Guilherme, Lê, Pedro Brazil

Gabi

Naty (from Lausanne), Carol mana Guilherme Fernando

Taboada

Caroline Emanuel

My Friends From Banyuls

Cicero Sheree

Francesca Jem

Lydvina, Laurie Nicola Anthony

Pavla

Coco

Jingguang Yan

Kathy

Elisa Haley

Fred Francine Marc

Vanda Éric

Jari, Ina, Imer, Xavi, Luis François

Elizabeth Renck

Marita Redin

Victor Hugo

Douglas Galante

Inacio Domingues

This thesis was one of the most challenging endeavors that I already faced. In fact, I believe that pursuing a PhD thesis is probably one of the most difficult things that anyone can do. A PhD student have to focus on learning a specific novel problem and think about how to solve it, or at least, indicate the possible paths to its solution, which may result in new discoveries. This can come sometimes with social isolation, for obvious reasons.

2010

). Algal organisms exist in the majority of "supergroups", that are 'kingdom-equivalents' of major lineages of eukaryotes [START_REF] Keeling | Progress towards the Tree of Eukaryotes[END_REF][START_REF] Burki | The New Tree of Eukaryotes[END_REF], as Archaeplastida (green Chlorophyta, red Rhodophyta and Glaucophyta), the SAR group (Stramenopila, Alveolata, and Rhizaria), Excavata and a series of Incertae sedis organisms, but are not found in the Amoebozoa and Opisthokonta (animals and fungi) supergroups [START_REF] Burki | The eukaryotic tree of life from a global phylogenomic perspective[END_REF][START_REF] Coy | Viruses of Eukaryotic Algae: Diversity, Methods for Detection, and Future Directions[END_REF]. Thus, while oxygenic photosynthesis is monophyletic, the eukaryotic algae are polyphyletic, given the secondary and tertiary acquisitions that spread plastids through lineages other than Archaeplastida algae in multiple and independent endosymbiotic events, including a possible primary independent event in Paulinella spp. (Raven and Giordano 2014;[START_REF] Archibald | Endosymbiosis and eukaryotic cell evolution[END_REF][START_REF] Brodie | The Algal Revolution[END_REF].

Furthermore, eukaryotic algae are morphologically and physiologically diverse, differing in their photosynthetic pigments and cell structures, and ranging in sizes from pico and nano Diplomonad (e); Foraminifera (f); Centrohelid (g). Figure adapted from [START_REF] Sibbald | More protist genomes needed[END_REF].

In protists we find the most extreme cases in terms of eukaryotic genome sizes, as in some Amoebozoans, with the largest known genomes (200 times larger than the human genome) [START_REF] Keeling | Causes and effects of nuclear genome reduction[END_REF] and also Dinoflagellates, possessing genomes 1-77 fold larger than that of the human genome, and than any other algae by a factor of hundreds to thousands [START_REF] Lajeunesse | Symbiodinium (pyrrhophyta) Genome Sizes (dna Content) Are Smallest Among Dinoflagellates1[END_REF][START_REF] Hou | Distinct Gene Number-Genome Size Relationships for Eukaryotes and Non-Eukaryotes: Gene Content Estimation for Dinoflagellate Genomes[END_REF]. At the same time, we found small and compact genomes, as in some Mamiellales green algae (around 13-22 Mb) (Moreau et al. 2012) and in the nucleomorph genomes of Cryptomonad and Chlorarachniophyte algae, remnants of nuclear genomes of what were once free-living algae, which just a few hundred genes, making them the smallest eukaryotic nuclear genomes [START_REF] Douglas | The highly reduced genome of an enslaved algal nucleus[END_REF][START_REF] Gilson | Complete nucleotide sequence of the chlorarachniophyte nucleomorph: nature's smallest nucleus[END_REF].

Protist species are the most abundant eukaryotes in marine pelagic communities and constitute an important and substantial fraction of the total plankton biomass, having a pivotal ecological role in marine ecosystems [START_REF] Ohtsuka | Marine Protists: Diversity and Dynamics[END_REF][START_REF] Worden | Rethinking the marine carbon cycle: Factoring in the multifarious lifestyles of microbes[END_REF][START_REF] Caron | Probing the evolution, ecology and physiology of marine protists using transcriptomics[END_REF]. Despite their fundamental roles in those ecosystems, genomic data and knowledge about them are still far behind those of other eukaryotes. These data could permit the understanding of protistan diversity distribution, evolutionary history, life cycles and interactions.

Life cycles in protists

Protist algal cells can experience dramatic transitions between an actively growing phase and phases in which cells are dormant, dead or undergo sexual reproduction. These phase transitions represent an organism's life cycle. Life cycles are key elements to understand species natural history, and yet remain one of the least understood aspects of algal biology. Some of these phases may be more ephemeral, episodic or challenging to observe, as the case of sexual cycles [START_REF] Von Dassow | Unveiling the mysteries of phytoplankton life cycles: patterns and opportunities behind complexity[END_REF]. In fact, for a long time it was assumed that protists lacked sexual stages [START_REF] Smith | The evolution of sex[END_REF]Tibayrenc et al. 1990;Tekle et al. 2017), given that these phase transitions are often difficult to induce and control under cultured laboratory conditions (von Dassow and Montresor 2011), posing major challenges when studied with classical observation methods, such as light microscopy.

The lack of mating partners, or the low frequency of sex interactions under laboratory conditions could be other factors that can hamper the empirical observations of sexual stages [START_REF] Dunthorn | Secretive ciliates and putative asexuality in microbial eukaryotes[END_REF][START_REF] Lahr | The chastity of amoebae: re-evaluating evidence for sex in amoeboid organisms[END_REF]. Moreover, some groups, as picoplanktonic protists, pose an even higher difficulty given their small size and lack of sufficient morphological characters to enable differences between cell types and stages.

Under these scenarios, modern genomic tools have been unveiling the capacity to perform sex (syngamy and meiosis) of diverse protist groups such as Amoebozoans, Dinoflagellates, Diatoms, Chrysophytes and Mamiellales, using genome assemblies or transcriptomes not only to screen for sex specific or related genes involved in processes such as membrane fusion, karyogamy and meiosis, (Ramesh et al. 2005;Derelle et al. 2006;[START_REF] Malik | An Expanded Inventory of Conserved Meiotic Genes Provides Evidence for Sex in Trichomonas vaginalis[END_REF][START_REF] Chi | Cryptic sex in Symbiodinium (Alveolata, Dinoflagellata) is supported by an inventory of meiotic genes[END_REF]Weedall et al. 2015;[START_REF] Patil | Identification of the meiotic toolkit in diatoms and exploration of meiosis-specific SPO11 and RAD51 homologs in the sexual species Pseudo-nitzschia multistriata and Seminavis robusta[END_REF][START_REF] Dunthorn | Meiotic genes in colpodean ciliates support secretive sexuality[END_REF][START_REF] Hofstatter | Comparative Genomics Supports Sex and Meiosis in Diverse Amoebozoa[END_REF][START_REF] Kraus | Putatively asexual chrysophytes have meiotic genes: evidence from transcriptomic data[END_REF], but also data from populations that can show evidence of recombination (Grimsley et al. 2010;Blanc-Mathieu et al. 2017). Currently, sex is regarded as a ubiquitous and inherent feature of eukaryotic life (Speijer et al. 2015), and is predicted to have evolved early in the most recent common ancestor of eukaryotes. In this sense, sexuality would be the ancestral state of eukaryotes and asexuality would have evolved later and several times independently (Goodenough and Heitman 2014;Dacks and Roger 1998). All of these referred cases suggested by genomic analysis constitute only indirect evidence for sexual reproduction, indicating "cryptic sexuality". In this regard, there is still a lack of direct observation of sexual interactions and sex cycles for many key species of protists [START_REF] Dunthorn | Secretive ciliates and putative asexuality in microbial eukaryotes[END_REF], Speijer et al. 2015) as in the case of the planktonic algae of the class Mamiellophyceae (Marin and Melkonian 2010;Grimsley et al. 2010). that a random acting process driven by biotic interactions operates in the extinction of species.

Because every species does the best to face pressures, such as competition, predation and parasitism, the response to one kind of pressure may well decrease the species resistance to some other.

In Carrol's book [START_REF] Lively | A review of red queen models for the persistence of obligate sexual reproduction[END_REF]:

" Alice runs after the Red Queen but is further perplexed to find that neither one seems to be moving. When they stop, they are in exactly the same place, which the Red Queen responds: "Now, here, you see, it takes all the running you can do to keep in the same place. "" This can be taken as coevolution between species partners, so the evolutionary change is required to keep the status quo , and if there is no change by one of the partners, this can result in an extinction event. Thus, Van Valen adopted this imagery from Lewis Carrol story as a metaphor for interactions between species, suggesting that the extinction rates might be due to these interactions [START_REF] Lively | A review of red queen models for the persistence of obligate sexual reproduction[END_REF]).

The genetic basis of sexual interactions in protists: mating types

In 1937, while studying the process of endomixis (nuclear reorganization of the cell) in the ciliate Paramecium , Sonneborn discovered certain "races" of P. aurelia that presented functional sexual activity. Although Paramecium was considered for a long time as an example of an organism lacking sex, two classes of individuals were described, and the conjugation process was observed to happen with specific members of some of theses classes [START_REF] Sonneborn | Sex, Sex Inheritance and Sex Determination in Paramecium Aurelia[END_REF]. After this, Sonneborn managed to divide the "stock" of P. aurelia in two sex classes and observed that this conjugation only happens between individuals of opposite sex type. Later in 1938, Sonneborn, while resuming his early observations (1937) that conjugation followed by the clumping (joining of cells) occurrying between individuals of diverse "types", started to referrer to these types as "mating types", a purely descriptive term, to replace the interpretative terms "sexes", "sex types" and "sex reaction types" used previously to describe the mating reaction. He also derived general rules required for a successful mating between Paramecium strains (or stocks according to the nomenclature) as:

" The first and most important one is that animals of appropriate different mating types must be brought together (…) individuals must not be overfed. Finally, in order to react, they must not be undergoing fission, endomixis or conjugation ." Sonneborn finished his remarks noting that Paramecium mating system was " strikingly similar to the sexual differences between gametes in some of the unicellular green alga " where cells that were able to perform mating were from two types (plus and minus) and clump and proceed to mating when present together under certain conditions [START_REF] Strehlow | thber die Sexualitat einiger Volvocales[END_REF][START_REF] Moewus | Untersuchungen fiber die Sexualitait und Entwicklung von Chlorophyceen[END_REF][START_REF] Moewus | Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus[END_REF], suggesting that:

" the plus and minus sexes in the unicellular alga are like the mating types of Paramecium ".

While meiosis processes evolved early in eukaryotes, since there is indirect evidence for such a process in the form of presence of meiotic genes in the majority of extant protist taxa (Speijer et al. 2015), the processes that govern the initial stages of sexual cycles are not well known or for many protist groups, specially in green algae.

Reproductive systems can be classified in a general way as being isogamous, where all gametes are morphologically indistinguishable, mostly in terms of size, with no separation into male and female gametes, thus there is a lack of "sexes", or "gender" (as some authors refer to male and female sexes) and anisogamous, when there is size dimorphism of gametes and they are separated by sexes [START_REF] Lehtonen | What do isogamous organisms teach us about sex and the two sexes?[END_REF]. Most unicellular protists are isogamous, suggesting that this constitutes the ancestral state of eukaryotes, since anisogamy probably evolved from isogamy [START_REF] Bulmer | The evolution of anisogamy: a game-theoretic approach[END_REF][START_REF] Lehtonen | What do isogamous organisms teach us about sex and the two sexes?[END_REF]. In isogamous species, the differences between the "types" of gamete classes are genetically encoded, requiring the joining of cells bearing differences at a genomic locus, encoding opposite types of each other, and only those would attract each other, mate and produce progeny [START_REF] Bachtrog | Sex Determination: Why So Many Ways of Doing It[END_REF]. These sexual types are referred to "mating types" ( MTs ) that are classes of gametes that govern the sexual cycle.

Isogamy would theoretically allow an unlimited number of MTs mostly because high numbers increase the probability that randomly mating partners display complementarity [START_REF] Bachtrog | Sex Determination: Why So Many Ways of Doing It[END_REF]). Nevertheless, the majority of species only exhibits two mating types, with rare and extreme cases as the fungi species Schizophyllum commune , which shows over 23,000 mating types, encoded in multiallelic regions [START_REF] Billiard | Having sex, yes, but with whom? Inferences from fungi on the evolution of anisogamy and mating types[END_REF][START_REF] Kothe | Tetrapolar fungal mating types: sexes by the thousands[END_REF][START_REF] Constable | The rate of facultative sex governs the number of expected mating types in isogamous species[END_REF]. Recently, [START_REF] Constable | The rate of facultative sex governs the number of expected mating types in isogamous species[END_REF] provided a model to explain the numbers of mating types in a given species, and predicted that the observed low numbers of mating types in the majority of organisms are associated with low mutation rates, small effective population sizes and facultative (rare) sex, when reproduction occurs through asexual processes as cell division.

