints [START_REF] Kovinich | Abiotic stresses induce different localizations of anthocyanins in Arabidopsis[END_REF]. Additionally, the lipid metabolism genes were found impacted by the abiotic signals, by which they probably contributed to stress tolerance as they had higher transcription in cold-and heat-tolerant populations.

Furthermore, the thermotolerance genes were upregulated in response to heat and cold stresses. However, their induction was not detected in the tolerant populations when comparing their differential expression by the treatment effect. This may be due to the weakness of the applied stress that did not boost thermal shock responses. Yet, they were upregulated in these populations when comparing them to Col-0 by the genotype effect. In addition, the genes involved in regulating the ROS homeostasis were highly differentially expressed due to the applied stresses, but they were not importantly changing in the heat-tolerant population suggesting that the oxidative burst in this population was not significant. Indeed, ROS are notably involved in the acclimation process of the plant against abiotic limitations via regulating different stress-responsive pathways (Choudhury et al. 2017;[START_REF] Miller | Reactive oxygen signaling and abiotic stress[END_REF].

A focus on class III peroxidases

CIII Prxs were previously characterized to play key roles during the plant response to environmental cues (Shahzad et al. 2019). In this study, the expression levels of the CIII Prxs genes were associated with the multiple performed experiments to characterize the roles of particular members of this multigene family in response to abiotic constraints. Novel CIII Prxs were regulated exclusively in the tolerant populations highlighting their putative roles in providing tolerance against abiotic stresses (Figure 23, Supp. Table 18).

Acknowledgement

The authors are thankful to Université Paul Sabatier-Toulouse III (France) and CNRS for supporting their research work. This work was supported by the French Laboratory of Excellence project ''TULIP'' (ANR-10-LABX-41; ANR-11-IDEX-0002-02).

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Annex

Genomic Analysis

Genetic diversity within and among populations is essential for their adaptation to their local environments. In the past decade, single nucleotide polymorphism (SNP) has been widely adopted as an efficient molecular marker to estimate such diversity at the whole-genome level, thanks to the high-throughput sequencing. In fact, this protocol has been used exponentially used to identify thousands to millions of unbiased SNPs and to estimate the SNP frequencies across the genomes of individuals and populations, more importantly in model species such as A. thaliana [START_REF] Fischer | Estimating genomic diversity and population differentiation-an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri[END_REF]. For this aim, pools of the studied Pyrenean populations genomic DNA have been sequenced to highlight their genetic diversity using the single nucleotide polymorphism (SNP).

Genomic DNA was extracted from the rosette leaves of 3-to 4-week-old plants harvested and frozen in collection microtubes (19560, Qiagen) containing metallic beads. They were then grinded for 2 minutes at 30 Hertz using the RETSCH Mixer Mill MM 400. The obtained powder in each well was incubated with 400 µL of a DNA extraction buffer (0.5 M NaCl, 100 mM Tris, 50 mM EDTA, 1.25% sodium dodecyl sulfate (SDS) (EU0660, Euromedex), 1% PVP, 1% sodium metabisulfite (S9000, Sigma-Aldrich), 10 µg/mL RNase A (A7973, Promega), and 0.5 mg/mL proteinase K (V3021, Promega)) at 65°C for 30 minutes. After cooling and centrifugation, 130 µL of 4 M potassium acetate (P1190, Sigma-Aldrich) and 0.35 M acetic glacial acid Thermo Fisher Scientific) mixture were added, and the plate was incubated at -20°C for 30 minutes. The resulting supernatants were transferred into a 96-well column plate (016086, Dutscher), where 600 µL of the fixation buffer (8 M guanidine chloride (50937, Sigma-Aldrich) and 100% ethanol Thermo Fisher Scientific)) were added to each sample. After centrifugation, the new supernatants were transferred into 96well AcroPrep TM Advance filter plate (# VWR 738-0120, Pall Laboratory) fixed above a new 96-well column plate. The plates' block was centrifuged, and the effluents were discarded. The filters were washed twice by 650 µL of a washing buffer (1 M Tris, 0.5 M EDTA, 5 M potassium acetate, and 100% ethanol). Finally, DNA was eluted into an elution plate (016061, Dutscher) by 50 µL of Tris-EDTA buffer added to each well. The extracted genomic DNA from 1 to 5 individuals corresponding to each population were pooled together into equimolar DNA pools that were sent for next-generation sequencing (NGS) of the single nucleotide polymorphism (SNP) at GeT-PlaGe GenoToul platform.

The preliminary results of the SNP calling reported 4205497 variant positions among populations, with 4201970 single nucleotide variants (SNVs) and 57706 insertion/deletions (indels). These results will be further used to perform genome-wide-associated-studies (GWAS) to highlight SNPs that may be associated with the observed root phenotypes [START_REF] Togninalli | The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog[END_REF]. Additionally, they will be