Mamadou D Sow

Anne-Laure Le Gac

Régis Fichot

Sophie Lanciano

Alain Delaunay

Isabelle Le Jan

Marie-Claude Lesage-Descauses

Sylvie Citerne

Jose Caius

Véronique Brunaud

Ludivine Soubigou-Taconnat

Hervé Cochard

Vincent Segura

Cristian Chaparro

Christoph Grunau

Christian Daviaud

Jörg Tost

Franck Brignolas

Steven H Strauss

Marie Mirouze

Stéphane Maury

RNAI suppression of DNA methylation affects the drought stress response and genome integrity in transgenic poplar

Keywords: ddm1, DNA methylation, drought, epigenetics, hormone, mobilome, poplar, shoot apical meristem

Trees are long-lived organisms that continuously adapt to their environments, a process in which epigenetic mechanisms are likely to play a key role. Via downregulation of the chromatin remodeler DECREASED IN DNA METHYLATION 1 (DDM1) in poplar (Populus tremula x Populus alba) RNAi lines, we examined how DNA methylation coordinates genomic and physiological responses to moderate water deficit.

We compared the growth and drought response of two RNAi-ddm1 lines to wild-type (WT) trees under well-watered and water deficit/rewatering conditions, and analyzed their methylomes, transcriptomes, mobilomes and phytohormone contents in the shoot apical meristem.

The RNAi-ddm1 lines were more tolerant to drought-induced cavitation but did not differ in height or stem diameter growth. About 5000 differentially methylated regions were consistently detected in both RNAi-ddm1 lines, colocalizing with 910 genes and 89 active transposable elements. Under water deficit conditions, 136 differentially expressed genes were found, including many involved in phytohormone pathways; changes in phytohormone concentrations were also detected. Finally, the combination of hypomethylation and drought led to the mobility of two transposable elements Our findings suggest major roles for DNA methylation in regulation of genes involved in hormonerelated stress responses, and the maintenance of genome integrity through repression of transposable elements.

INTRODUCTION

As long-living organisms, trees are subjected to repeated environmental challenges over their lifetimes. During recent decades, forest decline has been reported around the world due to heat and drought episodes [START_REF] Allen | A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests[END_REF][START_REF] Anderegg | Meta-analysis reveals that hydraulic traits explain cross-species patterns of drought-induced tree mortality across the globe[END_REF]. Survival and adaptation of populations will depend on the ability of trees to cope with rapidly changing conditions. Among the potential sources of flexibility in perennials like trees, epigenetics has received growing attention [START_REF] Yakovlev | An adaptive epigenetic memory in conifers with important implications for seed production[END_REF][START_REF] Yakovlev | Transcriptional profiling of epigenetic regulators in somatic embryos during temperature induced formation of an epigenetic memory in Norway spruce[END_REF]Br€autigam et al., 2013;[START_REF] Plomion | Forest tree genomics: 10 achievements from the past 10 years and future prospects[END_REF][START_REF] Carneros | The epigenetic memory of temperature during embryogenesis modifies the expression of bud burst-related genes in Norway spruce epitypes[END_REF]Sow et al., 2018a;Amaral et al., 2020). Epigenetics is defined as the study of heritable changes that affect gene expression without changing the DNA sequence [START_REF] Russo | Epigenetic mechanisms of gene regulation[END_REF]. Considerable efforts have been made to unravel the role of epigenetics in plant developmental processes, stress responses and adaptation, but primarily in annuals [START_REF] Slotkin | Transposable elements and the epigenetic regulation of the genome[END_REF][START_REF] Colome-Tatche | Features of the Arabidopsis recombination landscape resulting from the combined loss of sequence variation and DNA methylation[END_REF][START_REF] Cortijo | Mapping the epigenetic basis of complex traits[END_REF][START_REF] Kooke | Epigenetic basis of morphological variation and phenotypic plasticity in Arabidopsis thaliana[END_REF][START_REF] Raju | An epigenetic breeding system in soybean for increased yield and stability[END_REF][START_REF] Schmid | Extensive epigenetic reprogramming during the life cycle of Marchantia polymorpha[END_REF], while its role in perennials like trees still needs clarification (Amaral et al., 2020).

DNA methylation is one of the most studied epigenetic marks (Zhang et al., 2018a). It is important in both plants and mammals for many biological processes, such as imprinting, and its disruption can lead to developmental abnormalities [START_REF] Vongs | Arabidopsis thaliana DNA methylation mutants[END_REF][START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF]Zhang et al., 2018b). In addition to controlling gene expression, DNA methylation is also involved in the maintenance of genome integrity by silencing transposable elements (TEs), preventing them from spreading within the host genome [START_REF] Fultz | Silencing of active transposable elements in plants[END_REF][START_REF] Ikeda | The role of DNA methylation in transposable element silencing and genomic imprinting[END_REF]. DNA methylation is required to silence TEs located in the heterochromatin, and a decrease in DNA methylation level can result in their reactivation [START_REF] Lippman | Role of transposable elements in heterochromatin and epigenetic control[END_REF][START_REF] Mirouze | Selective epigenetic control of retrotransposition in Arabidopsis[END_REF][START_REF] Mirouze | Epigenetic contribution to stress adaptation in plants[END_REF]. One of the bestknown examples of the control of TEs by DNA methylation comes from the study of mutants of chromatin remodeling complexes which are involved in maintenance of DNA methylation, such as Decreased DNA Methylation I (DDM1, a SWI/SNF family member). Its depletion affects the distribution of methylation in all sequence contexts [START_REF] Vongs | Arabidopsis thaliana DNA methylation mutants[END_REF][START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF]. DDM1 was first identified in Arabidopsis through a forward genetic mutant screen causing a 'decrease in DNA methylation' [START_REF] Vongs | Arabidopsis thaliana DNA methylation mutants[END_REF]. Several studies further characterized ddm1 mutants in Arabidopsis [START_REF] Saze | Heritable epigenetic mutation of a transposonflanked Arabidopsis gene due to lack of the chromatin-remodeling factor DDM1[END_REF][START_REF] Yao | ddm1 plants are sensitive to methyl methane sulfonate and NaCl stresses and are deficient in DNA repair[END_REF][START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Cortijo | Mapping the epigenetic basis of complex traits[END_REF][START_REF] Ito | Genome-wide negative feedback drives transgenerational DNA methylation dynamics in Arabidopsis[END_REF][START_REF] Kawanabe | Role of DNA methylation in hybrid vigor in Arabidopsis thaliana[END_REF], turnip [START_REF] Fujimoto | Hypomethylation and transcriptional reactivation of retrotransposon-like sequences in ddm1 transgenic plants of Brassica rapa[END_REF][START_REF] Sasaki | RNAi-independent de novo DNA methylation revealed in Arabidopsis mutants of chromatin remodeling gene DDM1[END_REF], maize [START_REF] Li | Inheritance patterns and stability of DNA methylation variation in maize near-isogenic lines[END_REF], and rice [START_REF] Higo | DDM1 (Decrease in DNA Methylation) genes in rice (Oryza sativa)[END_REF][START_REF] Tan | Analysis of chromatin regulators reveals specific features of rice DNA methylation pathways[END_REF]. Recently DDM1 has been shown to mediate the deposition of H2AW, a histone variant important for heterochromatin [START_REF] Osakabe | The chromatin remodeler DDM1 prevents transposon mobility through deposition of histone variant H2A[END_REF] ;

In poplar trees, RNAi-ddm1 lines have been previously obtained by targeting the transcripts of the two orthologous DDM1 paralogs in Populus tremula x Populus alba cv INRA 717-1B4 [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF]. Under standard glasshouse conditions, the regenerated lines did not show developmental defects, although newly formed leaves displayed necrotic spots after a cycle of dormancy [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF]. These lines, which have been stabilized in vitro for several years now, represent valuable tools with which to clarify the functional role of DNA methylation in perennials such as forest trees. As a model tree with important genomic resources [START_REF] Tuskan | The genome of Black Cottonwood, Populus trichocarpa (Torr. & Gray)[END_REF][START_REF] Jansson | Populus: a model system for plant biology[END_REF], poplar (Populus spp.) has been a prime system for the study of the ecophysiological and molecular bases of the drought response [START_REF] Monclus | Impact of drought on productivity and water use efficiency in 29 genotypes of Populus deltoides9Populus nigra[END_REF][START_REF] Street | The genetics and genomics of the drought response in Populus[END_REF][START_REF] Bogeat-Triboulot | Gradual soil water depletion results in reversible changes of gene expression, protein profiles, ecophysiology, and growth performance in Populus euphratica, a poplar growing in arid regions[END_REF][START_REF] Cohen | Comparative transcriptomics of drought responses in Populus: a meta-analysis of genome-wide expression profiling in mature leaves and root apices across two genotypes[END_REF][START_REF] Hamanishi | Drought induces alterations in the stomatal development program in Populus[END_REF][START_REF] Fichot | Vulnerability to drought-induced cavitation in poplars: synthesis and future opportunities[END_REF]. Differences in global DNA methylation levels among poplar hybrid genotypes have been shown to correlate with biomass production under water deficit [START_REF] Gourcilleau | DNA methylation and histone acetylation: genotypic variations in hybrid poplars, impact of water deficit and relationships with productivity[END_REF][START_REF] Raj | Clone history shapes Populus drought responses[END_REF][START_REF] Gac | Developmental, genetic and environmental variations of global DNA methylation in the first leaves emerging from the shoot apical meristem in poplar trees[END_REF]. Epigenomic analyses have further shown that water deficit induces targeted changes in DNA methylation patterns at phytohormone-related genes, thereby favoring phenotypic plasticity [START_REF] Lafon-Placette | Changes in the epigenome and transcriptome of the poplar shoot apical meristem in response to water availability affect preferentially hormone pathways[END_REF]. This has raised the question of a possible link between epigenetics and phytohormone signaling/ synthesis in the regulation of plant plasticity, particularly in primary meristems where development is initiated [START_REF] Maury | Phytohormone and chromatin crosstalk: The missing link for developmental plasticity?[END_REF]. In addition, it has been shown that winter-dormant shoot apical meristems (SAMs) of poplars grown under field conditions can keep an epigenetic memory of a summer drought experienced during the growing season through modifications in DNA methylation [START_REF] Gac | Winter-dormant shoot apical meristem in poplar trees shows environmental epigenetic memory[END_REF]Sow et al., 2018b). The role of epigenetic memory in trees, besides poplar, in response to biotic and abiotic stresses or priming is becoming increasingly documented [START_REF] Yakovlev | Temperaturedependent differential transcriptomes during formation of an epigenetic memory in Norway spruce embryogenesis[END_REF][START_REF] Carneros | The epigenetic memory of temperature during embryogenesis modifies the expression of bud burst-related genes in Norway spruce epitypes[END_REF][START_REF] Gömöry | Epigenetic memory effects in forest trees: a victory of "Michurinian biology[END_REF]Yakovlev & Fossdal, 2017;Amaral et al., 2020) ; So far, most of the studies conducted in trees focusing on DNA methylation and gene expression have used a correlative approach. For example, extensive gene-body methylation is found in open chromatin, is linked to structural gene characteristics, and correlates with tissue-specific gene expression or stress [START_REF] Vining | Dynamic DNA cytosine methylation in the Populus trichocarpa genome: tissue-level variation and relationship to gene expression[END_REF][START_REF] Bräutigam | Epigenetic regulation of adaptive responses of forest tree species to the environment[END_REF][START_REF] Lafon-Placette | Methylome of DNase I sensitive chromatin in Populus trichocarpa shoot apical meristematic cells: a simplified approach revealing characteristics of gene-body DNA methylation in open chromatin state[END_REF], 2018;[START_REF] Liang | Single-base-resolution methylomes of Populus trichocarpa reveal the association between DNA methylation and drought stress[END_REF]. Here, we employed a reverse genetic approach using RNAi-ddm1 poplar lines to investigate the functional impact of variations in DNA methylation under water deficit conditions. We combined a fine-scale ecophysiological characterization of water deficit responses and growth dynamics with hormone profiling and integrative (epi)genomics in the shoot apical meristem of the hypomethylated RNAi-ddm1 lines.