Chlamydomonas mating types: a model of sex evolution in Chlorophyta

The first reports of the mating processes in algae, with connections between stress, as in Chlamydomonas , and other algae were made by the German botanist Georg [START_REF] Klebs | Die Bedingungen der Fortpflanzung bei einigen Algen und Pilzen[END_REF] in the book " Die Bedingungen der Fortpflanzung bei einigen Algen und Pilzen ", involving nutrient depletion and light changes (Sager and Granick 1954). In the paper "Nutritional control of sexuality in Chlamydomonas reinhardi ", Sager and Granick (1954) noted that given the fact that mating behavior in this species was not understood in terms of predictability, the factors and conditions that govern mating behavior needed to be carefully investigated in order to control the mating process. To that aim, these authors performed several crosses of plus and minus mating types, under multiple conditions, such as presence/absence of nutrients and light, and presented evidence for differentiation of vegetative growing cells into gametic cells when the nutrient sources were depleted from the growth medium, but were most effective when it was nitrogen depleted, which stressed the algae, inducing cell differentiation into gametes. Light regimes also had an indirect influence in zygote formation, since cells which grow in the dark receiving acetate as external carbon sources only formed zygotes in this condition and in lower quantities.

Experiments conducted at that stage reported that the suspension of cells in distilled water and aged cultures were able to induce gamete formation and zygotes in several protists including Chlamydomonas . Nevertheless, the precise indication made by Sager and Granick (1954) of the key role of nitrogen to activate and modulate the sexual cycle and intensity of gamete production in Chlamydomonas was considered a milestone in the field, given that enabled the fine control of the system. In comparative terms, these authors discussed similarities with Sonneborn's Paramecium (1938) and also with [START_REF] Elliott | Mating Types in Tetrahymena[END_REF] studies in Tetrahymena , another ciliate, which also performed mating under starvation, by mixing mating types and washing the cultures in distilled water. Also, Sager and Granick (1954) made a parallel with the effects of nitrogen depletion in plants, which was known to control flowering bud differentiation [START_REF] Miller | Plant Physiology[END_REF]. At this stage, no molecular mechanism connecting nitrogen deficiency with mating types was known, because these experiments occurred in a pre-molecular biology era. Today the full sexual cycle, the molecular pathways and genes involved in Chlamydomonas are well known, making Chlamydomonas the best described Chlorophyte in terms of sexual interactions, and the evolution of mating types in the Volvocales lineage is better understood.

The first genetic maps of Chlamydomonas mating type loci, obtained via cloning, were reported by [START_REF] Ferris | The mating-type locus of Chlamydomonas reinhardtii contains highly rearranged DNA sequences[END_REF]. It was known that in the haploid state, the locus controls gametic interactions, and that in the diploid state it controls organelle transmission and meiosis [START_REF] Ferris | Transcription of novel genes, including a gene linked to the mating-type locus, induced by Chlamydomonas fertilization[END_REF]. Using the chromosome walking technique, [START_REF] Ferris | The mating-type locus of Chlamydomonas reinhardtii contains highly rearranged DNA sequences[END_REF] described twelve genes in the mating type locus, mt+ and mt-, tightly linked to mt , with seven having no apparent roles in life cycles or sex, suggesting that the locus exerts suppression of recombination. Three domains inside the mt locus could be recognized, the central domain R (from rearranged) which contains major rearrangements, insertions and deletions, lacking collinearity, the C domain (centromere-proximal) with transposon insertions and a region called "the swamp" containing tandem repeats, and last the T domain (telomereproximal). At that time, no mating type specific gene was identified, although the gene fus1 , the "fringe" glycoprotein was located inside the R domain, the probable candidate region to contain these specific genes, was observed only in the mating type plus strain [START_REF] Ferris | A sex recognition glycoprotein is encoded by the plus mating-type gene fus1 of Chlamydomonas reinhardtii[END_REF]. It was only in 1997 that Ferris and Goodenough identified a specific gene for the mating type minus in the R region of the minus mating type strain of Chlamydomonas reinhardtii, the Minus Dominance Gene (MID). The MID gene, the master sex controller gene which initiates the sex cycle, is a transcription factor of the RWP-RK family (Nishimura et al. 2017).

lichenologist Heinrich Anton de [START_REF] De Bary | Vortrag: Uber Symbiose[END_REF][START_REF] De Bary | Chapter Two -Diversity and Evolution of Algae: Primary Endosymbiosis[END_REF] as a long term intimate association between organisms of dissimilar species, and these associations can range from extremes such as parasitism, where one partner benefits at the expense of the other, when generally the host is affected, to mutualism, where both partners benefit from the interaction. While the most common symbiosis is between two kinds of partners, it could entail multiple entities. Symbiosis is present in virtually all living organisms, it is central to the evolution and ecology of ecosystems, although their contributions to organismal life history started to receive more attention just recently [START_REF] Smith | Generating novelty by symbiosis[END_REF][START_REF] Margulis | Whittaker's Five Kingdoms of organisms: minor revisions suggested by consideration of the origin of mitosis[END_REF]Fester 1991, Mordret et al. 2016). Through registering around 2,500 ecological interactions by screening ~500 publications from the last 150 years, [START_REF] Bjorbaekmo | The planktonic protist interactome: where do we stand after a century of research?[END_REF], found that all major aquatic protist lineages were engaged in interactions in one or multiple ways, and that "symbiosis" was the most common interaction (43%), followed by predation (39%) and parasitism (18%). If we sum the categories "symbiosis" with "parasitism", since in this case these authors equate symbiosis with mutualism, we will find that the majority (61%) of these interactions would be from the symbiotic type sensu de Bary (1878, 1879).

Red queen, sex and parasites

While [START_REF] Van Valen | A new evolutionary law[END_REF] did not apply his law of extinction to sexual interactions, [START_REF] Bell | The Masterpiece of Nature: The Evolution and Genetics of Sexuality[END_REF] used the same name "Red Queen" for a hypothesis based on parasite hosts interactions and their role in the maintenance of sexual reproduction. In Bell's theory, as in Van Valen "Red Queen", hosts and parasites are constantly evolving in response to each other, but instead of explaining extinction rates from the resulting dynamics, the idea is to capture the movement of genotypes through time that oscillate in hosts and parasites. In this framework, host genotypes that become common should eventually be selected against by virulent parasites, leading to host/parasite genotype oscillations over time, that averaged over thousands of generations appears to remain constant. [START_REF] Jaenike | A hypothesis to account for the maintenance of sex in populations[END_REF] already proposed that not only abiotic pressures are exerted on organisms, but biotic pressures as well as competition, predation and parasitism. Under this intense pressure to escape, sexual reproduction, resulting in recombination and generation of not only novel but rare genotypes, would allow organisms to escape in time. Parasite infections could explain short-term advantages of sex, if novel genotypes produced by sexual females permits to escape in time from pre-adapted parasites or from parasites that spread preferentially among parental clones [START_REF] Bremermann | Sex and polymorphism as strategies in host-pathogen interactions[END_REF][START_REF] Rice | Parent-offspring pathogen transmission: A selective agent promoting sexual reproduction[END_REF][START_REF] Kelley | Viral pathogens and the advantage of sex in the perennial grass Anthoxanthum odoratum[END_REF]. Thus, in the presence of parasites, sexual females would gain a fitness advantage for their offspring by this time escape from parasites that are pre-adapted to the parental genotype or, through the production of rare genotypes [START_REF] Kelley | Viral pathogens and the advantage of sex in the perennial grass Anthoxanthum odoratum[END_REF]. In Metazoa, lineages of obligate sexuals can outcompete obligate asexuals when comparing host resistance to parasites [START_REF] Michiels | Parthenogenetic flatworms have more symbionts than their coexisting, sexual conspecifics, but does this support the Red Queen?[END_REF][START_REF] Vergara | Infection dynamics in coexisting sexual and asexual host populations: support for the Red Queen hypothesis[END_REF]. Parasites can generate strong selective forces against hosts, and this was empirically demonstrated in flatworms and snails, where parasites generally adapt locally to common host genotypes [START_REF] Michiels | Parthenogenetic flatworms have more symbionts than their coexisting, sexual conspecifics, but does this support the Red Queen?[END_REF][START_REF] Jokela | The maintenance of sex, clonal dynamics, and host-parasite coevolution in a mixed population of sexual and asexual snails[END_REF][START_REF] Auld Skjr Tinkler | Sex as a strategy against rapidly evolving parasites[END_REF]. Thus, running in-order-to-stay-in-the-same place is an appropriate metaphor for host-parasite interactions, leading to selection for genetic diversity. Under this assumption, sex could be maintained by parasite-mediated selection against common clonal genotypes by generating diversity in short term, and in the opposite way, parasites would evolve other ways to infect them, and in the case of failing, one would go extinct [START_REF] Lively | A review of red queen models for the persistence of obligate sexual reproduction[END_REF][START_REF] Lively | Sex uncovered special issue: The ecology of sexual reproduction[END_REF]. Once that sex can recycle alleles that may generate novel resistance genotypes on which selection can act, maintaining host fitness despite evolving virulent parasites, Red Queen dynamics may favor the permanence of sexual over asexual reproduction [START_REF] Haeckel | Generelle Morphologie der Organismen[END_REF][START_REF] Hamilton | Sex versus Non-Sex versus Parasite[END_REF][START_REF] Auld Skjr Tinkler | Sex as a strategy against rapidly evolving parasites[END_REF].

Although the Red Queen hypothesis, both in Van Valen's and Bell form, has been controversial since early discussions [START_REF] Benton | The Red Queen and the Court Jester: species diversity and the role of biotic and abiotic factors through time[END_REF], their broader insight that brought biotic interactions as drivers of change in evolution has been hugely influential and the main body of the hypothesis has been tested, providing compelling empirical results that support the hypothesis across a range of biotic systems (Lively 1990;[START_REF] Busch | Evidence for maintenance of sex by pathogens in plants[END_REF][START_REF] Venditti | Phylogenies reveal new interpretation of speciation and the Red Queen[END_REF][START_REF] Ezard | Interplay between changing climate and species' ecology drives macroevolutionary dynamics[END_REF][START_REF] Brockhurst | Running with the Red Queen: the role of biotic conflicts in evolution[END_REF].

Sex and parasites: a case for viruses?

In host/virus dynamics, the host or virus that most recently changed is the one that is temporarily winning the genetic conflict, since there is constant evolutionary pressure on the losing side to change, given that host adaptation is often counteracted by viral adaptation, which is in turn counteracted by the host again. Indeed, these cyclical host-virus interactions make both parties rapidly evolve to deviate from or restore the status quo in the interaction, and also, this can be true for molecular parasites as endogenous retroelements [START_REF] Daugherty | Rules of Engagement: Molecular Insights from Host-Virus Arms Races[END_REF].

As an example of this dynamic, [START_REF] Kelley | A test of the short-term advantage of sexual reproduction[END_REF] showed that in a plant species, Anthoxanthum odoratum , which produces sexual and asexual offspring, the sexual offspring had higher reproductive rates than asexual offspring. This survival difference was later explained by susceptibility to an RNA virus [START_REF] Kelley | Viral pathogens and the advantage of sex in the perennial grass Anthoxanthum odoratum[END_REF].

Viruses and symbiosis

Since the discovery of tobacco mosaic virus (TMV), the first virus description, independently by [START_REF] Ivanovsky | Concerning the mosaic disease of the tobacco plant[END_REF] that reported that the disease was caused by a filterable infectious agent, and by [START_REF] Beijerinck | Concerning a contagium vivum fluidum as a cause of the spot-disease of tobacco leaves[END_REF], which described an infectious soluble agent, or " contagium vivum fluidum " (contagious living fluid), viruses have been largely viewed as pathogens [START_REF] Lustig | One hundred years of virology[END_REF][START_REF] Roossinck | The good viruses: viral mutualistic symbioses[END_REF]. By definition, viruses are parasitic biological entities, since they benefit from their hosts by sequestering their molecular machinery, yet it does not mean that they cannot perform commensal or even mutualistic roles, given that these distinctions are dependent on whether the benefits conferred by the association outweigh the costs (Roosinck and Bazan 2017). While parasitic relationships between host and viruses are the most known and studied, commensal relationships where there are no observable costs to the host and no recognizable symptoms associated with diseases, are probably the most common [START_REF] Breitbart | Here a virus, there a virus, everywhere the same virus?[END_REF][START_REF] Suttle | Viruses in the sea[END_REF][START_REF] Wren | Plant Virus Biodiversity and Ecology[END_REF]Roosinck and Bazan 2017). Their evolutionary plasticity and genetic versatility make viruses excellent models to understand the formation and maintenance of symbiotic relationships (Roosinck and Bazan 2017).

Marine viruses

Viruses are the most abundant biological entities in the earth's oceans. Concentrations up to 10 8 mL -1 have been observed [START_REF] Bergh | High abundance of viruses found in aquatic environments[END_REF]) with abundances typically of 10 10 per liter in surface waters [START_REF] Fuhrman | Marine viruses and their biogeochemical and ecological effects[END_REF]. Over 5,000 viral genotypes had been found in just 100 L of seawater and about 1 million species in just 1 kg of marine sediment (Rohwer and Vega Thurber 2009). Twenty to 40% of marine microorganisms may be killed by viruses on each day (Suttle 2007). Viral lysis of host cells may be responsible for a significant fraction of the total carbon, and nutrient regeneration by release of element-rich cell components [START_REF] Middelboe | Effects of viruses on nutrient turnover and growth efficiency of noninfected marine bacterioplankton[END_REF][START_REF] Noble | Rapid Virus Production and Removal as Measured with Fluorescently Labeled Viruses as Tracers[END_REF]. Indeed, 6-26% of fixed carbon in the photic zone is recycled as a result of host lysis, through the "viral shunt" phenomenon [START_REF] Wilhelm | Viruses and Nutrient Cycles in the SeaViruses play critical roles in the structure and function of aquatic food webs[END_REF], making viruses dynamic components of the marine microbial loop [START_REF] Suttle | Viruses in the sea[END_REF].

The viral shunt phenomenon consists in the release of particular or dissolved organic material, provided from cellular debris being primarily used by microorganisms, but also by inorganic nutrients rapidly assimilated by eukaryotic plankton [START_REF] Poorvin | Viral release of iron and its bioavailability to marine plankton[END_REF], instead of being used by the higher trophic level organisms such as plankton and fishes [START_REF] Weitz | Ocean viruses and their effects on microbial communities and biogeochemical cycles[END_REF]).

On a planetary scale, marine viruses can modulate biogeochemical cycles releasing and recycling nutrients through host mortality through the viral shunt (Hurwitz and U'Ren 2016), and horizontal gene transfer (HGT) (Monier et al. 2009), with transference estimations of ∼10 29 genes per day [START_REF] Paul | Microbial gene transfer: an ecological perspective[END_REF]. By host metabolic reprogramming [START_REF] Breitbart | Marine viruses: truth or dare[END_REF][START_REF] Rosenwasser | Rewiring Host Lipid Metabolism by Large Viruses Determines the Fate of Emiliania huxleyi, a Bloom-Forming Alga in the Ocean[END_REF][START_REF] Hurwitz | Metabolic reprogramming by viruses in the sunlit and dark ocean[END_REF]) viruses could have a direct impact on world climate by increasing the emission of biological sulfur molecules like dimethylsulfide, that acts as a cloud and acid rain catalysts [START_REF] Bratbak | Viral activity in relation to Emiliania huxleyi blooms: A mechanism of DMSP release?[END_REF].

The vast majority of these viruses are bacteriophages [START_REF] Breitbart | Marine viruses: truth or dare[END_REF], while 1 to 10% of the viral pool is represented by eukaryotic virus from the NCLDV group [START_REF] Brussaard | Viral control of phytoplankton populations--a review[END_REF], including large algal viruses, with genome abundances estimated from 4000 to 170,000 genomes per mL in the photic zone on the surface of the ocean [START_REF] Hingamp | Exploring nucleo-cytoplasmic large DNA viruses in Tara Oceans microbial metagenomes[END_REF][START_REF] Wilson | Development of DNA mismatch repair gene, MutS, as a diagnostic marker for detection and phylogenetic analysis of algal Megaviruses[END_REF].

Algal viruses

In the region comprising the euphotic zone of aquatic environments, planktonic algae are responsible for about half of the photosynthetic activity of the planet [START_REF] Field | Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components[END_REF]), being at the base of the global food web. In those environments, co-occurring with algae, viruses outnumber bacteria by a ratio of 10 to 1 [START_REF] Grimsley | Genomic of Algal Host-Virus Interactions[END_REF]. Algal viruses are powerful drivers in the control of algal blooms, and yet little is known about their biological functions, host-virus pair diversity and genome characteristics, especially when considering conservative estimations of algal species diversity, from 100 000 to several million species with only ~40 000 species identified, and only ~60 algal viruses formal identifications, at least until the last decade (Wilson et al. 2005[START_REF] Wilson | The Phycodnaviridae: The Story of How Tiny Giants Rule the World[END_REF][START_REF] Coy | Viruses of Eukaryotic Algae: Diversity, Methods for Detection, and Future Directions[END_REF].

The first reports of viruses in algae, in form of viral-like particles (particles with resemblance with viral capsids but with no genetic and infectivity information), date back from the 1950's, but further confirmations about their viral nature came only in the 1970's, with detailed micrographs of large particles with sizes around 100-200 nm [START_REF] Brown | Algal viruses[END_REF]Van Etten et al. 1991;[START_REF] Grimsley | Genomic of Algal Host-Virus Interactions[END_REF]. Algal viruses revealed extreme modes of architectural organization, in terms of nucleic acid types, as DNA or RNA in linear, circular, single or double-stranded, and segmented genomes, also different genome sizes (4.4 to 638 kb) (Short et al. 2018;[START_REF] Coy | Viruses of Eukaryotic Algae: Diversity, Methods for Detection, and Future Directions[END_REF]. While most of these are lytic, dsDNA viruses, other life cycles and strategies, such as lysogenic, mutualistic viruses, and slow growers could have been missing from surveys, since this could be a bias of the cultivation and isolation techniques, as well as the molecular kit protocols implemented when investigating viruses in the environment and/or viral-host systems in the laboratory.

The majority of characterized algal viruses with a complete genome sequence, come from the family Phycodnaviridae, with the first isolated member in 1979 from the Mamiellales Micromonas pusilla [START_REF] Mayer | A virus which lyses the marine nanoflagellate Micromonas pusilla[END_REF]. Phycodnaviridae is a family of large double stranded DNA viruses and belongs to the superfamily of Nucleocytoplasmic Large DNA Virus (NCLDV) [START_REF] Iyer | Evolutionary genomics of nucleo-cytoplasmic large DNA viruses[END_REF]), a diverse viral group that shares a set of 25-50 conserved genes encoding mainly structural and informational proteins [START_REF] Iyer | Evolutionary genomics of nucleo-cytoplasmic large DNA viruses[END_REF][START_REF] Yutin | Mimiviridae: clusters of orthologous genes, reconstruction of gene repertoire evolution and proposed expansion of the giant virus family[END_REF][START_REF] Filée | Genomic comparison of closely related Giant Viruses supports an accordion-like model of evolution[END_REF], and contains large and giant viruses from the families Ascoviridae , Asfarviridae , Iridoviridae , Marseilleviridae , Megaviridae , Mimiviridae , Pandoraviridae , Pithoviridae , Poxviridae and Phycodnaviridae [START_REF] Abergel | The rapidly expanding universe of giant viruses: Mimivirus, Pandoravirus, Pithovirus and Mollivirus[END_REF]. Phycodnaviruses infect freshwater and marine algae, with capsid sizes ranging from 100 to 220 nm, and genomes ranging in length from 170 to 560 kb [START_REF] Van Etten | Phycodnaviridae--large DNA algal viruses[END_REF][START_REF] Wilson | The Phycodnaviridae: The Story of How Tiny Giants Rule the World[END_REF]). The Phycodnaviridae family comprises six genera named after the hosts they infect when first discovered: Chlorovirus , Coccolithovirus , Prasinovirus , Prymnesiovirus , Phaeovirus and Raphidovirus [START_REF] Wilson | The Phycodnaviridae: The Story of How Tiny Giants Rule the World[END_REF]).

Pangenome analysis revealed that current members of Phycodnaviridae can be categorized into four groups. The first group includes Chloroviruses and Prasinoviruses. The second group is Phaeoviruses . The third group is Prymnesioviruses that seems to be closely related to the extended Mimiviridae clade (Mimiviruses and other viruses of amoebae are also called Megaviridae). Raphidovirus appears to be independent of the other three groups, being positioned between the Coccolithovirus and the Megaviridae-phycodnaviruses [START_REF] Maruyama | Evolution and Phylogeny of Large DNA Viruses, Mimiviridae and Phycodnaviridae Including Newly Characterized Heterosigma akashiwo Virus[END_REF].

Haptophyte which presents the alternation between a non-motile diploid (2N) coccolith-bearing phase, and a motile biflagellated haploid (N) cell phase alga with the cells covered by organic non-mineralized scales that do not form coccoliths [START_REF] Paasche | A review of the coccolithophorid Emiliania huxleyi (Prymnesiophyceae), with particular reference to growth, coccolith formation, and calcification-photosynthesis interactions[END_REF][START_REF] Frada | The "Cheshire Cat" escape strategy of the coccolithophore Emiliania huxleyi in response to viral infection[END_REF][START_REF] Morin | Sex as an algal antiviral strategy[END_REF]. Even though haploid and diploid cells may grow and reproduce independently by mitosis, they are likely to be be interconnected through sex and meiosis, although there is no direct observation of sexual reproduction in E . huxleyi [START_REF] Frada | Morphological switch to a resistant subpopulation in response to viral infection in the bloom-forming coccolithophore Emiliania huxleyi[END_REF]).

E. huxleyi can be infected by large DNA viruses from the Phycodnaviridae family, the E . huxleyi virus (EhV) [START_REF] Wilson | Isolation of viruses responsible for the demise of an Emiliania huxleyi bloom in the English Channel[END_REF], one of the primary agents for bloom termination in natural populations of E . huxleyi [START_REF] Schroeder | Virus Succession Observed during an Emiliania huxleyi Bloom[END_REF]. During the haploid phase in the "naked" biflagellated state, [START_REF] Frada | The "Cheshire Cat" escape strategy of the coccolithophore Emiliania huxleyi in response to viral infection[END_REF] observed that E . huxleyi appears to be resistant or immune to viral attacks, providing a refuge and a reservoir of haploid cells that can mate, then presumably repopulating new blooms in the diploid phase, since diploid stage cells can be infected [START_REF] Morin | Sex as an algal antiviral strategy[END_REF]. Furthermore, [START_REF] Frada | The "Cheshire Cat" escape strategy of the coccolithophore Emiliania huxleyi in response to viral infection[END_REF] suggested that infection by EhV may trigger meiosis, or at least induce the shift from diploid to haploid populations.

Under the Red Queen dynamics, the rapid evolution of algal immunity to viruses might arise after production of resistant genotypes by sexual recombination, thus maintaining the ecological status quo [START_REF] Morin | Sex as an algal antiviral strategy[END_REF]. However, the observation of the same genetically distinct strains of diploid cells recurring in different blooms of E. huxleyi and the persistence of viruses in natural environments over multiple years in the North Atlantic, the lack of biogeographic structuring in the infectivity patterns, and in general the maintenance of elevated growth rate and high infectivity is inconsistent with classic Red Queen dynamics, which in this case would produce genetically different resistant strains over time, and with each strain being decimated by viruses that evolved mechanisms that circumvent the resistant strains. Since viruses infect and lyse only the diploid calcifying phase, while the non-calcifying haploid phase is resistant, the alga effectively becomes "invisible" to viral attacks [START_REF] Frada | The "Cheshire Cat" escape strategy of the coccolithophore Emiliania huxleyi in response to viral infection[END_REF] suggested the term "Cheshire Cat dynamics" for this phenomena, the decoupled interaction between haploid algae and viruses. Under the same influence from Lewis Carroll's Alice and the Red Queen, it was suggested that a "Cheshire Cat" strategy was taking place here, since in the Alice story, the One of the main descriptive morphological diagnoses of Mamiellophyceae, although not conserved in all genera, and also not unique to this groups of algae, is the presence of organic non-mineralized (primarily polysaccharide) scales, mostly in spider web-like format. These scales cover portions of the cell surface and also the flagella (if present) in the genera Bathycoccus , Mamiella , Mantoniella , and Dolichomastix . Scales are absent in Ostreococcus and Micromonas , while flagella are also lacking in Ostreococcus and Bathycoccus . Some genera, such as Micromonas , Mamiella , Mantoniella , Dolichomastix, Crustomastix and Monomastix possess 1 or 2 flagella ( Monomastix ). Mamiellophyceae cells also have a single but sometimes two chloroplasts, with chlorophylls a and b, and the pigment prasinoxanthin may also be present [START_REF] Wetherbee | The Protistan Cell Surface[END_REF]Marin and Melkonian 2010).

Mamiellales algae, the smallest eukaryotes

The Mamiellales order is represented by the genera Ostreococcus , Bathycoccus and Micromonas , as well as the lesser known relatives Mantoniella and Mamiella that are distributed across several marine environments [START_REF] Vaulot | The diversity of small eukaryotic phytoplankton (≤3 μm) in marine ecosystems[END_REF]. The most well studied genera in this order are Ostreococcus , Bathycoccous and Micromonas . The genus Ostreococcus is found mostly in coastal, and estuarine regions, but some species O . lucimarinus and Ostreococcus sp.