MATERIAL AND METHODS

Plant material, experimental design and control of water deficit

Experiments were conducted on two PtDDM1 RNAi lines (ddm1 -15 and ddm1 -23) and a wild type (WT) line of Populus tremula x Populus alba (clone INRA 717-1B4). These two RNAi-ddm1 lines were chosen among those previously described by [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF] as they consistently displayed lower levels of PtDDM1 residual expression (38.0% and 37.5% for ddm1 -15 and ddm1 -23, respectively) and a decrease of cytosine methylation levels (decrease of 17.0 and 16.7%, respectively) compared to WT. These characteristics were confirmed in the present study. The experiment was conducted in a controlled glasshouse on 4-l potted saplings (see Supporting Information Methods S1 for detailed growth conditions). In total, 81 plants were randomly distributed into nine blocks and assigned to either a wellwatered control treatment (WW, one individual of each line per block) or a water deficit treatment followed by rewatering (WD-RW, two individuals of each line per block) (Fig. 1).

Water deficit was initiated at t0 on 3-month-old plants and lasted for 3 wk until t1. Plants from the WW condition were kept watered at close to field capacity, while plants from the WD-RW condition were watered to a target value of 40% of relative extractable water (REW, see Methods S1 for detailed information on the control of water deficit). At t1, three blocks were destructively harvested while the six blocks remaining were rewatered and maintained at field capacity before being sampled 1 wk later (t2). As the focus of this study was on post-stress epigenomic events, the blocks sampled at t1 were not considered in this study and the measurements reported hereafter were systematically performed on the six remaining blocks (n = 6 for WW, n = 12 for WD-RW) except where another subset is specified.

The intensity of water deficit was evaluated at t1 by measuring predawn leaf water potential (Ψpd, MPa) before rewatering.

Measurements were performed on a subset of five randomly selected blocks using a pressure chamber (PMS instruments, Albany, OR, USA; n = 5 for WW, n = 5 for WD-RW). Minimum leaf water potential (Ψmin) was estimated for the same plants at midday on the day preceding rewatering.

Physiological and phenotypic characterization

Assessment of growth and leaf phenotypes

Stem height was measured every 2 d using a telescopic ruler, while stem diameter was measured every 4 d using a digital caliper. We also repeatedly measured the number of leaves showing necrotic spots (mottled leaves, see [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF] during the whole duration of the experiment and counted the number of leaves showing a 'folded' morphology. These measurements were performed on all plants (n = 6 for WW, n = 12 for WD-RW).

Leaf traits

Leaf gas exchange was assessed every day during the experiment (n = 5 per line for WW and WD-RW). Bulk leaf carbon isotope composition (∂13C) was measured at t2 from a mature leaf on all plants (n = 6 for WW, n = 12 for WD-RW) while stomatal density was assessed on a subset of three blocks (n = 3 for WW and WD-RW). See Methods S1 for detailed procedures for stomatal conductance, carbon isotope composition and stomatal counts.

Xylem vulnerability to drought-induced cavitation

Xylem vulnerability to drought-induced cavitation was assessed at t2 on stems of all plants under the well-watered condition only (n = 6) (INRAE Phenobois Platform, Clermont-Ferrand, France). We used the Cavitron technique, which is well suited to poplars [START_REF] Cochard | Evaluation of a new centrifuge technique for rapid generation of xylem vulnerability curves[END_REF][START_REF] Fichot | Vulnerability to drought-induced cavitation in poplars: synthesis and future opportunities[END_REF]. The xylem tension causing a 50% loss of hydraulic conductance (P50, MPa) was used to compare vulnerability. See Methods S1.

Phytohormone quantification

Phytohormone assays for abscisic acid (ABA), free auxin, salicylic acid (SA), jasmonic acid (JA) and cytokinins were performed on the individual SAMs collected at t1 (n = 3 for each line and condition) using liquid chromatography-mass spectrometry (LC-MS) according to a previously published procedure (OVCM platform, IJPB, INRAE Versailles, France; [START_REF] Li-Marchetti | Genotypic differences in architectural and physiological responses to water restriction in rose bush[END_REF][START_REF] Trapet | The Pseudomonas fluorescens siderophore pyoverdine weakens Arabidopsis thaliana defense in favor of growth in iron-deficient conditions[END_REF]. For more details, see Methods S1.

DNA extraction and determination of global DNA methylation levels by high-performance liquid chromatography (HPLC)

Genomic DNA was extracted from individual SAMs (n = 3 for each line for each water condition at t2) using a cetyl trimethylammonium bromide (CTAB) protocol [START_REF] Doyle | A rapid DNA isolation procedure for small quantities of fresh leaf tissue[END_REF], and was stored at -80°C. Quantity and quality were approximated using a NanoDrop spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). For the HPLC determination of global DNA methylation, we followed the method described by [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF].

Methylome analyses using whole genome bisulfite sequencing (WGBS)

An equimolar pool of 2 µg DNA at c. 100 ng µl -1 was made for each line in each treatment from four individual SAMs (n = 4; at t2). Whole-genome bisulfite sequencing was performed at the Centre National de Genotypage (CNRGH; Evry, France) in accordance with the procedure described by [START_REF] Daviaud | Whole-genome bisulfite sequencing using the Ovation ® ultralow methyl-seq protocol[END_REF], adapted from the library preparation kit manufacturer's online instructions (http://www.nugen.com/products/ovationultralow-methyl-seq-library-systems) (see Methods S1). The sequencing was performed in paired-end mode (2 x 150bp) on an Illumina HiSeq4000 platform. Raw data were stored as FASTQ files with a minimal theoretical coverage of 30x.

The bioinformatic pipeline for methylome analysis was adapted from the ENCODE pipeline (https://www.encodeprojec t.org/data-standards/wgbs) and installed on the Galaxy instance of the Interactions H^otes Pathogenes Environnements (IHPE) platform (http://galaxy.univ-perp.fr/, Perpignan, France) using the reference genome Populus tremula x Populus alba (http:// aspendb.uga.edu/index.php/databases/spta-717-genome). For more details, see Methods S1.

Transcriptomic analyses

We performed RNAseq on samples obtained in WD-RW conditions to compare one RNAi-ddm1 line (ddm1-23) to the WT. The line ddm1-23 was chosen as the most representative of the two lines as it showed a smaller decrease in methylation compared to ddm1-15, and most of its DMRs were common to ddm1-15 (see the Results section). Total RNA was extracted from SAMs from three biological replicates per line (n = 3; at t2) using a modified version of the protocol described by [START_REF] Chang | A simple and efficient method for isolating RNA from pine trees[END_REF]. For more details, see Methods S1.

Mobilome-seq and copy number variation of transposable elements

We sequenced extrachromosomal circular DNAs (eccDNAs) in order to identify active TEs, as described by [START_REF] Lanciano | Sequencing the extrachromosomal circular mobilome reveals retrotransposon activity in plants[END_REF]. We used c. 6 µg of genomic DNA (the same pools used for WGBS) obtained for each line in each condition from individual SAMs (n = 4; at t2) to prepare mobilome-seq libraries. eccDNAs were isolated and amplified and libraries were prepared and sequenced following [START_REF] Lanciano | Sequencing the extrachromosomal circular mobilome reveals retrotransposon activity in plants[END_REF]. Bioinformatic analyses were carried out on the Populus tremula x Populus alba genome (SPta717 v1.1) using the pipelines described by [START_REF] Lanciano | Sequencing the extrachromosomal circular mobilome reveals retrotransposon activity in plants[END_REF]. DNA copy number variation of TEs was assessed for all studied lines in both conditions by quantitative polymerase chain reaction (qPCR) in triplicate. For more details, see Methods S1.

Statistical analyses

Statistical analyses were performed using the R statistical software under the R STUDIO integrated development environment (R Development Core Team, 2015; http://www.rstudio.com/). Means are represented with their standard errors (SE). When measurements were available for more than one individual replicate per block under the WD-RW condition, pseudoreplicates were averaged to yield a single value per block. Differences between lines and conditions for phenotypic traits were evaluated by analysis of variance (ANOVA) on individual values adjusted for block effects. Tukey's posthoc test was used to identify differences between groups when ANOVAs indicated significant effects. Statistical tests were performed and P-values were calculated according to the methods described by [START_REF] Wasserstein | The ASA statement on p-Values: context, process, and purpose[END_REF].