RCC809 have been found in the open ocean [START_REF] Demir-Hilton | Global distribution patterns of distinct clades of the photosynthetic picoeukaryote Ostreococcus[END_REF][START_REF] Treusch | Phytoplankton distribution patterns in the northwestern Sargasso Sea revealed by small subunit rRNA genes from plastids[END_REF][START_REF] Simmons | Abundance and Biogeography of Picoprasinophyte Ecotypes and Other Phytoplankton in the Eastern North Pacific Ocean[END_REF]. Recently Tragin and Vaulot (2019) suggested that a novel Ostreococcus clade, clade E, was the most dominant Mamiellales in some stations sampled during the ocean sampling day project (OSD), from coastal warm temperate stations, and on both sides of the Atlantic and in the Mediterranean Sea. In addition, the ecological distribution of Ostreococcus does not seem to overlap as in O. tauri , a coastal lacustrine species and O. lucimarinus that is more broadly distributed in the open regions of the ocean. The genus Bathycoccus is composed of two cryptic species, exhibiting respectively the reference genome from the strain RCC1105 and a co-assembled single cell genome (from 4 cells) TOSAG39-1. They have identical 18S rRNA sequences but differences in the ITS region and most importantly, divergent genomes [START_REF] Vannier | Survey of the green picoalga Bathycoccus genomes in the global ocean[END_REF]Vaulot et al. 2012). These Bathycoccus are found distributed from coastal to polar waters (RCC1105 was sampled in Mediterranean), while TOSAG39-1 (sampled in the Arabian sea) is more prevalent in tropical and subtropical regions in the Pacific, Atlantic and Indian Oceans, with its occurrence in waters 3 °C warmer on average than B . prasinos RCC1105. [START_REF] Vannier | Survey of the green picoalga Bathycoccus genomes in the global ocean[END_REF][START_REF] Limardo | Quantitative biogeography of picoprasinophytes establishes ecotype distributions and significant contributions to marine phytoplankton[END_REF][START_REF] Simmons | Abundance and Biogeography of Picoprasinophyte Ecotypes and Other Phytoplankton in the Eastern North Pacific Ocean[END_REF]Joli et al. 2017;Tragin and Vaulot 2019). Micromonas is the genus regrouping most species with open ocean species and also some species adapted to polar environments [START_REF] Lovejoy | Distribution, Phylogeny, and Growth of Cold-Adapted Picoprasinophytes in Arctic Seas1[END_REF][START_REF] Balzano | Composition of the summer photosynthetic pico and nanoplankton communities in the Beaufort Sea assessed by T-RFLP and sequences of the 18S rRNA gene from flow cytometry sorted samples[END_REF]Simon et al. 2017), M. bravo, a newly described Mamiellales species appears to be ubiquitous in the environment [START_REF] Foulon | Ecological niche partitioning in the picoplanktonic green alga Micromonas pusilla : Evidence from environmental surveys using phylogenetic probes[END_REF]Simon et al. 2017) and may even outcompete other Micromonas lineages in coastal and warm waters, although it was also suggested to have evolved recently a second thermotype, which occupies an isolated higher latitude, cold water niche [START_REF] Demory | Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean[END_REF]).

The genus Ostreococcus

Ostreococcus is probably the best studied genus from the Mamiellophyceae. This organism is a free-living picoplanktonic species, with cell diameter of ∼0,8-1 μm, with minimal cellular components (one mitochondrion and one chloroplast), showing in culture a relatively fast cell cycle of about 2-3 divisions/day under continuous light [START_REF] Derelle | Life-Cycle and Genome of OtV5, a Large DNA Virus of the Pelagic Marine Unicellular Green Alga Ostreococcus tauri[END_REF]. The first species of Ostreococcus , O . tauri , was discovered in the Thau Lagoon in 1994 in France [START_REF] Courties | Smallest eukaryotic organism[END_REF]Chretiennot-Dinet et al. 1995) and still to date is regarded as the smallest eukaryote.

Mamiellophyceae genomes and transcriptomes

In general, Mamiellales' genomes are small and streamlined, ranging from 13 Mb in O. tauri RCC4221 (Derelle et al. 2006), 15 Mb in B . prasinos (Moreau et al. 2012 ) to 22 Mb in M. pusilla (Worden et al. 2009). About three quarters of the protein encoding genes show similarities to known gene functions while half of the genes show similarities to plant genes. The most probable scenario of genome evolution is that these algae evolved under selective pressure to reduce the genome sizes with consequences such as low numbers of gene families, with some disappearing completely, like flagellar genes in Ostreococcus , and with another likely consequence, that these species might lose some distinguishing morphological characteristics to distinguish between species, even when using molecular and phylogenetic analyses of nuclear type locus ( MT-). In Micromonas and Ostreococcus genomes, Worden et al. (2009) identified 3 subfamilies with RWP-RK motif and one of these families were subdivided into 3 clades encoding shorter Mid-like proteins (MLPs) similar to the C. reinhardtii MID gene: MID, MLPa, and MLPb, all located in their BOC chromosomes. Whereas Ostreococcus tauri RCC4221 an O. lucimarinus carried an MLPa gene, Micromonas commoda (RCC299) carried an MLPb, and there was no MID/MLP genes in M. pusilla (CCMP1545), a pattern that would concur with the hypothesis that these 3 genomes were derived from "minus-equivalent" mating type strains and the fourth from a "plus-equivalent" mating type strain, given the lack of a MID-like gene in this genome. These observations makes the case stronger for the hypothesis of BOCs being a sex-chromosome candidate. In Bathycoccus , the BOC region also shows a lower GC content (42%) compared to the rest of the genome (48%), and whereas most chromosomes share a similar organization with the other Mamiellales, there is lack of collinearity when compared with other BOCs. There is also an over-representation of basic housekeeping functions like primary metabolism, gene expression, photosynthesis and protein transport, and genes are more highly expressed than other genes in the genome (Moreau et al. 2012). Blanc-Mathieu et al. (2017) described a mating type loci in O . tauri strains isolated from a population of O. tauri , MT+ being the opposites from the MTlocated in the reference genome strain RCC4221, that was already suggested of being the minus mating type strain by Worden et al. (2009) given the presence of a MID-like gene from the RWP-RK family. The MTstrain consists of a 650 kb region, while the MT+ is a 460 kb region. The observed spectrum of polymorphism on MT+ strains in the low-GC region of the BOC revealed signs of recombination suppression, a characteristic observed in sex-determining regions in eukaryotes (Ferris et al. 2010;[START_REF] Charlesworth | The status of supergenes in the 21st century: recombination suppression in Batesian mimicry and sex chromosomes and other complex adaptations[END_REF]. The mating type division and thus, the time when both mating type loci started to diverge, is witnessed in orthologous genes with housekeeping functions that are trapped inside this region. The phylogenetic profile of those genes clusters only species bearing the mating type minus ( O. tauri and O. lucimarinus ) being highly divergent from the species

Mating type discoveries in O. tauri genomes

The Small Outlier Chromosome (SOC): roles in host immunity against viruses

Empirical evidence for the hypothesis of the role of SOC in defense against viral attacks was provided in O . tauri, the chronic producer of Ostreococcus tauri virus 5 (OtV5) [START_REF] Yau | A Viral Immunity Chromosome in the Marine Picoeukaryote, Ostreococcus tauri[END_REF], where massive transcriptional change was observed in the SOC in virus-infected cells, showing a correlation between viral resistance and increased rate of spontaneous (or induced) large rearrangements, that may correspond mainly to deletions and duplications in the SOC region. In O . tauri the size increase of SOC may caused by translocation events between these atypical chromosomes, that could alter gene expression, which could have produced adaptive changes, probably reflected in different susceptibilities to Mamiellales viruses [START_REF] Clerissi | Prasinoviruses of the Marine Green Alga Ostreococcus tauri Are Mainly Species Specific[END_REF]. It is not yet known whether or not these chromosomes play similar defensive roles against specific viral pathogens in the other Mamiellales genera Bathycoccus and Micromonas (Moreau et al. 2012). Nevertheless, viral resistance has also been observed in these species against their specific viruses BpV2 ( Bathycoccus prasinos Virus 2) and MpV1 ( Micromonas pusilla Virus1) [START_REF] Thomas | Acquisition and maintenance of resistance to viruses in eukaryotic phytoplankton populations[END_REF]. While high levels of viral susceptibility were not observed in the other Mamiellales genera Mamiella sp. and Mantoniella, (Subirana et al. 2013), it was predicted that if there is a link between SOC and viral interactions, genomes from these Mamiellales species might not present a SOC-like structure (Moreau et al. 2012). Last, to account for the genetic strangeness in SOCs, different authors suggested the apparently alien origin of some genes in these chromosomes occurred by horizontal gene transfer, most probably from bacteria [START_REF] Grimsley | Typical Features of Genomes in the Mamiellophyceae[END_REF] or from viruses (Blanc-Mathieu et al. 2017), and could have yielded the defense against viruses (Derelle et al. 2006;Moreau et al. 2012).

Altogether, Mamiellales genomes reveal ancient divergence and gene content differences, and their small and streamlined genomes probably reflect local biogeographical adaptations and changes in their lifestyle (Jancek et al. 2008;Worden et al. 2009;Piganeau et al. 2011b;Moreau et al. 2012). Therefore, the widespread distribution of these green algae combined with their basal phylogenetic position in the tree of life and their ease of growth in laboratory render these algae interesting for evolutionary studies [START_REF] Bellec | Phylogenetic analysis of new Prasinoviruses (Phycodnaviridae) that infect the green unicellular algae Ostreococcus, Bathycoccus and Micromonas[END_REF].

Despite the progress towards describing the ecological importance of Mamiellophyceae and the breath of genomic data available for the main genera of this group, aspects related to their organismal interactions, especially in the environment, as well as the presence, origin and evolution of sexual interactions and also their interactions with marine viruses still all remain enigmatic.

Dwarfs and giants: symbiosis between Mamiellales algae and Prasinoviruses

Is rather striking that Mamiellales algae, where we find the smallest eukaryotic organisms, could be infected forging symbiosis with some of the largest DNA viruses, from the Prasinovirus from the family Phycodnaviridae. Prasinoviruses are the most abundant genus of NCLDVs in the oceans and probably outnumber eukaryotic organisms in the photic zone [START_REF] Hingamp | Exploring nucleo-cytoplasmic large DNA viruses in Tara Oceans microbial metagenomes[END_REF][START_REF] Clerissi | Prasinovirus distribution in the Northwest Mediterranean Sea is affected by the environment and particularly by phosphate availability[END_REF] were they could reach to two orders of magnitude higher than their hosts in those waters (Bellec et al. 2010). The first prasinovirus characterized was from the host Micromonas pusilla in 1975, the Micromonas pusilla Virus (MPV), during transmission electron microscopy (TEM) observations of natural communities from British Columbia, Strait of Georgia [START_REF] Mayer | A virus which lyses the marine nanoflagellate Micromonas pusilla[END_REF]. Only in 2003, a report of the rapid decline of transient Ostreococcus blooms was hypothesized to be caused by a virus in eastern coast of the USA (O' Kelly et al. 2003).

Three major groups of prasinoviruses are known to infect the most widespread and abundant genera of the Mamiellophyceae: Ostreococcus virus (OV), Micromonas virus (MpV), and Bathycoccus virus (BpV) (Marin and Melkonian 2010;[START_REF] Not | A single species, Micromonas pusilla (Prasinophyceae), dominates the eukaryotic picoplankton in the Western English Channel[END_REF][START_REF] Zhu | Mapping of picoeucaryotes in marine ecosystems with quantitative PCR of the 18S rRNA gene[END_REF].

Their hosts, Mamiellales' algae from the genera Bathycoccus , Micromonas , and Ostreococcus, are prevalent in coastal surface waters (Worden et al. 2009;[START_REF] Demir-Hilton | Global distribution patterns of distinct clades of the photosynthetic picoeukaryote Ostreococcus[END_REF], Vaulot et al. 2012, Tragin and Vaulot 2019) and are an abundant group throughout the oceanic euphotic zone (Worden et al. 2004).

Ostreococcus viruses (OV) demonstrate a tendency of genome expansion for most of their representatives [START_REF] Filée | Genomic comparison of closely related Giant Viruses supports an accordion-like model of evolution[END_REF].

Marine viruses can significantly influence and control the life and death of their host species as in the termination of algal blooms [START_REF] Bratbak | Viral mortality of the marine alga Emiliania huxleyi (Haptophyceae) and termination of algal blooms[END_REF][START_REF] Castberg | Microbial population dynamics and diversity during a bloom of the marine coccolithophorid Emiliania huxleyi (Haptophyta)[END_REF]. In Micromonas about 2-10% of cells per day were lysed by viruses in the gulf of mexico [START_REF] Cottrell | Dynamics of lytic virus infecting the photosynthetic marine picoflagellate Micromonas pusilla[END_REF] and in a mesocosm experiment in Raunefjorden, Norway, it was estimated that up to 34% of host is lysed by MpV [START_REF] Evans | Direct estimates of the contribution of viral lysis and microzooplankton grazing to the decline of a Micromonas spp. population[END_REF]. Prasinoviruses show high levels of specificities to their hosts, as in Ostreococcus and Micromonas viruses, tending to infect related host strains [START_REF] Derelle | Life-Cycle and Genome of OtV5, a Large DNA Virus of the Pelagic Marine Unicellular Green Alga Ostreococcus tauri[END_REF][START_REF] Clerissi | Prasinoviruses of the Marine Green Alga Ostreococcus tauri Are Mainly Species Specific[END_REF][START_REF] Sahlsten | Seasonal abundance in Skagerrak-Kattegat coastal waters and host specificity of viruses infecting the marine photosynthetic flagellate Micromonas pusilla[END_REF][START_REF] Sahlsten | Vertical distribution of virus-like particles (VLP) and viruses infecting Micromonas pusilla during late summer in the southeastern Skagerrak, North Atlantic[END_REF].