RESULTS

Phenotypic and physiological differences among lines under well-watered conditions

We performed a drought experiment on WT and RNAi-ddm1 poplar lines (Fig. 1). Plants in the control condition remained watered close to field capacity during the whole experiment. Relative extractable water (REW) never dropped below 70% (Fig. 2a) and predawn leaf water potential (Ψpd) values remained above -0.5 MPa (Fig. 2b). There was no significant difference in either REW or Ψpd among lines (Fig. 2a,b). The WT and RNAi-ddm1 lines all showed linear growth during the experiment (Fig. S1a) and there was no significant difference for height growth rates (1.27 0.03 cm d -1 , P = 0.797) or diameter growth rates (0.09 0.02 mm d -1 , P = 0.091) (Fig. 3a,b). Differences among lines were, however, visible for total leaf area, with RNAi-ddm1 lines exhibiting, on average, 28% lower values compared to the WT (P = 0.021, Fig. S2a), which was mainly explained by the smaller leaves in the middle canopy (Fig. S2b).

Significant differences were observed for xylem vulnerability to cavitation (P < 0.001, Fig. 3c). The WT was c. 10% more vulnerable (P50 =2.16 0.05 MPa) compared to the RNA-ddm1 mean; ddm1-23 was the most resistant (P50 =2.45 0.04 MPa), and ddm1-15 was intermediate (P50 =2.28 0.04 MPa).

By contrast, there were no significant differences between lines for leaf traits (Fig. S3) and xylem structural or biochemical traits (Table S1).

The proportion of leaves showing necrotic spots reached 40% at the end of the experiment for ddm1-23 and > 60% for ddm-15, while it remained close to zero for the WT (Fig. 4). Symptom occurrence was not linear but tended to increase at a specific physiological stage (Fig. 4), mainly on mature leaves and not in the uppermost third of the plant. The RNAi-ddm1 lines (mostly ddm1-23) also exhibited leaves that tended to fold around the midvein (Fig. 4).

In summary, under well-watered conditions, RNAi-ddm1 lines showed growth and leaf physiology similar to WT. However, RNAi-ddm1 lines displayed necrotic spots on mature leaves and higher xylem resistance to cavitation (Table 1).

Differences in drought response

Soil water content of drought stressed plants started to exhibit significantly lower values than the control 4 d after the initiation of the water deficit. Values of REW then fluctuated between 20 and 40% until t1 (Fig. 2a); rewatering at t1 increased REW back to control values (Fig. 2a). Predawn leaf water potential at t1 was significantly lower than in well-watered plants (P < 0.001 for each line) and reached c. -0.8 MPa with no significant difference among lines (Fig. 2b). Height and diameter growth rates during the 3-wk water deficit were significantly reduced, by 25% and 39%, in the WT trees (Fig. 3, P = 0.037 and P = 0.026). By contrast, height and diameter growth rates of RNAi-ddm1 lines were not significantly affected by water deficit (8% and 13% reduction in height growth rates with P = 0.204 and P = 0.244 for RNAiddm1-15 and RNAi-ddm1-23, respectively; 4% and 8% reduction in diameter growth rates with P = 0.828 and P = 0.516 for ddm1-15 and ddm1-23, respectively). Rewatering brought growth back to the levels of the controls (Fig. S1).

In response to water deficit, stomatal conductance started to decrease c. 10 d after drought initiation, that is, once REW had dropped below 40% (Figs 2a,S3). The WT and RNAi-ddm1 lines showed relatively comparable dynamics and reached almost an 80% decrease relative to controls (Fig. S3). Net CO2 assimilation rates were less impacted, in agreement with the moderate intensity of the water deficit (Fig. S3). The WT and RNAi-ddm1 lines all showed leaf traits that were comparable to those of the plants under the well-watered condition, although the WT did show a significant effect of water deficit for leaf ∂ 13 C and stomatal density (Fig. S3). Xylem traits were seldom affected by water deficit and were not statistically different among the WT and RNAi-ddm1 lines (Table S1). Water deficit also had no significant effect on the occurrence of leaf symptoms (Fig. 4).

In summary, RNAi-ddm1 lines exhibited a drought response that was mostly similar to the WT in terms of leaf physiology and xylem structure/biochemical composition. However, height and diameter growth were not significantly decreased by the moderate water deficit, in contrast to the WT, suggesting enhanced stress tolerance (Table 1).

Phytohormone concentrations in shoot apices

There were no significant differences among lines in phytohormone concentrations under wellwatered conditions. Salicylic acid content, however, was on average almost 2.5 times higher in RNAi-ddm1 lines (Fig. 5). Under water deficit-rewatering conditions, significant differences among lines were observed for SA (Fig. 5); SA was still almost two times higher in RNAi-ddm1 lines, while zeatine riboside and zeatine-O-glucoside riboside levels were on average one third lower in RNAi-ddm1 lines (Fig. 5). Although the ABA concentrations were on average 20% lower for the RNAi-ddm1 lines compared to WT, the results did not reach statistical significance (P = 0.267). Free auxin concentrations were similar among all lines (Fig. 5). The WT exhibited the lowest values among all lines for SA, and the SA concentration did not change significantly as a function of the stress conditions (Fig. 5). Concentrations of zeatine riboside and zeatine-O-glucoside riboside were higher in the WT because of a treatmentinduced increase (Fig. 5). Concentrations of isopentenyladenosine showed a more complex pattern, with RNAiddm1-15 and RNAi-ddm1-23 exhibiting the lowest and the highest values, respectively (Fig. 5).

In summary, RNAi-ddm1 lines differed from the WT, mostly under water deficit for SA (higher) and cytokinin (lower) concentrations (Table 1; Fig. 5) suggesting a physiological change in the hormonal balance ;

Methylome analysis and identification of constitutive and stress-specific RNAi-ddm1 differentially methylated regions (DMRs) and differentially methylated genes (DMGs) in the shoot apical meristem

Global DNA methylation values in the SAM, obtained via HPLC, ranged from 17.5% to 21.3% depending on the line and condition (Fig. S4a), confirming a reduction of whole genome methylation of up to 17.8%, in agreement with [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF]. There was no significant line x condition interaction. Values were significantly lower in RNAi-ddm1 lines compared to the WT under water deficit/rewatering (WD-RW) only, although there was no significant general effect of water deficit (Fig. S4a). Whole genome bisulfite sequencing (WGBS) analysis was performed on SAMs (Fig. S5), and cytosine methylation percentages for the three contexts ranged from 18.6% to 19.6% in the CpG context, 4.4% to 6.0% in the CHG context and 1.6% to 2.0% in the CHH context, with RNAi-ddm1-15 systematically displaying the lowest values, with a 25.0% decrease for the CHG context (Table S2; Fig. S5d) ;

We considered different types of differentially methylated regions (DMRs) between lines and conditions (Figs 6, S4b, S6a; Tables 1,S3). In order to focus on DMRs specifically related to PtDDM1 down-regulation, DMRs common to both ddm1-15 and ddm1-23 lines vs WT were identified and used for further analysis (Table 1, Fig. 6). In total, 5374 common DMRs were identified under well-watered conditions (hereafter named 'constitutive RNAi-ddm1 ' DMRs; Table 1; Figs 6a,S6a). Under the water deficit/rewatering condition, 5172 DMRs were similarly identified, among which 1736 were common to RNAi-ddm1 constitutive DMRs, while 3436 were specific to the WD-RW condition (hereafter named 'stress-specific RNAi-ddm1 ' DMRs) (Table 1, Figs 6a, S6a). Altogether, most of the DMRs were hypomethylated and context-dependent, with higher values found in the CHG context, followed by the CpG and CHH contexts (Fig. 6a). However, in the CpG context, these DMRs presented both significant hypo-and hypermethylated patterns (Fig. 6a). In addition, 2592 DMRs that were common to the WT and RNAi-ddm1 lines were identified in response to water deficit/rewatering (Table 1, Fig. 6b). However, as this type of DMR has already been reported for the WT [START_REF] Lafon-Placette | Changes in the epigenome and transcriptome of the poplar shoot apical meristem in response to water availability affect preferentially hormone pathways[END_REF], we further focused our attention on constitutive and stress-specific RNAi-ddm1 DMRs (Tables 1,S3; Figs 6,S7).

Regardless of the treatment, constitutive and stress-specific RNAi-ddm1 DMRs were found in intergenic regions (73% and 71%, for WW and WD-RW conditions, respectively), genes (19% and 21%), promoters ( 2 kb from the TSS; 7% and 8%) and TEs (1%, 47 TEs in WW and 48 TEs in WD-RW) (Fig. S7a). Under control conditions, 879 genes were strictly included within the RNAi-ddm1 constitutive DMRs (hereafter called DMGs for 'differentially methylated genes'), while 910 DMGs were found in stress-specific RNAi-ddm1 DMRs (Tables 1,S3). Approximately one-third of DMGs (390 genes) were common between conditions and represented constitutive and stable RNAi-ddm1 -DMGs, while 520 new DMGs were observed (stress-specific RNAi-ddm1 DMGs) (Tables 1,S3). These numbers increased considerably (up to > 13 000 out of 41 335 genes) when enlarging the windows for DMR identification from 2 kb to 25 kb (Fig. S7b). Under both conditions, a similar number of hypo-and hypermethylated DMGs was found in the CpG context, while in the CHG and CHH contexts, DMGs were mostly hypomethylated (Fig. 6c). In the CHH context, DMGs were slightly methylated (25% to 50% difference) compared to the CpG and CHG contexts (Fig. 6c). Gene ontology (GO) annotation of DMGs (879 in WW or 910 in WD-RW) revealed significant enrichment in similar biological functions such as development (including shoot system morphogenesis), regulation of gene expression (epigenetics, ATPdependent chromatin remodeling, histone modifications), response to hormones, immune response and abiotic stress (Fig. 6d,e). Under the WD-RW condition, GO terms for the lost DMGs (489, Fig. S7c) were related to development (meristem development), hormones (regulation of hormone levels, response to auxin) and gene silencing. Gene ontology terms for stable DMGs (390, Fig. S7d) were related to development, jasmonic acid, epigenetics, immune response and metabolic processes, while the new DMGs (520, Fig. S7e) were associated with development, and defense/immune/abiotic responses, suggesting that stable and new DMRs preferentially target stress related genes.