Prasinovirus in Metagenomes

Using culture-independent metagenomic analyses, genomes from prasinovirus-related viruses, the Yellowstone Lake Phycodnavirus (YSLPVs), were discovered in the freshwater Yellowstone Lake [START_REF] Zhang | Four novel algal virus genomes discovered from Yellowstone Lake metagenomes[END_REF]. Also using the same technique, the sequence assembly for metagenomic datasets, Chen et al. ( 2018) described a complete genome from another Prasinovirus-related novel large Phycodnavirus, DSLPV1, from freshwaters of the Dishui lake in Shanghai, China. Currently, this viral genome represents the closest freshwater relative of marine Prasinovirus genomes. The genome seems to be more closely affiliated with the marine Prasinoviruses rather than with the freshwater-originated Prasinovirus-related YSLPVs. These authors speculate that the host of DSLPV1 may be some freshwater Ostreococcus related algae, given that the closest homologues of several viral genes in DSLPV1, were present in the O. lucimarinus , O. tauri genomes, and Mamiellophyceae related contigs were the most abundant in the algae-related contigs identified in the Dishui lake metagenomic dataset.

Other types of virus in Mamiellales

The majority of the described algal viruses consists of double stranded DNA molecules, with few examples of exceptions, such as the single stranded RNA viruses (ssRNA) from the Raphidophyte Heterosigma akashiwo [START_REF] Tai | Characterization Of HARNAV, a single-stranded RNA virus causing lysis of Heterosigma akashiwo (Raphidophyceae)1[END_REF] and the Dinoflagellate Heterocapsa circularisquama [START_REF] Tomaru | Isolation and characterization of two distinct types of HcRNAV, a single-stranded RNA virus infecting the bivalve-killing microalga Heterocapsa circularisquama[END_REF]) but also single stranded DNA viruses (ssDNA) from

Introduction

Sex evolved very early at the dawn of eukaryotic life (Goodenough and Heitman 2014;Dacks and Roger 1998) but for a long time, many microbial eukaryotes have been assumed to lack sexual stages [START_REF] Smith | The evolution of sex[END_REF]Tibayrenc et al. 1990;Tekle et al. 2017). Nowadays, sex is regarded as a ubiquitous and ancestral feature of eukaryotes (Speijer et al. 2015) and is well-documented and pre dicted to occur in many protist lineages (Sager and Granick 1954;[START_REF] Suda | Evidence for Sexual Reproduction in the Primitive Green Alga Nephroselmis Olivacea (prasinophyceae)1[END_REF][START_REF] Chepurnov | Experimental studies on sexual reproduction in diatoms[END_REF]Ramesh et al. 2005;[START_REF] Schurko | Using a meiosis detection toolkit to investigate ancient asexual "scandals" and the evolution of sex[END_REF]Weedall and Hall 2015;[START_REF] Wood | Genetic Evidence for Sexuality in Cochliopodium (Amoebozoa)[END_REF]). Nevertheless, direct observation of sexual interactions for many unicellular eukaryotic species is still lacking (Speijer et al. 2015), as in the case of the planktonic green algae of the class Mamiellophyceae (Grimsley et al. 2010).

This cosmopolitan algal class contains the smallest known free living photosynthetic eukaryotes with cell diameters smaller than 1 µm (Chretiennot-Dinet et al. 1995), and represents an early branch within the green lineage (Marin and Melkonian 2010). Within Mamiellophyceae there are three established orders: Mamiellales, Dolichomastigales and the freshwater Monomastigales (Marin and Melkonian 2010). While Mamiellales contain the best characterized cosmopolitan species (Tragin and Vaulot 2018), Dolichomastigales display a higher genetic diversity in the environment (Monier et al. 2016) and the environmental distribution and ecology of Monomastigales is still obscure. Mamiellales encompass the genera Bathycoccus , Ostreococcus and Micromonas , for which complete genome sequences are available in seven species (Palenik et al. 2007) (Moreau et al. 2012) (Blanc-Mathieu et al. 2014) (van Baren et al. 2016) (Yau et al. 2019). However, genomic data for Dolichomastigales and Monomastigales remain scarce, with notable exceptions such as the chloroplast genome from the freshwater Monomastix sp. (Turmel et al. 2009) and transcriptomes from the MMETSP and 1KP projects (Keeling et al. 2014) (Matasci et al. 2014) Meiosis, a critical and fundamental step in eukaryotic sex, could be cryptic in other Mamiellophyceae. Indeed, genes encoding for proteins involved in meiosis have also been described in O . lucimarinus (Palenik et al. 2007), Micromonas pusilla , M . commoda (Worden et al. 2009), and in Bathycoccus spp. metagenomes from the Arctic (Joli et al. 2017). Nevertheless, no complete sexual life cycle nor diploid stage has yet been reported for any Mamiellophyceae to our knowledge.

In many protists, sexual interactions are governed by mating types ( MT s) loci, sex-determining regions that possibly evolved before differentiation in gamete size and separation of sexes [START_REF] Hoekstra | The evolution of sexes[END_REF][START_REF] Parker | The origin and maintenance of two sexes (anisogamy), and their gamete sizes by gamete competition[END_REF][START_REF] Geng | Evolution of Sexes from an Ancestral Mating-Type Specification Pathway[END_REF]. This genetic make-up controls sexual development and gamete formation, and generally each partner can only mate with an opposite or different mating type [START_REF] Geng | Evolution of Sexes from an Ancestral Mating-Type Specification Pathway[END_REF]). Several hypotheses have been proposed to explain the maintenance of mating types: the avoidance of inbreeding (no self-fertilization) (Charlesworth and Charlesworth 1979;Hadjivasiliou et al. 2016); the evolution of uniparental inheritance of cytoplasm [START_REF] Hastings | Population genetic aspects of deleterious cytoplasmic genomes and their effect on the evolution of sexual reproduction[END_REF] or as suggested by [START_REF] Hoekstra | On the asymmetry of sex: Evolution of mating types in isogamous populations[END_REF] and expanded by Hadjivasiliou and Pomiankowski (2016), for ecological reasons, where cell signalling allows more efficient partner recognition and pairing in a MT -specific manner by the production of recognition/attraction molecules and their receptors.

In green algae (Chlorophyta), sex-determining regions are well-described in Volvocales, including the Volvox , Gonium and Chlamydomonas genera among others (Ferris and Goodenough 1997;Ferris et al. 2010;[START_REF] Hamaji | Sequence of the Gonium pectorale Mating Locus Reveals a Complex and Dynamic History of Changes in Volvocine Algal Mating Haplotypes[END_REF][START_REF] Geng | Evolutionary divergence of the sex-determining gene MID uncoupled from the transition to anisogamy in volvocine algae[END_REF]. In Chlamydomonas , sex-specific developmental programs are controlled by biallelic mating type loci MT+ and MT-, located near the telomeric region of chromosome 6 [START_REF] Ferris | Genetic structure of the mating-type locus of Chlamydomonas reinhardtii[END_REF]De Hoff et al. 2013). The MID gene, the master sex controller gene which initiates the sex cycle, is a transcription factor of the RWP-RK family located on the MTlocus ( Nishimura et al. 2017 ). The MT locus spans a 200-400 kb size region and shows a high degree of gene rearrangements, as well as recombination suppression. However, analysis of shared genes between both MT+ and MTsuggested "cryptic recombination" via gene conversion events, as genetic divergence between some genes located within the MT regions was similar to the one of genes located on autosomal chromosomes (De Hoff et al. 2013). The common genetic basis of the sex-determining systems within Volvocales comprises two sex-specific genes, the MID ( MT-/male) and the gamete recognition factor FUS1 ( MT+ /female) [START_REF] Hamaji | Anisogamy evolved with a reduced sex-determining region in volvocine green algae[END_REF]. These two genes are the only conserved genes within both the isogamous (genetic sex differentiation only with same gamete size) and anisogamous (male and female differentiation) species in the Volvocales lineage.

Recently, a population genomic analysis provided evidence of a candidate ~500 kb long mating type locus in O . tauri (Blanc-Mathieu et al. 2017). O . tauri RCC4221 was suggested to represent the candidate minus mating type (hereafter MT -) together with O . lucimarinus CCE9901, because of the presence of a gene encoding for a RWP-RK transcription factor (Worden et al. 2009), from a related gene family of the "sex determining gene" (minus dominance MID ) of minus mating type loci in Volvocales algae (Ferris and Goodenough 1997;[START_REF] Umen | Evolution of sex and mating loci: an expanded view from Volvocine algae[END_REF] ). The candidate opposite mating type (the plus type, hereafter MT+ ) was identified from the genome analysis 12 O . tauri strains which displayed a high genetic divergence with O . tauri RCC4221 over this ~500 kb region and lacked any gene containing a RWP-RK domain (Blanc-Mathieu et al. 2017). Phylogenetic analysis of five genes with/having orthologous copies in the two mating type regions revealed that O . tauri MTand MT+ strains clustered with different Ostreococcus species of the same mating type, suggesting that mating type differentiation predates speciation within Ostreococcus . The polymorphism spectrum on MT + loci in O. tauri was consistent with recombination suppression in this low GC region of chromosome 2, O. tauri 's Big Outlier Chromosome (BOC) a large chromosome with unique structures found in all Mamiellales genomes (Moreau et al. 2012). Despite no morphological differences between different Ostreococcus species (Subirana et al. 2013), the four sequenced Ostreococcus species have highly divergent genomes: the 72% average amino-acid identity of orthologous genes between O . tauri and O . lucimarinus is similar to the amino-acid identity between chicken and human orthologous genes (Jancek et al. 2008). Therefore MT+ and MTare expected to be remarkably ancient in Ostreococcus . In addition to a lower GC content, this large candidate MT region exhibits several remarkable properties: a high proportion of species-specific genes, a lack of synteny of orthologous genes, a different codon usage compared to genes located on standard chromosomes, and a higher gene expression level (Moreau et al. 2012;Worden et al. 2009). GC decrease is consistent with recombination suppression, and the role of the BOC in the sexual cycle had been suspected since the analysis of the first available genome sequence (Derelle et al. 2006).

Here, we investigated the architecture, composition and phylogenetic profiles of the MT+ and MTloci of O . tauri to unfold the evolutionary history of this region in Mamiellales genomes. The analyses of the MT+ and MTshared versus specific gene families enabled to define the core conserved set of genes within candidate MT loci in Mamiellales. This information was then leveraged to identify the opposite mating types from additional Mamiellophyceae sequence data, and thus trace back the age of this mating type in the green lineage.

First, we defined a " MT specific" GF class containing genes shared only by species from the same Ostreococcus MT , but absent in the opposite Ostreococcus MT . Second , we defined a "core MT " GF class, which contains GFs exclusively composed of genes located inside the boundaries of all candidate MT regions in all sequenced Mamiellophyceae (supplementary table S1 , Supplementary Material online ) . A third GF class, also contained genes shared by both Ostreococcus MT loci, but that could be absent from the MT regions in some Mamiellales species (Shared MT GFs, non-core). The fourth class of GFs contains genes located inside O .

tauri MT locus but also genes located on standard chromosomes (GFs extending outside MT ).

The remaining GFs, that are present in only one O . tauri MT locus but also in other Mamiellales genomes, or that contains highly divergent genes, for which alignments are too short to generate phylogenies, and singleton genes (except the MTspecific GFs ) were not retained for analysis.

The MT specific GF contained the smallest number of genes; 14 and 2 genes for MTand MT +, respectively. These GFs are expected to contain the genes involved in sex determination and functional control associated to each MT . Functional annotation revealed that while the majority of these genes encode for hypothetical proteins and/or do not have any predicted function, the MTspecific GFs contain, as previously reported (Worden et al. 2009) gene with a RWP-RK domain (ostta02g01710). Additionally, 3 MT -specific genes are predicted to encode for a polyketide synthase protein (ostta02g00160, ostta02g00180, ostta02g00710), while the other specific genes are hypothetical proteins with no gene ontology associated, ne gene (ostta02g00990) possesses a SRP-dependent cotranslational protein targeting to membrane.

Within the MT + specific GFs, there are only 2 genes that encode for hypothetical proteins with gene ontology associated with mismatch repair, protein binding and transport ( supplementary table S4 , Supplementary Material online).