In summary, the analysis of the SAM methylome highlighted that DDM1 knock-down mostly led to hypomethylated CHG DMRs in RNAi-ddm1 lines, irrespective of the treatment. However, the constitutive ddm1 -DMRs were largely (approximately two-thirds, Table 1) affected in water deficit conditions (WDRW), suggesting that alteration of DDM1 machinery in the SAM has the potential to affect development and stress responsive genes, including those related to hormone pathways under stress conditions (Table 1; Fig. S6b).

Transcriptome analysis in the shoot apical meristem

To analyze the impact of a water deficit and rewatering cycle on the SAM, we performed an RNAseq experiment to investigate the differences between RNAi-ddm1 (ddm1-23) and WT SAMs under the WD-RW condition. The identification of differentially expressed genes (DEGs) revealed limited but clear differences (Fig. 7). Out of 32 048 analyzed genes, only 136 genes (Fig. 7; Table S3) were significantly differentially expressed (76 upregulated and 60 down-regulated genes in RNAi-ddm1 as compared to the WT, P < 0.05). Gene ontology annotation revealed significant enrichment in functions such as defense response, immune and wounding responses, response to hormones and signaling, leaf senescence and programmed cell death (Fig. 7a).

The 136 DEGs (RNAi-ddm1 vs WT in WD-RW condition) were grouped into main classes (Fig. 7b). Genes related to the immune response were systematically up-regulated in RNAiddm1 (RBOHD, CYP94B1, RLP1, RLP56, RPM1, PLDGAMMA1, PDF1; Fig. 7b). Most genes related to transcription factors (15/17) were also up-regulated (WRKY, MYB106, ERF, SZF2, PDF2, SVP/AGL22), with only two genes downregulated (MYB48 and DTA2). Defense and cell wall related genes were both upregulated (18, including CHITIV, KTI1, and PR4, involved in plant pathogen-interaction) and downregulated (13). Phytohormone pathways were also overrepresented in distinct classes, with 13 DEGs (8 up-regulated and 5 down-regulated) directly involved in defense responsive hormone biosynthetic pathways such as salicylic acid (SAMTs), jasmonic acid (OPR2, CYP94B1), ethylene (ERF1, ERF12), auxin responsive genes (SAUR29, GH3.1, IBR3, BG1, ABCG36), gibberellic acid synthesis (GA3OX1) and cytokinins (AHP1) (Fig. 7b).

Although only seven DEGs overlapped strictly with the DMR genomic locations (previously identified DMGs) (Fig. 7b), 53 were located within the close vicinity of a DMR ( 10 kb) and 98 within 25 kb (Fig. S8a). Methylation in the three contexts correlated negatively with expression values when considering at least a 10 kb window for DMRs (Spearman's rho =-0.32 at P = 0.0004) (Fig. S8b).

In summary, the analysis of the SAM stress-transcriptome suggests that, under the stress conditions tested, DDM1 plays a role in repressing genes involved in stress and defense response, including hormonal pathways (Table 1; Fig. S6b).

Mobilome analysis and transposable element genomic integration in the shoot apical meristem

The mobilome-seq approach, which consists of the sequencing of intermediate extrachromosomal circular forms (eccDNA) of TEs [START_REF] Lanciano | Sequencing the extrachromosomal circular mobilome reveals retrotransposon activity in plants[END_REF], allowed the identification of both active DNA transposons and retrotransposons belonging to 44 to 169 TE families, depending on lines and conditions (RNAi-ddm1-23 in Fig. 8a, RNAi-ddm1-15 in Fig. S9a). This number of identified active TE families was always higher under water deficit conditions, regardless of the line. Most of the eccDNAs identified belonged to the annotated Gypsy, Copia, ENSPM, L1, Ogre, POPGY and SAT families of TEs and repeats. We used depth of coverage (DOC), ranging from 4 x to 51 000 x, to classify TEs into four categories. Transposable elements identified in RNAiddm1 and WT lines belonged to the four groups under either condition (Figs 8a, S9a; Table S3), with split-read (SR) coverage ranging from 3 x to 4600 x suggesting the presence of reads spanning the junction of eccDNAs.

Constitutive (WW) and stress-induced (WD-RW) specific TEs were identified (414 TE families in all lines and conditions; Fig. 8a; Table S3). The two most active TEs (Gypsy23 and Gypsy27) were detected in both WT and RNAi-ddm1 lines, but Gypsy23 was specifically activated under stress conditions (i.e. the WD-RW condition) (Figs 8a, S9a). Active TEs only detected in RNAi-ddm1 lines were found under WW (28 TEs) and WDRW (89 TEs) conditions. Approximately 21% of the active TEs detected by mobilome-seq strictly co-localized with RNAi-ddm1 DMRs. This percentage reached > 50% when considering the presence of a DMR at 25 kb (Fig. S9b). These active TE families were mainly hypomethylated (c. 92% of the TE families) in RNAi-ddm1 lines (Fig. 8b), and the most active TEs (TE+++) co-localized with DMRs in the CHG context (data not shown). Under stress conditions, active TEs were also hypomethylated in both CpG and CHG contexts but hypermethylated in the CHH context.

The number of genes identified in the vicinity of TEs varied from 45 (TEs inside genes) to 1788 (when considering TEs within 25 kb of genes) (Fig. S9b; Table S3). Gene ontology annotation of the genes co-localizing with TEs ( 10 kb of genes) revealed an enrichment for function in hormone response, immune/defense/abiotic responses and development (Fig. S9c). However, only seven of these genes were previously detected as DEGs (Fig. 7b) when considering the region of 25 kb.

In order to test for new genomic integrations of the detected active TEs, we assessed copy number variation for three highly active TEs (DNA-3-3_1, Gypsy23 and SAT-1) localized in or near DMRs by qPCR analysis (Figs 8c,S9d). For DNA-3-3_1, there was no significant variation in the copy number, regardless of the line and condition. For the other TEs, an increase in copy number was observed in RNAi-ddm1 lines under water deficit only -15 copies of Gypsy23 in RNAi-ddm1-23 (Fig. 8c) and 18 copies of SAT-1 in RNAi-ddm1-15 (Fig. S9d). In the RNAi-ddm1 background, Gypsy23 is located inside a CHG hypomethylated DMR, while SAT-1 is found near (2 kb) a CpG and CHG hypomethylated DMR.

In summary, hundreds of active TEs were detected in the SAM, and several of them were stressinduced. DDM1 knockdown had only a limited impact on the active TE population. However, a genomic copy number increase for two TE families could only be detected in RNAi-ddm1 lines, showing a role for DDM1 in protecting meristem genome integrity under stress conditions (Figs 8c,S6b).

DISCUSSION

Relevance of RNAi-ddm1 poplar lines to the investigation of the stress response in trees

Decreased DNA Methylation I (DDM1) is a plant gene encoding a nucleosome remodeler which facilitates DNA methylation [START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Zhang | The chromatin remodeler DDM1 promotes hybrid vigor by regulating salicylic acid metabolism[END_REF][START_REF] Osakabe | The chromatin remodeler DDM1 prevents transposon mobility through deposition of histone variant H2A[END_REF]. While studies on ddm1 mutants have revealed a major role in silencing TEs and a minor role for DDM1 on silencing few heterochromatic genes depending on annuals plants (Arabidopsis, tomato, maize, rice), its role in trees and the effect of the environment remain largely unknown [START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Tan | Analysis of chromatin regulators reveals specific features of rice DNA methylation pathways[END_REF][START_REF] Zhang | The chromatin remodeler DDM1 promotes hybrid vigor by regulating salicylic acid metabolism[END_REF][START_REF] Corem | Redistribution of CHH methylation and small interfering RNAs across the genome of tomato ddm1 mutants[END_REF][START_REF] Long | Decrease in DNA methylation 1 (DDM1) is required for the formation of mCHH islands in maize[END_REF]. Here, we investigated the role of DDM1 in a perennial tree (i.e. poplar) under drought conditions in the shoot apical meristem, the center of morphogenesis and differentiation of reproductive cells. We previously characterized stress-induced DMRs in the SAM of various poplars, including the WT P. tremula x P. alba 717-1B4, revealing that epigenome and transcriptome remodeling following post-drought recovery preferentially affects genes in hormonal pathways [START_REF] Lafon-Placette | Changes in the epigenome and transcriptome of the poplar shoot apical meristem in response to water availability affect preferentially hormone pathways[END_REF]. DNA methylation and other epigenetic marks are thought to interact with hormone signaling to control developmental plasticity [START_REF] Ojolo | Regulation of plant growth and development: A review from a chromatin remodeling perspective[END_REF], especially in meristems [START_REF] Maury | Phytohormone and chromatin crosstalk: The missing link for developmental plasticity?[END_REF]Amaral et al., 2020) but, so far, functional evidence in meristems has been lacking. Thus, we used a reverse genetic approach and investigated the drought response of RNAi-ddm1 poplar lines that have already been stabilized in vitro for several years [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF].

The global hypomethylation observed in the two poplar RNAi-ddm1 lines indicated that PtDDM1 knock-down [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF] was effective in the shoot apical meristem. Wholegenome bisulfite sequencing further confirmed this hypomethylation at the genomic level in the three contexts (CpG, CHG and CHH). However, methylation levels in CHG were drastically reduced, suggesting that poplar DDM1 preferentially targeted methylation in this context. This agrees with reports in rice and maize [START_REF] Li | Inheritance patterns and stability of DNA methylation variation in maize near-isogenic lines[END_REF][START_REF] Tan | Analysis of chromatin regulators reveals specific features of rice DNA methylation pathways[END_REF][START_REF] Long | Decrease in DNA methylation 1 (DDM1) is required for the formation of mCHH islands in maize[END_REF] but differs from those in Arabidopsis and tomato [START_REF] Vongs | Arabidopsis thaliana DNA methylation mutants[END_REF][START_REF] Kakutani | Characterization of an Arabidopsis thaliana DNA hypomethylation mutant[END_REF][START_REF] Kakutani | Genetic characterization of late-flowering traits induced by DNA hypomethylation mutation in Arabidopsis thaliana[END_REF][START_REF] Lippman | Role of transposable elements in heterochromatin and epigenetic control[END_REF][START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Corem | Redistribution of CHH methylation and small interfering RNAs across the genome of tomato ddm1 mutants[END_REF]. In addition, DDM1-dependent methylation in the SAM of poplar was shown to affect active TEs but also many genes, and to be remodeled by the stress conditions. This confirms that the effects of DDM1 on euchromatic and heterochromatic DNA methylation patterns are different depending on species [START_REF] Zemach | The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1containing heterochromatin[END_REF][START_REF] Tan | Analysis of chromatin regulators reveals specific features of rice DNA methylation pathways[END_REF][START_REF] Long | Decrease in DNA methylation 1 (DDM1) is required for the formation of mCHH islands in maize[END_REF] and environmental conditions.