Apart from the MT specific genes, less than 10% of genes in all MT loci of all seven Mamiellales genomes ("core MT GF", Table 1). Functional annotation of these genes are related to housekeeping functions, such as DNA and ATP binding, transcription, glycolipid biosynthesis, protein transport, and RNA methylation, although there is no obvious relation to the cell cycle or mating (supplementary table S3 , Supplementary Material online ) . The two Genes of the same GFs as MT -genes were located on diverse autosomes (fig. 1B), and this patchy distribution was also observed for GFs for gene members extending outside the MT+ (fig. 1C). This provides evidence for past gene translocations between many autosomes and the MT regions.

To search for evidence of evolutionary strata, regions of the MT where genes can be clustered by genetic divergence (measured by the substitution ra te) we computed the rate of synonymous substitution (Ks) [START_REF] Tzeng | Comparison of three methods for estimating rates of synonymous and nonsynonymous nucleotide substitutions[END_REF]) of the genes belonging to the 69 shared MT GFs on MTand MT+ in O. tauri (shared GFs). Only 22 gene pairs had a Ks < 1, of which only 2 genes were adjacent on both the MT+ and MT-(supplementary table S2 , Supplementary Material online ). This is consistent with a scenario of independent gene conversion events between the two MT s, except for one event spanning over two genes. Interestingly, within these recently diverged genes only 2 pai rs were adjacent, but only in one of the mating types ( MT+ ).

This suggests that the source, or the destination, of the conversion events between MT s tends to span several kb. In any case, these observations are not consistent with any indication of strata [START_REF] Lahn | Four evolutionary strata on the human X chromosome[END_REF], defined as discrete regions containing orthologous genes with similar substitution rates, along the large MT regions of O. tauri .

Phylogenetic insights into evolutionary dynamics of mating types

To trace back the age of the insertion of a gene within the MT region, we screened the topology of each GF phylogenetic tree to assess whether they supported the speciation history within Ostreococcus (no mating type separation), or the existence of an ancient mating type that predated the speciation event. The number of GFs for each topology is displayed in fig. 2.

Interestingly, this dual phylogenetic signal (mating type separation and no-separation) is mirrored by a dual GC3 content signature of the genes: genes belonging to GF supporting ancient mating type origin have a significantly lower GC3 content than genes whose evolutionary history is concordant with the speciation history of the genus (fig. 2). Of the 23 MT GF core genes (supplementary table S3 , Supplementary Material online ) , that were located within candidate MT regions in all Mamiellales genomes, the majority of GF phylogenies phylogenetic spread of the transcriptomes spanned from the early divergent freshwater species These phylogenetic analysis thus confirmed a shared ancestry of some genes, reflecting an ancient divergence of two MT regions rather than a speciation event. This led us to conclude that O . lucimarinus strain RCC2572 and O . mediterraneus strain BCC118000 (MMETSP0929 and MMETSP0939 respectively) are of the opposite mating types from the strains for which the reference genome is available. This extended the evidence of the existence of two mating types in two Ostreococcus species in addition to O . tauri.

encode for a polyketide synthase protein. In Chlamydomonas , one polyketide synthase protein is essential to diploid zygote development during their sexual cycle, while not playing any role during the haploid state [START_REF] Heimerl | A giant type I polyketide synthase participates in zygospore maturation in Chlamydomonas reinhardtii[END_REF]. Second, phylogenetic signatures of core GFs provided evidence of a MT + and MT -strain in two additional Ostreococcus species: O . mediterraneus and O . lucimarinus . This is because of the divergence time of the MT + and MTregions, genes on this region cluster by MT and not by species. This sub-clustering could also be observed between strains from M . commoda, strains from, of the, comparing the actin, b-tubulin genes and 18s rRNA phylogenetic topology and distance in M . commoda transcriptomes (fig. 7 and supplementary table S11, Supplementary Material online), which confirm their taxonomic affiliation as bona fide M . commoda strains, and enables to reject the hypothesis that these strains belong to a cryptic species complex, that could also produce distant sub-clustering within a lineage, given that we observed two divergent sub clusters in the core MT GF phylogeny. Third, insights into the dynamic of the MT loci. One fascinating feature of sex chromosomes and mating types, is that they may be organized as multiple discrete regions, were genes can be clustered by genetic divergence (measured by the rate of non-synonyms substitutions), defined as "evolutionary strata". In some cases, the divergence has been reported to decrease with distance from sex-determining genes and sexual compatible loci (Branco et al. 2017). In humans, where strata were first described by [START_REF] Lahn | Four evolutionary strata on the human X chromosome[END_REF], it was suggested that suppressed recombination was initiated in one region (stratum) and later expanded in discrete steps, by strata, through additional chromosomal inversions, which were known to suppress recombination in mammalian chromosomes. Only a few X-Y sequence similarities persisted, and these alleles are orderly stratified by age in the X chromosome but scrambled in the Y. Although strata have been observed in several vertebrates and plants [START_REF] Bachtrog | Sex Determination: Why So Many Ways of Doing It[END_REF][START_REF] Coelho | UV Chromosomes and Haploid Sexual Systems[END_REF]), it appears that they are not a common feature of algal mating types and sex chromosomes. Indeed, we found no evidence of evolutionary strata in Ostreococcus MT s, as nor ancient nor recent genes do cluster on any of the MT s. This may be due to their ancient divergence, erasing strata signals, or to a limited expansion dynamic, as suggested in the UV chromosomes of the brown algae Ectocarpus [START_REF] Ahmed | A Haploid System of Sex Determination in the Brown Alga Ectocarpus sp[END_REF]). Nevertheless, it has been suggested that two internal syntenic blocks were acquired more recently in an ongoing stratification process in Volvox MT s

The full set of coding sequences (CDS) from eight Mamelliales species (supplementary the mating type region of either Ostreococcus tauri RCC4221 or RCC1115, the GF they were part of was retrieved. Based on the location of the GF members (chromosome/scaffold and coordinates), a 'BOC signal' value was then computed for every species in which the GF was represented. This value corresponds to the fraction of members being located on the mating type region (for the given species-GF combination) and was used to filter the list of candidate mating type GFs.

For every retained GF, protein sequences were aligned using MAFFT version 7.187 [START_REF] Katoh | MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability[END_REF] ) (L-INS-i alignment method with 1000 iterative refinement maximum). The multiple sequence alignments (MSAs) were edited using multiple filters on both sequences and positions, following the procedure described by [START_REF] Proost | PLAZA: A Comparative Genomics Resource to Study Gene and Genome Evolution in Plants[END_REF]. Briefly, highly divergent and partial sequences were filtered out, and positions containing gaps in minimum 10% of the sequences or containing potentially misaligned amino acids (based on the median BLOSUM62 value of all the residue pairs at that position), were removed. A minimum length cutoff was also applied to the edited MSA: the edited MSA had to at least be 50 AA long, otherwise it was ignored. In case the original unedited MSA was shorter, this length was used as cutoff instead. Finally, we kept only MSAs with at least alignment 50% of AA identity in half of the sequences of the MSA.

Gene family clustering and phylogeny

For each GF MSA that passed our filtering criteria, Maximum Likelihood (ML) phylogenetic trees were built using IQ-TREE version 1.6.5 [START_REF] Nguyen | IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies[END_REF] under the best amino acid substitution model as selected by ModelFinder [START_REF] Kalyaanamoorthy | ModelFinder: fast model selection for accurate phylogenetic estimates[END_REF] ),

chosen among a set of potential models (JTT, LG, WAG, Blosum62, VT, and Dayhoff).

Empirical amino acid frequencies were calculated from the data and rate heterogeneity across sites was accounted for using the FreeRate model [START_REF] Yang | A space-time process model for the evolution of DNA sequences[END_REF] . Branch support was estimated using ultrafast bootstrap approximation (UFBoot) [START_REF] Hoang | UFBoot2: Improving the Ultrafast Bootstrap Approximation[END_REF]) with 1,000 bootstrap replicates.

Identical alignment, MSA editing, and phylogenetic tree building procedures were used when sequences from external sources (e.g. transcripts from MMETSP samples) were considered. The divergent gene removal criterion was however not used to filter out these sequences from the MSAs, as it is based on the results of the all-against-all protein sequences similarity search that was performed using data from the eight reference species (table 1) only.

Additionally, when investigating the molecular phylogeny of the 18S rDNA genes, the scoring matrix used to filter out positions was replaced by the EDNAFULL matrix, and IQ-TREE's

ModelFinder Plus option (-m MFP) was used to select the best DNA substitution model.

GF Phylogenetic tree classification

Manual inspection of the MT GF trees was performed using Geneious version 10.0.5.

Ultrafast bootstrap support and topology type were examined, and we counted the number of times that species shown separation (clustering) by mating type or according to their taxonomic classification (by species).

Searching for homologs in publicly available transcriptomes

Sequences of core MT GF members were used as queries to search for homologs in Mamiellophyceae transcriptomes (33 transcriptomes transcriptomes (1084, 1327, 1387, 1393, 1400, 1401, 1402, 1403, 1404) and Mantoniella MMETSP transcriptomes (1106, 1468) were performed as previously described for the reference genomes. The presence/absence matrix of each informative orthologous group against the transcriptomes was generated using the ggplot2 package [START_REF] Wickham | ggplot2: Elegant Graphics for Data Analysis[END_REF]) in R (http://www.R-project.org/). Circular plots (fig. 1) were generated with the package "circlize) [START_REF] Gu | circlize implements and enhances circular visualization in R[END_REF] ) also in the R environment.

To validate and elucidate each MMETSP transcriptome's taxonomic affiliation, we downloaded Mamiellophyceae 18S rRNA sequences from reference genomes in GenBank, the SILVA database [START_REF] Quast | The SILVA ribosomal RNA gene database project: improved data processing and web-based tools[END_REF], and Micromonas spp. sequences provided in Simon et al.

(2017) (supplementary table S7, Supplementary Material online). Transcriptome contigs with hits against our 18S rRNA database were extracted with blastn (maximum e-value 1e-5) and 18S rRNA sequences were predicted using RNammer [START_REF] Lagesen | RNAmmer: consistent and rapid annotation of ribosomal RNA genes[END_REF]. A Maximum likelihood phylogeny was built using IQ-TREE and following each clustering of this Mamiellophyceae reference tree (rooted in Monomastix spp.), transcriptomes were tentatively classified according to a species clustering (supplementary fig. S8, Supplementary Material online). Phylogeny indicated that MMETSP transcriptomes matched their species classification, and transcriptomes from novel Micromonas species as M. polaris and M. bravo were designated using the data and new classification of Simon et al. (2017).

Virus-host coexistence in phytoplankton through the genomic lens

Sheree Yau Nucleo-cytoplasmic large DNA viruses (NCLDV) are estimated to be present at 10 4 •mL -1 in the photosynthetic zone (3), a large proportion of which are prasinoviruses, a monophyletic group known to infect Mamiellophyceae, a class of cosmopolitan marine picophytoplankton ( 4), which can be dominant primary producers in coastal areas (5).

Unlike bacteriophages that may integrate into their hosts as prophages and develop complex lysogeny-lysis switch strategies (6), by which the prophage is excised from the host genome and whose transcription induces cell lysis, all known NCLDV infecting unicellular organisms replicate by cell lysis (7). Nonetheless, acquisition of viral resistance after initial viral lysis has been reported in several phylogenetically diverse microalga-NCLDV populations, which displayed continuous production of infective viruses (8). Here, we define as "coexistence" of microalgae and viruses the situation where infective viruses are produced by healthy microalgal cultures grown from one single cell, and are thus isogenic except for the presence of spontaneous mutations. The process allowing a sustained virus production in such isogenic microalgal cultures has remained unsolved.

Virus and microalga coexistence has been previously reported in the freshwater green alga Chlorella variabilis N64A infected by PBCV-1, and this phenotype was coined a "carrier" state (9). Coexistence was also observed in the haptophyte Emiliania huxleyi upon infection by

EhV-99B1 over 12 days (8), and subsequently in the marine Mamiellophyceae picoalga

Ostreococcus tauri upon infection by OtV5 over 18 days (10). More recently, a study of the population dynamics of Chlorella variabilis and PBCV-1 (11) reported stable coexistence evolved after 30 days post-infection, which was maintained until the end of the experiment 45 days later.

Ostreococcus and their prasinoviruses represent ecologically relevant cultivable microalga-NCLDV model systems for focused study of host-virus interaction mechanisms and dynamics (12). Ostreococcus mediterraneus is the most recently described species and gene phylogeny of the 18S rRNA indicated it is the earliest branching member of the Ostreococcus genus (13). The analysis of the complete genome sequence of O. mediterraneus (strain RCC2590) surprisingly revealed the sequence of a novel prasinovirus, hereafter named OmV2

for Ostreococcus mediterraneus Virus 2. Because the DNA extraction was performed shortly after the environmental sampling of the strain and because subsequent inspections of the culture revealed the presence of infective OmV2 particles for over a decade, we concluded that this microalga-NCLDV system was isolated as a coexisting system, rather than upon the selection of resistant cells after an initial lytic event. We investigate the evolutionary history of this system by whole genome analysis, and the mechanisms underlying viral production by experimental evolution. Last, mathematical modeling of host-virus coexistence as a resistant-susceptible phase switch in the host allows us to explain the observed microalga-virus dynamics.