The necrotic spots on RNAi-ddm1 leaves reported by [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF] were consistently observed in our experiment, mainly on mature leaves, and this has previously been associated with ddm1 mutation in Arabidopsis [START_REF] Kakutani | Characterization of an Arabidopsis thaliana DNA hypomethylation mutant[END_REF][START_REF] Questa | € DDM1 and ROS1 have a role in UV-B induced-and oxidative DNA damage in A. thaliana[END_REF][START_REF] Kooke | Epigenetic basis of morphological variation and phenotypic plasticity in Arabidopsis thaliana[END_REF] and hypomethylated drm1 drm2 cmt3 mutants [START_REF] Forgione | Hypomethylated drm1 drm2 cmt3 mutant phenotype of Arabidopsis thaliana is related to auxin pathway impairment[END_REF]. It has been suggested that this phenotype is associated with either the demethylation-induced hyperactivation of disease resistance genes or the demethylation-induced reactivation of retrotransposon and virus-like elements under stress conditions [START_REF] Zhu | Poplars with a PtDDM1-RNAi transgene have reduced DNA methylation and show aberrant post-dormancy morphology[END_REF]. In our case, the higher endogenous concentrations of SA observed in the SAM of RNAi-ddm1 lines would support the first hypothesis, since the accumulation of SA is known to be associated with DDM1 mutations and is related to the activation of hypersensitive response cell death or systemic acquired resistance [START_REF] Dong | NPR1, all things considered[END_REF][START_REF] Song | A key role for ALD1 in activation of local and systemic defenses in Arabidopsis[END_REF][START_REF] Liu | Amino acid homeostasis modulates salicylic acid-associated redox status and defense responses in Arabidopsis[END_REF][START_REF] Zhang | The chromatin remodeler DDM1 promotes hybrid vigor by regulating salicylic acid metabolism[END_REF][START_REF] Badmi | Induced and primed defence responses of Fragaria vesca to Botrytis cinerea infection[END_REF]. However, further research in leaves will be needed to confirm this hypothetical SA accumulation in mature leaves in relation to the appearance of necrotic spots during the time-course of the experiment.

Apart from the leaf phenotypic alterations, we did not observe any striking phenotypes for RNAi-ddm1 lines -growth and water relations under control conditions were mostly comparable to those of the WT. As gas exchanges were measured on young developing leaves without necrotic spots, we do not take into account their potential effect. However, the moderate water deficit revealed subtle differences in growth capability, which, combined with the intrinsic higher cavitation resistance, suggests that alterations to the DDM1-dependent DNA methylation in the two RNAi-ddm1 lines translated into increased tolerance to water-stress.

Hypomethylated RNAi-ddm1 poplar lines are more tolerant to water deficit

Tolerance to water deficit is a complex trait encompassing multiple physiological determinants that relate to diverse processes such as growth maintenance, survival, or recovery, depending on the context of drought intensity and duration [START_REF] Mcdowell | Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought?[END_REF][START_REF] Volaire | Embolism and mechanical resistances play a key role in dehydration tolerance of a perennial grass Dactylis glomerata L[END_REF]. The moderate water deficit we imposed avoided a rapid growth cessation and promoted steadystate acclimation. The time course of soil REW was similar between the RNAi-ddm1 and the WT lines during the whole experiment, indicating that all lines actually faced the same level of water deficit. However, while growth progressively slowed in the WT as REW dropped below 40%, as commonly observed in poplars [START_REF] Bogeat-Triboulot | Gradual soil water depletion results in reversible changes of gene expression, protein profiles, ecophysiology, and growth performance in Populus euphratica, a poplar growing in arid regions[END_REF], RNAi-ddm1 lines remained unaffected. This, combined with the fact that RNAiddm1 lines exhibited growth similar to that of the WT under control conditions, suggested increased tolerance to moderate water deficit in the RNAi-ddm1 lines. Furthermore, the RNAiddm1 lines also exhibited higher xylem resistance to droughtinduced cavitation, suggesting improved stress resilience under severe water deficit [START_REF] Brodribb | Hydraulic failure defines the recovery and point of death in waterstressed conifers[END_REF][START_REF] Barigah | Water stress-induced xylem hydraulic failure is a causal factor of tree mortality in beech and poplar[END_REF]. How modifications to the DDM1 machinery can affect xylem resistance to cavitation remains unknown at this stage. Interestingly, xylem morphometric features, xylem density and xylem biochemical composition were not significantly different from the WT. However, given the mechanistic understanding of drought-induced cavitation in angiosperms, it is likely that the increased resistance observed in the RNAi-ddm1 lines was primarily linked to modifications in the ultrastructure of vesselvessel bordered pits [START_REF] Plavcova | Heterogeneous distribution of pectin epitopes and calcium in different pit types of four angiosperm species[END_REF][START_REF] Fichot | Vulnerability to drought-induced cavitation in poplars: synthesis and future opportunities[END_REF]. Whether the slight gain in intrinsic cavitation resistance (i.e. a few tenths of a MPa) does promote increased survival under severe water deficit, and whether epigenetics might be exploited as such for increasing drought tolerance, remains to be purposely tested.

DDM1-dependent DNA methylation and hormone signaling interact in the shoot apical meristem to orchestrate stress tolerance

The improved stress tolerance in the two RNAi-ddm1 lines was not associated with sharp differences in water relations or more general phenotypes. Another possibility could be physiological differences related to the phytohormone balance under water deficit. Epigenetics has been linked to phytohormone pathways [START_REF] Latzel | Epigenetic variation in plant responses to defence hormones[END_REF][START_REF] Yamamuro | Epigenetic modifications and plant hormone action[END_REF][START_REF] Ojolo | Regulation of plant growth and development: A review from a chromatin remodeling perspective[END_REF][START_REF] Raju | An epigenetic breeding system in soybean for increased yield and stability[END_REF][START_REF] Kooke | Epigenetic mapping of the Arabidopsis metabolome reveals mediators of the epigenotype-phenotype map[END_REF], which could play a major role in meristems for developmental plasticity (Maury et al., 2019;Amaral et al., 2020). Interestingly, although poplar RNAi-ddm1 lines displayed hormone profiles in the shoot apex comparable to those of the WT under control conditions, differences were visible under the water deficit conditions, especially for cytokinins (CKs) and salicylic acid (SA). RNAi-ddm1 lines also displayed decreased expression of histidine-containing phosphotransfer protein 1 (AHP1) which plays a role in propagating cytokinin signal transduction. Cytokinins are known to be negative regulators of stress signaling, and CK-deficient plants with reduced levels of various CKs are generally more tolerant to drought and salt stress [START_REF] Havlova | The role of cytokinins in responses to water deficit in tobacco plants over-expressing transzeatin O-glucosyltransferase gene under 35S or SAG12 promoters[END_REF][START_REF] Nishiyama | Analysis of cytokinin mutants and regulation of cytokinin metabolic genes reveals important regulatory roles of cytokinins in drought, salt and abscisic acid responses, and abscisic acid biosynthesis[END_REF][START_REF] Ha | Cytokinins: metabolism and function in plant adaptation to environmental stresses[END_REF]. Higher endogenous levels of SA, as observed for the RNAi-ddm1 lines compared to WT, have also been shown to promote tolerance to stresses including drought [START_REF] Munne-Bosch | ~ Photo-and antioxidative protection, and a role for salicylic acid during drought and recovery in field-grown Phillyrea angustifolia plants[END_REF]Bandurska & Stroi ~ nski, 2005;[START_REF] Azooz | Evaluation of heat shock and salicylic acid treatments as inducers of drought stress tolerance in Hassawi wheat[END_REF][START_REF] Pandey | Salicylic acid and drought stress response: Biochemical to molecular crosstalk[END_REF][START_REF] Sedaghat | Physiological and antioxidant responses of winter wheat cultivars to strigolactone and salicylic acid in drought[END_REF]. Accordingly, SAMT1, a salicylic acid methyltransferase gene, was up-regulated in stressed RNAi-ddm1 lines compared to the WT [START_REF] Mofatto | Identification of candidate genes for drought tolerance in coffee by highthroughput sequencing in the shoot apex of different Coffea arabica cultivars[END_REF].