Results

Production of virions is the consequence of lysis of a subpopulation of microalgae

Population dynamics of microalgal cells and OmV2 in culture was followed over two weeks. The logarithm of microalgal concentration, C, increases linearly with time, t, in RCC2590 cultures (Figure 1A, ln(C)= 0.557xt+7.559, R 2 =0.94). Virus concentration was estimated by flow cytometry and by plaque assay, which measure the total number of DNA containing particles in the culture medium and the number of infectious viruses, respectively. Despite variation in the estimation of the number of viruses between replicates and between the two methods, the number of viruses increases with the number of microalgae, providing evidence of continuous production of viruses in culture.

Susceptible (S) cells derive from resistant (R) cells and vice versa

In order to validate the existence of a switch by which S phenotypes could be generated by R cells within isogenic cultures, we performed experimental evolution. First, we established a clonal culture line that was free of viruses by diluting the original OmV2-producing RCC2590 culture to a single cell. This parent line (hereafter ML for "mother line") was confirmed to be virus-free by PCR screening for OmV2. The ML was not lysed after re-addition of purified OmV2, showing the ML remained virus-resistant. Furthermore, this demonstrated that uninfected individual cells were in the original RCC2590 culture that could be physically separated from OmV2. Second, the virus-free ML was used to generate hundreds of clonal cultures, again from a single cell, in four independent tests. As the phenotype at the level of a single cell cannot yet be determined, we screened these newly cloned cultures for susceptibility to OmV2 after 7 days of growth; thus, the phenotype of the majority of the cells in culture would reflect the phenotype of the starting cell. In the first test, the ML was repeatedly cloned via single-cell bottlenecks every two weeks for 1 year in multiple lines as part of a mutation accumulation experiment (15) in which 3 out of 24 independent lines were visibly lysed upon addition of OmV2. To determine if S phenotypes could evolve over short time periods, three independent experiments were performed where the ML was sub-cloned once by end-point dilution to generate a total of 204 clonal cultures, and tested for susceptibility to OmV2. Visual inspection revealed no lysis in 159 clones while 45 clones lysed with addition of OmV2. This demonstrated that cultures containing a majority of S cells evolved from a single R cell, at a 12.5% to 22% frequency.

To test whether cultures containing a majority of S cells similarly could regenerate an R phenotype, the three independent S lines from the first mutation accumulation experimental evolution study were exposed to OmV2. Infected susceptible cultures showed a sharp decrease in cell concentration in the first 15 days, consistent with a lytic event, dropping as low as 167 cells•mL -1 , after which cultures recovered and cell concentrations reached that of uninfected controls (Supplementary Figure S1). These cultures subsequently showed no visible lysis when re-challenged with OmV2, demonstrating that S cultures can reliably switch to an R state.

Exposure to OmV2 was performed independently a second time on 24 S lines and confirmed systematic resistance acquisition.

What is the genomic signature of the R to S switch?

The three S lines, S1, S2 and S3, obtained from the mutation accumulation experimental evolution study were maintained in batch culture and intermittently tested for susceptibility to OmV2. Viral lysis was observed at each test, confirming that these cultures retained a majority of susceptible cells. Pulsed Field Gel Electrophoresis (PFGE) karyotype analysis of the ML and three S lines revealed a visible size reduction of 95-435 kb in one chromosome, while no difference in karyotype could be observed in the OmV2-resistant ML, which remained unchanged from the OmV2-producing original RCC2590 (Figure 2). Hybridization using specific probes designed from the complete genome sequence identified the chromosome with a reduced size to be the 'Small Outlier Chromosome' (SOC) of O. mediterraneus . The term SOC was coined to describe a chromosome found in all Mamiellales genomes sequenced so far, including Ostreococcus (16), Micromonas (17) and Bathycoccus (18), due to its modest size (< 300 kb), as well as its lower GC content, gene density, and expression rate as compared to the other chromosomes.

To determine if a change in SOC size was exclusive to an R to S switch, we karyotyped a selection of 10 lines from the mutation accumulation experiment that remained R after passage through single-cell bottlenecks. R lines showed variation of ±5 kb in the size of the SOC compared to the ML (Supplementary Figure S2). To determine if S to R changes were also associated to a SOC size switch, three S lines that had regenerated the R phenotype after reintroduction to OmV2 (S to R) were karyotyped, and no visible karyotype change could be observed (Supplemental Figure S2). Altogether this supports there being minor size variation in the SOC in R lines, a large reduction in SOC size linked only to the R to S switch and no systematic visible SOC change linked to an S to R switch.

One susceptible line, S1, was selected for long read genome re-sequencing to elucidate the changes involved in the R to S switch. This line was chosen as it had the smallest deletion in the SOC and could show the smallest change linked to a switch in phenotype. Resequencing showed that 58 kb was deleted from one of the extremities of this chromosome (Figure 2). The SOC comprised a mosaic of short repeated sequences, mainly of intrachromosomal origin, with some contributions from other chromosomes. As a consequence, the deleted fragment was a pastiche of redundant SOC sequences, with only 7 genes deleted that were not found elsewhere on the SOC corresponding to 4,323 bp of coding sequence (Figure 2). Three of the unique deleted genes encoded proteins with unknown functions. Those with putative functional matches included a nucleotide diphosphosugar transferase, an esterase-domain-containing family, transmembrane-domain containing protein and an RNase H1 related to retrotransposases.

Mathematical modeling of S-R switch

To investigate the consequences of such a phase switch on the microalga and virus population dynamics, we set up a host-virus interaction model of this system (Figure 3A). In the absence of viruses, this model predicts the exponential growth typically observed in microalgae populations (Figure 3B). The virus-free population growth rate converges toward an asymptotic value; λ f ree = 2 3B. When the virus is introduced, the population size drops as S cells are eliminated from the population (Figure 3A), but only until the R cells, which were previously produced by the switch of S cells, take over the population (Figure 3B). During this transitory stage that only lasts for a few days, the S/R ratio changes and converges toward , which for small values of , ) e /(1

S -e S e S
indicates that R cells dominate the population. The dynamics then enters a second asymptotic stage where the infection is maintained because R cells produce S cells that sustain the viral population (Figure 3A). The growth rate of such infected population quickly converges to; ≈B λ inf and the proportion of virus, V, to microalga, M (M=S+R), can then be approximated by :

V M ≈ v S a R e S 1-e S
The proportion of microalga relative to viruses is then defined by the growth rate of R microalga, the burst size (v S ) and the switch rate from R to S (e S ). Numerical fit of model behaviour to observations of Figure 1 provides indirect estimates of e S between 0.1 to 0.2 and v S between 5 to 30, in accordance with the expected range of biological values in this system.

(Supplementary Figure S4) and from 2,161 single copy Mamiellales orthologues placed O. mediterraneus at the earliest diverging branch within the Ostreococcus genus (Figure 4), consistent with 18S rDNA phylogeny (13). Protein families gained, lost or expanded were retrieved in O. mediterraneus by comparative protein family analysis on the fully sequenced Mamiellales genomes. This showed all Ostreococcus species have lost 261 of the 5096 protein families present in all Mamiellales (Figure 4), which represent probable ancestral Mamiellales functions and thus reflect the general trend of genome reduction in Ostreococcus (Table 1).

Nonetheless, O. mediterraneus has retained relatively more of these ancestral protein families, of which 72 are uniquely present in O. mediterraneus and lost in the other Ostreococcus species.

The lower genomic GC content of O. mediterraneus as compared to other Ostreococcus species, raised the question of whether it descended from a high GC-content ancestor and experienced a shift towards a lower GC composition, or whether it descended from a low GC-content ancestor and that an increase in GC occurred in the rest of the Ostreococcus clade.

To discriminate between these two alternative hypotheses, we inferred the ancestral genomic GC content for all ancestors of the species tree using ancestral sequence reconstruction techniques.

Because current GC-contents vary between 0.5 and 0.65, we reconstructed ancestral sequences with a non-homogeneous codon substitution model to allow each lineage to vary in global nucleotide compositions. This analysis showed that the last common ancestor of the Ostreococcus clade had a GC-content of ~0.57, similar to that of O. mediterraneus , and lower than that of O. tauri , O. lucimarinus and Ostreococcus sp. RCC809 (~0.60) (Figure 4). This global trend is consistent across all codon positions, although to a much lesser degree for the highly constrained second codon position (Supplementary Figure S5). This genomic GC content increase occurred twice within Mamiellophyceae once within Ostreococcus , and once in the other in the branch leading to the Micromonas lineage (Figure 4). shared between the 15 complete prasinovirus genomes. Phylogenies computed for each of these genes showed that most orthologs supported the monophyly of Ostreococcus viruses, with only 3.5% clustering with MpV1 (Figure 5C). To highlight the incongruencies of the gene tree topologies within the Ostreococcus virus phylogeny, we estimated the percentage of genes supporting the position of OmV2 on different branches. The majority (36%) of OmV2 genes clustered within the OmV1, OtV1 and OtV5 clade (Figure 5B), as compared to 8% of OmV2 genes supporting a more basal position.

Discussion

A decade of coexistence of microalgae and prasinovirus reveals a reversible susceptible-resistant phase switch

The study of a microalgae-virus system maintained for more than a decade provided evidence of two phenotypes: a virus-susceptible, S, and a virus-resistant phenotype, R, as well as the existence of an R to S phase switch within an isogenic culture undergoing clonal reproduction. Previous analyses of the related O. tauri -OtV system, have shown that O. tauri strains resistant to a broader range of virus strains tend to have larger SOC sizes (19) and increased differential expression of SOC-encoded genes (25). As the spontaneous mutation rate associated to random errors of the replication machinery ( 26) is too low to account for the rapidity and prevalence of the acquisition of viral resistance (Supplemental Text S1), we suggest that the phase switch is associated to a immunity specific mutation process involving a programmed modification of the SOC, as observed in O. tauri switching from S to R (25), but in O. mediterraneus was linked to an R to S switch. The cell immunity toolkit is notorious for combining genetic and non-genetic mechanisms to produce phenotypic plasticity from a single genome (27). While we can only speculate about the genes involved as there are no orthologous genes in the SOC of the Mamiellales sequenced to date, the same kinds of gene functions are overrepresented in the SOCs of all of these species, suggesting that variation in these functional genes imparts viral immunity in Mamiellales. Our results support the proposed function of the SOC as a specialised chromosome involved in antiviral immunity, evidence for which has been provided in two species so far: O. tauri and O. mediterraneus .

Analysis of the whole gene content of O. mediterraneus confirmed its phylogenetic position at the base of the Ostreococcus lineage. Maximum likelihood inference suggests that the Ostreococcus ancestor had a GC-poorer genome and contained a larger number of genes than the present species, revealing a global trend towards genome streamlining (28). The comparison of the genome sequence of its resident prasinovirus, OmV2, with available prasinovirus sequence reflected the story of a highly dynamic virus genome with recombination between related viral clades (29), and independent horizontal gene transfers from different microalga hosts into the virus genome (30). Altogether, phylogenetic analysis of OmV2 genes dismisses co-evolution of this host-virus pair since the speciation of O. mediterraneus . Instead, it is consistent with substantial gene exchange between the ancestors of present day species-specific prasinoviruses (23).

How does this phase switch translate into microalga-virus population dynamics?

Mathematical modelling of the phase switch is consistent with observed continuous virus production of OmV2 by O. mediterraneus , which is a consequence of the production of new viruses by S cells that are generated from R cells. This model does not generate oscillatory dynamics after an initial lysis event, contrary to many previous host-lytic virus coexistence models (11). The recently proposed 'leaky resistance' model from a bacteria-bacteriophage system (31) does also predict continuous virus and host growth and could also be invoked to describe the R to S switch. Interestingly, the population collapse observed upon infection in culture is only predicted if susceptible microalgae make up most of the population. This is predicted either if there is a bias between the S to R and the R to S switch (e S > e R ), or if susceptible microalgae have a higher growth rate than resistant microalgae, producing a trade-off between resistance and growth. While there is evidence of this trade-off in many bacterial-bacteriophage systems (32), there is little evidence for this in microalgae yet (33). This might be due to the long generation time of microalgae as compared to bacteria, but also because over longer time periods, our model predicts an equilibrium S/R ratio depending on four parameters that are independent of the phenotype of the founder cell. Interestingly, long term competition experiments started with an equal number of S and R O. tauri cells resulted in the evolution of cultures with a majority of S cells (10), consistent with either a higher growth rate of S cells and thus a cost of resistance, or e S > e R . In the present microalga-virus system, the cost of resistance may be metabolic, as a consequence of an increase in the size of the SOC, which requires additional energy and resources for cell replication.