Although PtDDM1 knock-down affected the methylation of c. 900 genes common to both RNAi-ddm1 lines, only a limited number of DEGs was found under water deficit, with seven DEGs strictly overlapping with DMRs (53 for genes at 10 kb of DMRs). While no clear correlation between DNA methylation and expression changes may exist at the genomic level, the transcriptional activity of a subset of genes still might be regulated, both directly and indirectly, by DNA methylation in response to abiotic stress [START_REF] Karan | Salt stress induced variation in DNA methylation pattern and its influence on gene expression in contrasting rice genotypes[END_REF][START_REF] Garg | Divergent DNA methylation patterns associated with gene expression in rice cultivars with contrasting drought and salinity stress response[END_REF][START_REF] Chwialkowska | Water-deficiency conditions differently modulate the methylome of roots and leaves in barley (Hordeum vulgare L.)[END_REF][START_REF] Lafon-Placette | Changes in the epigenome and transcriptome of the poplar shoot apical meristem in response to water availability affect preferentially hormone pathways[END_REF]. Indeed, we found genes such as transcription factors and hormonerelated pathways that are likely to explain, at least in part, the improved performance of poplar RNAi-ddm1 lines under water deficit. Several transcription factors, such as SVP, MYB48, ERF1, acting in phytohormone pathways and involved in biotic and abiotic stresses were also upregulated in RNAi-ddm1 lines in comparison to WT under water deficit [START_REF] Sun | Activated expression of AtWRKY53 negatively regulates drought tolerance by mediating stomatal movement[END_REF][START_REF] Bechtold | Time-series transcriptomics reveals that AGAMOUS-LIKE22 affects primary metabolism and developmental processes in drought-stressed Arabidopsis[END_REF][START_REF] He | Drought-responsive WRKY transcription factor genes TaWRKY1 and TaWRKY33 from wheat confer drought and/or heat resistance in Arabidopsis[END_REF][START_REF] Wang | Overexpression of a maize MYB48 gene confers drought tolerance in transgenic Arabidopsis plants[END_REF][START_REF] Heyman | Emerging role of the plant ERF transcription factors in coordinating wound defense responses and repair[END_REF][START_REF] Wang | The flowering repressor SVP confers drought resistance in Arabidopsis by regulating abscisic acid catabolism[END_REF][START_REF] Guo | Meta-analysis of the effects of overexpression of WRKY transcription factors on plant responses to drought stress[END_REF]. Other DEGs, including genes involved in the leaf cuticle and waxes (MYB106, CER8, FLA12), could also partly explain the improved tolerance to moderate water deficit in RNAi-ddm1 lines by preventing uncontrolled water loss [START_REF] Chen | A functional cutin matrix is required for plant protection against water loss[END_REF][START_REF] Oshima | The MIXTA-like Transcription factor MYB16 is a major regulator of cuticle formation in vegetative organs[END_REF][START_REF] Von Wettstein-Knowles | Plant waxes[END_REF][START_REF] Von Wettstein-Knowles | Plant waxes[END_REF].

Altogether, these findings confirm that common changes in DDM1-dependent DNA methylation found in both RNAi-ddm1 lines, especially in the shoot apical meristem, can alter hormonal balance and pathways under stress conditions, possibly leading to improved physiological performance (Fig. S6b). This shows the complex connections between chromatin, hormones in meristems and plasticity [START_REF] Lafon-Placette | Changes in the epigenome and transcriptome of the poplar shoot apical meristem in response to water availability affect preferentially hormone pathways[END_REF][START_REF] Maury | Phytohormone and chromatin crosstalk: The missing link for developmental plasticity?[END_REF].

DDM1-dependent DNA methylation regulates transposable element reactivation and insertion in the shoot apical meristem under stress conditions

The repressive role of DNA methylation and DDM1 on TE proliferation is well-established in plants [START_REF] Miura | Mobilization of transposons by a mutation abolishing full DNA methylation in Arabidopsis[END_REF][START_REF] Johannes | Assessing the impact of transgenerational epigenetic variation on complex traits[END_REF][START_REF] Mirouze | Selective epigenetic control of retrotransposition in Arabidopsis[END_REF][START_REF] Reinders | Compromised stability of DNA methylation and transposon immobilization in mosaic Arabidopsis epigenomes[END_REF][START_REF] Tsukahara | Bursts of retrotransposition reproduced in Arabidopsis[END_REF][START_REF] Corem | Redistribution of CHH methylation and small interfering RNAs across the genome of tomato ddm1 mutants[END_REF][START_REF] Quadrana | Transposition favors the generation of large effect mutations that may facilitate rapid adaption[END_REF]. We identified a large set of active TE families in the SAM, with up to 50% of them located within 25 kb of one RNAiddm1 common DMR and being mostly hypomethylated in the CpG and CHG contexts and hypermethylated in the CHH context under stress conditions. However, the activation of TEs was more affected by the stress conditions than the DDM1 knockdown. We could nonetheless detect increased copy numbers of some of the most active TEs (Gypsy-23 and SAT-1) only in RNAi-ddm1 lines under water deficit, suggesting that DDM1 plays a role in limiting TE reactivation and integration under stressful conditions in the SAM.

Our findings provide evidence that a repression of DDM1dependent DNA methylation can reactivate TEs, especially under stressful conditions, potentially producing genetic variations. [START_REF] Quadrana | Transposition favors the generation of large effect mutations that may facilitate rapid adaption[END_REF] proposed that TEs are potent and episodic (epi)mutagens that increase the potential for rapid adaptation. Epigenetic regulation may act as a hub through which nongenetically inherited environmentally induced variation in traits can become genetically encoded over generations [START_REF] Danchin | Epigenetically facilitated mutational assimilation: epigenetics as a hub within the inclusive evolutionary synthesis[END_REF]. Recently, [START_REF] Baduel | The epiallelic potential of transposable elements and its evolutionary significance in plants[END_REF] proposed that the adaptive contribution of TE-associated epivariations is mainly related to their ability to modulate TE mobilization in response to the environment. This definitely deserves further attention, as genes found close to our active TEs were involved in hormone and stress responses or development. Elucidating the evolutionary significance of both naturally occurring and environmentally induced variations in DNA methylation in the context of tree population dynamics will be of particular interest for long-living organisms such as trees in the age of rapid climate change.

AKNOWLEDGMENTS

MDS and ALLG received PhD grants from the Ministère de la Recherche et Enseignement Superieur. This work was supported by INRAE (grant PI EFPA-2014 to SM), the RTP3E CNRS grants for mobility (http://rtp-3e.wixsite.com/rt3e; ALLG, SM, CG and MM) and access to the IHPE platform (http://galaxy. univ-perp.fr/, Perpignan, France). The LBLGC also benefits from the support of the ANR EPITREE (ANR-17-CE32-0009-01) to SM. English editing was done by Infinity English (no. SIRET 82950710200012). The IJPB benefits from the support of Saclay Plant Sciences-SPS (ANR-17-EUR-0007). This work has benefited from the support of IJPB's Plant Observatory technological platforms. SL and MM were supported by the French National Agency for Research (ANR-13-JSV6-0002 'ExtraChrom') and the Laboratoire d'Excellence LABEX TULIP (ANR-10-LABX-41).

AUTHOR CONTRIBUTIONS

SM designed and coordinated the research. The plant experimental design was established by SM, SHS, RF, and FB. Ecophysiological measurements were performed by A-LLG, RF, AD, ILJ and HC; analysis was conducted by A-LLG and RF. Near infrared spectroscopy (NIRS) measurements and analysis were performed by A-LLG and VS. Phytohormone analysis was performed by SC. DNA and RNA extractions were done by AD, A-LLG and MDS. High-performance liquid chromatography analysis was performed by AD and SM. RNA-seq was conducted and analyzed by JC, VB, and LS-T with MDS. JT and CD performed the WGBS analysis. The WGBS data analysis was performed by SM, ALLG and MDS. Bioinformatics for WGBS was done with the help of CC and CG. Mobilome analysis was performed under the supervision of MM with SL and A-LLG.

Quantitative polymerase chain reaction analyses were performed by MCLD with AD and MDS. Data analysis was performed by SM, A-LLG and MDS. Statistical analyses were performed by RF, A-LLG and MDS. SM, RF, A-LLG and MDS conceived and wrote the first draft of the manuscript, MM helped revise the manuscript, and SHS edited and helped to direct final analyses and organization of the manuscript. All authors approved the final version of the manuscript. MDS and A-LLG contributed equally to this work.

DATA AVAILABILITY

The data that support the findings of this study are openly available: The WGBS data have been deposited in the Sequence Read Archive (SRA) at https://www.ncbi.nlm.nih.gov/sra/ PRJNA611484, reference no. PRJNA611484; the RNA-Seq data in the GEO (Gene Expression Omnibus) at http://www.ncbi. nlm.nih.gov/geo/query/acc.cgi?acc=GSE135313, reference no. GSE135313 and also in the CATdb database at http://tools.ips2. u-psud.fr/CATdb/, reference no. NGS2017-01-DDM1; and the Mobilome-Seq data in the GEO at https://www.ncbi. nlm.nih.gov/geo/query/acc.cgi?acc=GSE147934, reference no. GSE147934, as well as in the Supporting Information Table S3.

SUPPORTING INFORMATIONS

Additional Supporting Information may be found online in the Supporting Information section at the end of the article. Methods S1 Additional detailed procedures for ecophysiological, genomic and bioinformatic analyses.

Table S1 Xylem structural, functional and biochemical traits measured for the WT and the two RNAi-ddm1 poplar lines.

Table S2 Mean methylation levels in RNAi-ddm1 and WT lines in both conditions. Table S3 Lists of DMRs, DMGs, differentially expressed genes (DEGS), transposable elements (TEs) and genes near TEs. Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

Fig. 1

General overview of the drought experiment on poplars (Populus tremula x Populus alba). (a) Timeline of the experiment. Propagated in vitro plantlets from the wild-type (WT) and the two RNAiddm1 transgenic lines were acclimated in a heated glasshouse, transferred into 4 l pots and kept under control conditions until they were 3-months-old. At that time (t0), a water deficit was initiated for the plants assigned to the water deficit/rewatering treatment (WDRW), while control plants were kept wellwatered (WW). After 3 wk of water deficit (t1), plants of the WD-RW condition were rewatered to field capacity for 1 wk, after which the experiment ended (t2). The ecophysiological characterization of plant material was performed between t0 and t2. Sampling of shoot apical meristems (SAMs) for molecular analysis was performed at t2.

Fig. 4

Leaf phenotypes during the drought experiment. Plants were phenotyped for the occurrence of (a) necrotic spots (mottled phenotype) and (b) folded phenotype. For each panel the upper part shows a picture of a typical phenotype, and the lower graph shows a time course of leaf phenotypic alterations for the wild-type (WT) and the two RNAi-ddm1 (ddm1-15, ddm1-23) poplar lines (Populus tremula x Populus alba) under control (well-watered, WW) and stress (moderate water deficit followed by rewatering, WD-RW) conditions. Values are line means SE (n = 6 for WW, n = 12 for WD-RW). At the end of the experiment (t2), all lines differed significantly from each other for the proportion of necrotic spots (mottled phenotype), but water deficit had no significant effect; only ddm1-23 showed a significantly higher proportion of folded leaves, but water deficit still had no significant effect Phytohormone content in the shoot apical meristems. Measurements were performed at rewatering (t1) for the wildtype (WT) and the two RNAi-ddm1 (ddm1-15, ddm1-23) poplar lines (Populus tremula x Populus alba) for the six indicated phytohormones. White bars represent the control condition (WW) and white bars represent the stress condition (moderate water deficit followed by rewatering, WDRW). Values are genotypic means SE (n = 3). The effects of water deficit were evaluated within each line using a t-test and differences are only indicated when significant (*, P < 0.05; **, P < 0.01; ***, P < 0.001). Different letters indicate significant differences between lines within each condition (uppercase for WW, lowercase for WD-RW) following a Tukey's post-hoc test. The dashed lines indicate the detection threshold for each phytohormone.

Fig. 6

Variations in DNA methylation among RNAi-ddm1 and wild-type (WT) lines in shoot apical meristems 1 wk after rewatering (t2). (a) Common differentially methylated regions (DMRs) between the two RNAi-ddm1 lines (ddm1-15 and ddm1-23) (Populus tremula x Populus alba) vs the WT in all sequence contexts (CpG, CHG and CHH) under well-watered (WW) and stress (moderate water deficit followed by rewatering, WD-RW) conditions. Black bars represent hypomethylated DMRs and grey bars represent hypermethylated DMRs. (b) Identification of DMRs in WD-RW conditions compared to WW conditions for WT and RNAi-ddm1 lines. Black bars represent hypomethylated DMRs and grey bars represent hypermethylated DMRs. (c) Genic DNA methylation variation of the common DMRs in the RNAi-ddm1 lines vs the WT line under WW and WD-RW conditions for each methylation context. Only DMRs with at least a 25% difference were kept, except for CHH where a threshold of 10% was applied due to the low proportion of DMRs in that context. (d) Heatmap view of enriched clusters on constitutive (i.e. not stress induced) RNAi-ddm1 differentially methylated genes (DMGs) (in WW) (n = 879 annotations of homologous Arabidopsis genes). Each bar is a single cluster representative of TAIR10 corresponding to sPta717 v1.1 annotations. (e) Heatmap view of enriched clusters on stress-specific RNAi-ddm1 DMGs (in WD-RW) (n = 910 annotations of homologous Arabidopsis genes). Enriched GO clusters were generated using METASCAPE [START_REF] Zhou | Metascape provides a biologist-oriented resource for the analysis of systems-level datasets[END_REF]; see Supporting Information Methods S1).

Fig. 7

Gene expression variations in RNAi-ddm1-23 vs the wild-type (WT) line (Populus tremula x Populus alba) under the water deficit/rewatering condition (WD-RW) in shoot apical meristems collected 1 wk after rewatering (t2). (a) Geno ontology (GO) annotation of the differentially expressed genes (DEGs; genes with a false discovery rate (FDR)-adjusted P-value < 0.05; 136 DEGs identified) between RNAi-ddm1-23 and the WT. Gene ontology labels were retrieved from PopGenIE and a heatmap was produced with METASCAPE. (b) Annotation of DEGs with expression variation values (log2FoldChange) using GO labels retrieved from PopGenIE. Blue dots denote downregulated genes and red triangles upregulated genes. Asterisks (*) indicate hormone related genes found among DEGs; dollar symbols ($) represent DEGs overlapping with DMRs; the hash symbol (#) represents DEGs that overlap with TEs; and the numbers ( 1), ( 31), ( 8), ( 25), ( 19), (17), and (35) represent the numbers of DEGs found corresponding to cell death, defense & cell wall, immune response, metabolism, signalization, transcription factors and unknown processes, respectively. Log2FoldChange = log-ratio of normalized mean read counts in RNAi-ddm1-23 vs WT lines (n = 3 biological replicates for each line).

Table 1

Main characteristics of RNAi-ddm1 vs wild type (WT) lines (Populus tremula x Populus alba). CK, cytokinin; DEG, differentially expressed gene; DMG, differentially methylated gene; DMR, differentially methylated region; GO, gene ontology; SA, salicylic acid; SAM, shoot apical meristem; TE, transposable element; WD-RW, water deficit-rewatering; WW, well-watered.

  Fig. S1 Comparison of growth kinetics over the experiment between both conditions. Fig. S2 Leaf phenotypes among lines under both conditions. Fig. S3 Physiological differences among lines under both conditions. Fig. S4 Variations in DNA methylation among RNAi-ddm1 and wild-type (WT) lines in the shoot apical meristem 1 wk after rewatering (t2). Fig. S5 Strategies for bioinformatic analysis of the methylome. Fig. S6 Concepts and summary of differential methylation analyses: from ddm1 differentially methylated regions (DMRs) to phenotype. Relationship between variation in DNA methylation and gene expression. Fig. S9 Transposable element activity among RNAi-ddm1 and WT lines in the shoot apical meristem collected 1 wk after rewatering (t2).

  (b) Overview of the plants in the glasshouse. (c) Examples of plant phenotypes at t2 under WW and WD-RW conditions for WT and RNAi-ddm1 lines.

Fig. 2 Fig. 3

 23 Fig. 2Measurements of soil water content and leaf water potential during the experiment. (a) Time course of soil relative extractable water (REW) during the experiment for the wild-type (WT) and the two RNAi-ddm1 (ddm1-15, ddm1-23) transgenic poplar lines (Populus tremula x Populus alba) under control (well-watered, WW) and stress (moderate water deficit followed by rewatering, WD-RW) conditions. Water deficit in the WD-RW condition started on day 0 (t0) and lasted for 3 wk, after which plants were rewatered (t1) for an additional 1 wk period (t2). Values are genotypic means SE (n = 6 for WW, n = 12 for WD-RW). (b) Predawn leaf water potential measured at the drought peak (i.e. before rewatering on day 21) for the WT and the two RNAi-ddm1 (ddm1-15, ddm1-23) poplar lines. The white bars represent the control condition and the black bars represent the stress condition (moderate water deficit followed by rewatering). Values are genotypic means SE (n = 5). Asterisks indicate significant differences between conditions for each line (***, P < 0.001)

  Fig. 5

Fig. 8

 8 Fig. 8 Transposable element activity in RNAi-ddm1 and wild-type (WT) lines (Populus tremula x Populus alba) in shoot apical meristems (SAMs) collected 1 wk after rewatering (t2). (a) Mobilome-seq depth of coverage (read per million, rpm) of different transposable element (TE) families in wild-type (WT) and RNAi-ddm1-23 lines and in both well-watered (WW, open diamonds, 115 and 44 families for WT and RNAi-ddm1-23, respectively) and water deficit followed by rewatering (WD-RW, closed triangles, 149 and 109 for WT and RNAi-ddm1 -23, respectively) conditions. The coverage was calculated for each TE family and families are represented according to their superfamily. The four most active TE families are annotated: Gyspy23 (G23), Gypsy27 (G27), DNA-3-3 (D3), SAT-1 (S1). Transposable element activity was classified based on the sequencing coverage of eccDNA forms, as follows: TE (0 to 200 x); TE+ (200 x to 2000 x); TE++ (2000x to 10 000 x); TE+++ (10 000 x to 55 000 x). (b) DNA methylation variations at active TEs in RNAi-ddm1 vs WT, represented for each context of methylation under WW (open plots) and WD-RW (closed plots) conditions. Note that no active TE could be detected inside a CHH differentially methylated region (DMR) under WW conditions. (c) DNA copy number variations analyzed by quantitative polymerase chain reaction (qPCR) on SAM genomic DNA for three different TE families (DNA-3-3, Gypsy23 and SAT-1) in the WT and RNAi-ddm1 -23 lines in both WW (open circles) and WD-RW (closed circles) conditions.

( a ) (b)


Jean-François Léon

Monitoring of ambient fine particulate matter concentrations from space: Application to European and African cities

Keywords: Aerosol, Pollution, Satellite, Health, Africa

Air pollution is a major issue for global environment as well as human health and well-being. Recently, satellites which are equipped with relevant air quality instruments have been placed into orbit. In this paper, we first present a review on satellite remote sensing of particulate pollution. We then present new results for Europe and on African cities particulate air pollutants using POLDER satellite data. Based on satellite AOD observations, we show that the number of days exceeding the 15.4 µg/m 3 threshold is twice frequent in Ouagadougou, Burkina-Faso than in Paris, France. At the regional scale, we observe that the northern coast of the golf of Guinea is dramatically impacted by poor air quality.

INTRODUCTION

Air pollution is a major issue for global environment as well as human health and well-being. Expose to airborne fine particulate matter is associated with adverse human health effects. [START_REF] Dockery | An association between air pollution and mortality in Six U.S. cities[END_REF][START_REF] Pope | Review of epidemiological evidence of health effects of particulate air pollution[END_REF] According to Aman et al., [START_REF] Aman | CAFE scenario analysis Report Nr.2: The 'current legislation' and the 'Maximum technically feasible reduction' cases for the CAFE baseline emission projections[END_REF] the mean statistical loss in life expectancy estimated in 2000 that can be attributed to anthropogenic contributions to fine particulate matter (PM2.5) is 9 months for the EU-25 countries. In their recent study, Pope et al. [START_REF] Pope | Fine-particulate matter air pollution and life expectancy in the united states[END_REF] evaluate the change in life expectancy in relation with differential change in fine particulate air pollution (PM2.5) that occurred in the United States during the 1980s and 1990s. They found that a decrease of 10 µg/m 3 in the concentration of fine particulate matter was associated with an estimate increase in mean life expectancy of 0.61 (±0.20) year. In response to the risk due to pollution fine particles, governments have adopted regulations for the monitoring of PM ambient concentrations and mitigation (Clean Air Act US congress in 1990, Clean Air for Europe and the 1996 framework directive, . . . ). Several national environmental agencies monitor PM10 and PM2.5 concentrations through a dense but geographically limited network. Few long-term measurement sites exist in rapidly developing countries where concentrations and estimated health impacts are greatest. Satellite observation can bring an new insight in particulate air quality monitoring by providing near global observations of aerosol concentrations and then substantially improve estimates of population exposure to PM.

POLLUTION PARTICULATE MATTER

Particulate air pollutants (particulate matter; PM or aerosols) consist of material in solid or liquid phase suspended in the atmosphere. They may be either emitted into the atmosphere (primary pollutants) or formed within the atmosphere itself (secondary pollutants). Aerosols have impact on human health as they can easily penetrate into the respiratory system. There capacity to penetrate the respiratory track and their impact on the epithelium depends on their size and chemical composition which is diverse by nature. Aerosol composition can be made of a highly complex mixture of different chemical component. The ultra-fine mode is usually dominated by carbonaceous particles (black carbon and particulate organic matter) while the accumulation modes show an internal mix of inorganic salts and particulate organic matter with a core of either black carbon or mineral dust. Particulate matter (PM) is continuously monitored at air quality station. PM10 is the mass concentration of aerosol with an aerodynamic diameter less than 10 µm. In the same way, PM2.5 and PM1 corresponds to mass concentration of particles having an aerodynamic diameter less than 2.5 and 1 µm, respectively. PM10 contains coarse material and mineral dust can be a major contributor.

SATELLITE REMOTE SENSING

During the last decade, satellite remote sensing was extensively used for aerosol monitoring because of their importance for climate. Satellite data can be directly used to improve air quality assessment, management and prediction. IDEA (Infusing satellite date into environmental air quality applications [START_REF] Al-Saadi | Improving national air quality forecasts with satellite aerosol observations[END_REF] ) or the University of Maryland Baltimore County Smog blog (http://alg.umbc.edu/usaq/) are web applications which gather data from satellite missions, ground-based measurements and numerical models to analyze extreme pollution events and to improve air quality management for public benefit. The use of satellite data products for forecasting PM2.5 in chemical models is at its very beginning. Global climate models now use assimilation of standard satellite products to improve aerosol optical depth (AOD) forecasts. [START_REF] Beneditti | Aerosol analysis and forecast in the ECMWF integrated forecast system. Part II: Data assimilation[END_REF][START_REF] Zhang | A system for operational aerosol optical depth data assimilation over global oceans[END_REF] However there is no regional or global satellite PM product that can be used to constrain air quality simulation. Indeed the relationship between AOD and PM as it measured by air quality monitoring station is not straightforward. The AOD is an ambient column-integrated optical characteristic while PM is a dry mass concentration measured at a few meters above the ground. The ability of AOD to be a proxi for PM will depend on several factors including the vertical distribution of aerosol in the atmosphere, their intrinsic optical and microphysical properties, and their ability to condensate water vapor.

Most of the recently published studies rely on a direct comparison between ground-level PM (PM2.5 or PM10) with satellite retrieved AOD using a linear regression. Correlation coefficients are significant but can vary widely from one site to another. The contribution of boundary layer PM to the total aerosol optical depth can widely vary depending on local meteorology, including turbulence and convective mixing, or large-scale transport. Table 3 provides a list of correlation studies. Most of the analysis are performed regionally and for a short period of time and no universal relationship can really be drawn at the global scale. Due to the large remaining uncertainties in the AOD-PM relationship, it is quite difficult to provide a global satellite operational product. However a global conversion of AOD to PM was achieved by Van Donkelaar et al. [START_REF] Van Donkelaar | Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing[END_REF] They have used a global chemistry transport model to essentially provide information on the vertical distribution of aerosols in the atmosphere at the global scale. Indeed, aerosol remote sensing from space in the lowest first few hundred meters remains a challenging issue. The dependency of the result to the model ability to provide an accurate vertical distribution is a drawback of this method.

Rather than using a conversion factor, Kacenelenbogen et al. [START_REF] Kacenelenbogen | Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data[END_REF] have established an AOD threshold for which particulate air quality can be considered as good or moderate. This threshold has been assessed at 0.17 considering AOD at 440 nm given by POLDER instrument. Polarization of Earth's Reflectance and Directionality (POLDER [START_REF] Deschamps | The POLDER mission: Instrument characteristics and scientific objectives[END_REF] ) was one of the very first spaceborne instrument dedicated to aerosol monitoring at the global scale. POLDER is still operating aboard PARASOL satellite since 2005 and provide a daily picture of the global aerosol optical depth. POLDER AOD is derived using a technique based on the measurement of the top-of-the atmosphere polarization state of reflected light. It is highly sensitive to fine particles. [START_REF] Deuzé | Remote sensing of aerosols over land surfaces from POLDER-ADEOS-1 polarized measurements[END_REF]

EUROPE

We have followed the method proposed by Kacenelenbogen et al. [START_REF] Kacenelenbogen | Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data[END_REF] and applied it to the PM2.5 data collected in the frame of the European Monitoring and Evaluation Programme (EMEP) over the period 2006-2008. 28 stations (see black dots on Figure 3) were selected for a total of 4634 daily observations. Using the AOD at 550 nm, we have found an equivalent threshold for "moderate" AQ conditions at 0.1. Considering this threshold, more than 76% of daily average PM are correctly identified to be above 15.4 µg/m 3 . A linear regression through all the dataset gives a correlation coefficient R=0.5, a slope of 60 µg/m 3 / AOD unit and an intercept of 9 µg/m 3 . Our results are very similar to those presented in Table 3 using the MODIS sensor. [START_REF] Wang | Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies[END_REF][START_REF] Chu | Global monitoring of air pollution over land from the Earth observing system-Terra Moderate imaging spectroradiometer (MODIS)[END_REF][START_REF] Al-Saadi | Improving national air quality forecasts with satellite aerosol observations[END_REF] Figure 3 shows a map centered on Western Europe of the number of days exceeding this threshold over 2006-2008 using POLDER/PARASOL observations. Industrial and large urban areas such as the Po valley in Northern Italy or the Benelux are clearly identified as "hot spot" of poor particulate matter air quality.

Cities

AFRICAN CITIES

The urban population of Africa will double from 294 million in 2000 to 742 million in 2030 (source United Nations Population Funds). Adverse effect of poor air quality in African cities is crucial. There is a large diversity in aerosol chemical composition due to both natural (mineral dust, biomass burning due to agricultural waste burning or deforestation) and anthropogenic (poor quality fossil fuel or biofuel use) sources. The PM concentration are very high compared to north-western cities. Table 4 gives a comparison between average concentration recorded in Lille, France and 3 different cities in Northern Africa: Ouagadougou, Burkina-Faso, Bamako, Mali and Dakar, Senegal. As mineral dust in the Sahel region can contribute a lot to PM10, this can partially explains the large difference observed in the average concentrations between both cities of Lille and Ouagadougou. However, PM2.5 concentration are twice higher in Bamako than in Lille, indicating a large pollution due to anthropogenic activities.

We have compared the AOD derived from POLDER sensor aboard the PARASOL mission with the PM recorded in the 3 aforementioned African cities (Figure 5). The PM data were acquired on a weakly basis during ground-based field experiments. The variation in monthly mean AOD and PM2.5 shows the same tendency in Dakar, except in October. In Bamako, both PM and AOD have low tendency during the summer months but their variation differs significantly at the end of the year. During summer, mass concentrations and AOD are low due to the monsoon rain. However some extreme events in PM2.5 are not detected in the AOD. We also observe a similarity in the PM10 and AOD variation on a weakly basis over Ouagadougou.

Considering the threshold established by Kacenelenbogen et al., [START_REF] Kacenelenbogen | Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data[END_REF] the number of days in "moderate" air quality category with respect to PM is 64% in Ouagadougou and 53% in Bamako (percentage over 2006-2008 period). As a comparison, this percentage is 31% in Paris, France. Figure 5 shows the seasonal cycle of poor air quality in Bamako. The worst conditions are observed in May. The number days in the "moderate" AQC decreases during the rainy season (July-August). Applying this threshold to the whole western Africa (Figure 3 on the right) shows that most of the coasts surrounding the Golf of Guinea are 90% of the time with degraded air quality conditions.

CONCLUSIONS AND PERSPECTIVES

Particulate pollution monitoring from space remains a challenging issue. Many studies have been devoted to quantitative assessment of PM from satellite derived aerosol optical depth over Europe and the US. In this paper, we have first used the EMEP PM2.5 data to verify that the threshold established by Kacenelenbogen et al. [START_REF] Kacenelenbogen | Characterization of aerosol pollution events in France using ground-based and POLDER-2 satellite data[END_REF] on POLDER satellite AOD can be used to identify polluted days. Then we have compared the POLDER fine mode optical depth to PM recorded in the major African cities of Bamako, Ouagadougou and Dakar. The similarities in the monthly and weakly trend of both PM and AOD indicates that this parameter might also be used as an estimator of PM concentration over major African cities. Regional picture of degraded air quality clearly higlights the coastal area in the northern part of the golf of Guinea.

Particulate pollution satellite remote sensing for air quality management and health risk assessment is in its infancy. Satellite missions dedicated to climate survey provide both quantitative and qualitative valuable information for PM monitoring. Further analysis of the data collected by the CALIOP lidar aboard CALIPSO mission (NASA-CNES) should provide crucial information on the aerosol vertical structure, which is a critical parameter for particulate pollution monitoring from space. However a dedicated air quality monitoring mission is still required for a quantitative assessment of pollution from space.

Figure 1 .

 1 Figure 1. Percentage of POLDER/PARASOL observations during year 2008 with a fine mode AOD above 0.17.

Figure 2 .

 2 Figure 2. Comparison between monthly mean POLDER-derived fine mode AOT and PM2.5 in the city of (left) Dakar and (center) Bamako. Comparison between weakly mean POLDER-derived fine mode AOT and PM10 in the city of Ouagadougou.

Figure 3 .

 3 Figure 3. Monthly percentage of days with a POLDER/PARASOL AOD at 550 nm above 0.1 in Bamako, Mali from 2006 to 2008.

Table 1 .

 1 List of correlative studies linking PM to AOD (adapted from Hoff and Christopher 21 ).

	5

Table 2 .

 2 Average PM10 and PM2.5 concentrations for different cities ( a From December 2007 to October 2008; b April 2008 to May 2009; c April 2008 to October 2008).

	PM10	PM2.5
	µg/m 3	µg/m 3

ACKNOWLEDGMENTS

In situ data have acquired in the frame of CORUS-POLCA program. The authors thank Bernard Nana for providing PM data in Ouagadougou. The author also thank the ICARE thematic center for providing an easy access to satellite data and products used in this paper. We thank the Norvegian meteorological institute for giving an access to the EMEP data.