One fundamental property of a life history strategy is its evolutionary stability (34), which can be estimated by investigating whether a population adopting one strategy can be invaded by individuals playing another. A microalga with a pure S strategy (it cannot convert from S to R) cannot invade a culture with the resistant/susceptible switch strategy (hereafter RS strategy) in the presence of viruses, as the viruses will lyse it. It will, however, invade an RS culture in the absence of viruses, since microalgae with a pure S strategy divide more rapidly than the R microalgae. Now, a microalga with a pure R strategy (not generating S cells), will not invade a RS population in the absence of viruses, because of its lower growth rate than the S microalgae. However, it will invade the RS population in the presence of viruses, as the R cells that do not switch to S will invade the population. The RS strategy we describe is therefore not evolutionarily stable, neither in the presence nor in the absence of viruses, so the most obvious explanation for its persistence comes from the evolutionary theory of bet-hedging (35) that demonstrates that a strategy may be suboptimal under one environmental condition, but advantageous in the long run, when environmental conditions alternate randomly. The RS strategy outcompetes both a pure S and a pure R strategy if virus presence and absence alternates (35). A droplet of seawater can certainly experience changes in virus prevalence over short timescales, by mechanisms of marine virus decay (36) or mixing of water masses or rain (37).

Last but not least, the RS strategy may confer a significant advantage by lysing competitors, because strains propagating a virus have a higher probability of invasion in face of competitors that may be susceptible to the virus produced (38).

What is the prevalence of the RS strategy in the environment?

Within the simplified one microalga one virus experimental set up our model makes two predictions. First, it predicts the systematic recovery of cell density after virus-induced lysis.

This has been reported in many different species from divergent branches of the eukaryotic tree of life: Haptophyceae, Stramenopiles and Chlorophytes (8)( 25) (39). Second, it predicts the steady production of viruses in apparently healthy cultures. While this has been explicitly reported in Emiliania huxleyi , Phaeocystis pouchetii (8) and O. tauri (10), it has also been observed in the dynamics of Chlorella variabilis (11). However, it is difficult to extend this single species dynamic to the community scale, where several microalga-virus pairs compete for the same resources (40). A general prediction we venture is that introducing RS microalgae in community models may increase the overall stability of the host-virus dynamics. This model is consistent with previously reported non 'boom and bust' dynamics in the natural environment (41), including persistent infection (42). Transcriptomes of several hundred species from the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP) initiative revealed the expression of core NCLDV genes in 13 cultures (43). While this may merely indicate infection, one of the haptophyte strains sequenced had been described as persistently infected (43). Screening six O. mediterraneus transcriptomes from the MMETSP (Supplementary Table S2) for OmV2 sequences, we found evidence for a virus in strain RCC2596. This strain was isolated on the same day and site as the genome sequenced strain RCC2590 and, although closely related, they are non-identical possessing ~5 differences per 10,000 bp and different karyotypes (13). RCC2596 was still available in culture in our lab and we could thus experimentally confirm the presence of viral DNA in the culture by PCR. Given that these strains were independently isolated, this implies stable coexistence was widespread in this population in the environment, but is simply not detected during the isolation of algae as the bulk culture grows reliably. We thus speculate that this phase switching is a common strategy within NCLDV-microalga interactions, in addition to mutation and selection mechanisms that lead to pure resistant microalga strains and the arms-race type of interaction. This phase switch is the result of a yet to be described molecular mechanism of cell immunity in microalgae, mirroring the complexity of the NCLDV genomes they have been co-evolving with since the early stages of eukaryotic life (44). S2.

Materials and Methods

Cultures and growth conditions

PFGE and in-gel hybridisation

PFGE and in-gel hybridization enabled estimation of chromosome sizes in different strains and testing for the presence of the virus genome. PFGE and in-gel hybridisation was performed as previously described (45) with modifications as follows. 8.7 × 10 7 cells in exponential growth phase were harvested by centrifugation (8000 g for 20 min) and resuspended in 150 µl of TE buffer 125 mM EDTA,pH 8), then embedded in plugs by mixing with an equal volume of molten low melting point agarose (1% in TE buffer precooled to 45°C). After setting, the cells were lysed in the agarose plugs by immersing the plugs in proteinase K buffer (10 mM Tris HCl pH 8, 0.5 M EDTA pH 8, 1% lauryl sarcosinate and 1 mg•mL -1 proteinase K (final concentration)) at 37°C for 24 h under constant agitation. The plugs were then washed three times in EDTA solution (0.5 M, pH 8) at 37°C for 2 hours under constant agitation and then stored in EDTA solution at 4°C. PFGE was performed in 0.8% agarose gels in 0.5 × TBE buffer (44.5 mM Tris,44.5 to cover the gels for 3 h at 65°C with constant agitation, after which radiolabelled probes were added and hybridised overnight at 65°C with constant agitation. After hybridisation, the gel was subjected to a series of washes with constant agitation: three washes in 6× SSC buffer at room temperature for 30 min, one wash in 6× SSC buffer at 65°C for 1.5 mins, followed by a final wash in 3× SSC buffer at room temperature for 5 mins. The gel was sealed in a transparent plastic sleeve, then exposed to radiographic film.

Transmission electron microscopy (TEM)

RCC2590 culture in exponential growth phase was centrifuged for 20mn at 6000g before inclusion in agar 1% to avoid successive centrifugations. Plugs were embedded in epoxy resin (epon 812) after fixation with 2.5% glutaraldehyde. Images were captured of individual cells and cells deemed to be visibly infected if clear virus-like particles were clearly present within the cell.

(Supplementary Table S2) had their transcriptome sequenced as part of the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP). The resulting transcriptomes are referenced in Supplementary Table S2 with their respective MMETSP identifiers.

The obtained set of contigs was cleaned from any contigs smaller that 300 bp, completed with EST sequences collected from NCBI (>300 bp), and mapped on the genomic scaffolds by combining BLASTN (for rapid detection on regions of interest) and GenomeThreader (for fine mapping, taking splice sites into account) with parameters set to map at least 98% of the transcripts sequence on the regions as reported by blastn. Besides, RNAseq was also mapped directly onto the genome using HISAT2 and junctions were extracted from the BAM alignments with regtools. The obtained junction instances where counted and grouped based on the intron coordinates that was spanned by a read. This count (or coverage) was used to filter for junctions confirmed by minimum 3 reads. Functional descriptions were inferred from filtered best-BLAST-hits and combined with protein domains obtained with Interpro. This automatic annotation was curated using the ORCAE portal (bioinformatics.psb.ugent.be/orcae/). All predicted genes were manually inspected and from the 8483 protein coding genes, 1142 have been modified (including gene fusions) and 59 discarded, resulting in a final set of 8110 protein coding genes. The functional description was manually edited for 662 genes.

Gene prediction in OmV2 was performed using Glimmer implemented within Geneious.

Functional description of predicted OmV2 genes was done using BLASTX against the NR database (from December of 2017) with default parameters and against the Pfam version 31.0 database (http://pfam.xfam.org/). tRNAs were predicted using the tRNAscan-SE 2.0 web server.

Comparative genome analysis

The The phylogenetic profile of TribeMCL gene families (excluding orphans) and the inferred Mamiellales tree topology were provided to reconstruct the most parsimonious gain and loss scenario for every gene family using the Dollop program from the PHYLIP package (version 3.69).

Prasinovirus phylogenomics

85 putative orthologous prasinovirus genes were identified for phylogenetic analyses by tBLASTx of predicted OmV2 genes against a database of all genes from 15 fully sequenced prasinovirus genomes (e-value < 10 -4 , amino acid identity > 75% and alignment length >50) accepting as 'core' those orthologs present in all genomes. Each ortholog family was aligned using MAFFT and phylogenetic trees were reconstructed using Bayesian inference with MrBayes using a mixed model for AA with 4 chains of 10 6 generations, trees sampled every 100 generations, and burnin value set to 20% of the sampled trees. We checked that standard deviation of the split frequencies fell below 0.01 to ensure convergence in tree search.

GC contents that vary from ~0.5 to ~0.65, the G+C composition has not evolved homogeneously in time, as was previously observed in many prokaryotic and eukaryotic lineages. For this reason, we considered a non-homogeneous and non-stationary approach in which stationary frequencies are allowed to vary from one lineage to another on the species tree. Each branch of the species tree is assigned its own set of parameters of the YN model and the stationary codon frequencies at the root of the species are also free to vary. We used Maximum Likelihood (ML)

and the bppML program to estimate the parameters of this non-homogeneous model and the branch lengths of the tree. Using the ML values for all these parameters, we reconstructed ancestral sequences with the bppAncestor program, using the marginal ASR approach. At a given internal node of the species tree, the codon state having the maximum posterior probability was inferred as the putative ancestral state. We then computed the ancestral global GC content as well as the ancestral GC content of all codon positions from these reconstructed ML ancestral sequences. We obtained a distribution of ancestral GCs for each ancestor from which we computed the mean and the 95% confidence interval.

Population dynamics of virus and microalga

Microalgae and viruses were counted over 13 days by flow cytometry and plaque assay from triplicate 20 ml cultures in tissue culture flasks at 15°C in a 12 h light:12 h dark regime.

Cultures of RCC2590 and S1 were inoculated to have a starting density of 10 4 cells•ml -1 .

Additionally, we passed the RCC2590 culture through a 0.2 µm filter to remove cells retaining free virions in the medium and kept this filtrate in the same conditions as the cultures to estimate viral particle stability over the duration of the experiment. For flow cytometry counts of cells and viruses, 250 µL was sampled every two days, fixed for 15 min in the dark with a final concentration of electron microscopy grade glutaraldehyde of 0.25% and Pluronic F68 of 0.01%, flash frozen in liquid nitrogen and stored at -80°C until analysis. Cell and viral particle counts were performed with the BD FACSCanto II (Becton Dickinson) where the flow rate over 1 min at a low rate was determined using triplicate measurements of BD Trucount Tube beads. Cells were counted from fixed samples using red autofluorescence and side scatter. Viral counts were performed on fixed samples after rapid thawing at 40°C, diluting as necessary in filtered seawater (< 0.02 µm), staining for 10 min at 80°C with SYBR Green I (Molecular Probes) (0.5× final concentration of commercial stock) and setting the trigger to measure green fluorescence and side scatter. To measure the concentration of infective OmV2 in the RCC2590 culture medium by plaque assay, 1 mL was sampled from the cultures every two days, centrifuged at 25,000 g for 10 min at 15°C to remove cells and the supernatant serially diluted with L1 medium. Plaque assay was performed with the diluted supernatant as described in [39] using the OmV2-susceptible O. mediterraneus strain S1 as the host.

Experimental assessment of the Resistant to Susceptible phase switch

Virus-free O. mediterraneus lines were obtained by end point dilution and virus absence was confirmed by PCR using degenerate primers for the viral DNA polymerase and Major

Capsid Protein gene (Supplementary Table S3). We started 204 clonal cultures from one single cell in 1 mL microwells and tested for virus susceptibility after 7 days. Virus susceptibility was tested using cell-free virus producing culture (VPC) medium.

To obtain cell-free VPC medium (i.e. separate potential virions from cell lysates), medium from growing or lysed cultures was centrifuged at 25,000 g for 10 mins at room temperature and the supernatant filtered (<0.45 μm). To test if a cell line was susceptible to lysis, VPC medium was introduced into the growing test culture, with a control culture grown in parallel inoculated with the same volume of sterile medium, and visually inspected for lysis up to five days after inoculation. This visual inspection detected when most cells are lysed and thus the ancestral cell was inferred to be susceptible. The validity of this inference relied on two assumptions: a low switch rate between the susceptible and resistant phenotype, and a low difference in growth rates between the resistant and susceptible phenotypes.

Mathematical modelling of the host-virus population dynamics

The model considered a population made of susceptible and resistant microalga (S t , R t )

and their viruses (V t ) at time t. The changes in microalgae and viruses numbers from one day (t)

to another (t+1) were modelled according to a simple representation of the algae and virus life-cycles and interactions with following assumptions: i) susceptible and resistant microalgae produce new microalgae at rate a s and a r , ii) microalgae born from a susceptible (resistant) to switch to a resistant (susceptible) phenotype at a fixed rate e R (e S ), iii) encounters between susceptible algae and virus to occur randomly at a rate c, iv) each infected microalga produced v viruses before death, and v) viral particles survived at a rate s V . The population dynamic of R, S and V can then be described by following equations:

1 )a e S a R S t+1 = ( -e R S -cV t t + e S R t a e S )a R R t+1 = e R S -cV t t + (1 -e S R t V t+1 = v S (1 ) -e -cV t S t + s e V v -cS t t
where is the probability drawn in Poisson distributions that a susceptible algae encounters e -cV t no virus or that a viral particle encounters no susceptible algae to infect.

This system was investigated analytically and numerically using the R software.

Confronting expected number of spontaneous mutations to prevalence of acquisition of resistance in the microalgae.

The combination of these two observations enables to estimate that at the time of infection, there was one (0.64) cell on average bearing a mutation in each culture. Therefore, it is very likely that one genome carrying the mutation was present in the culture at the time viruses were introduced. However, this spontaneous mutation had to confer viral resistance, which implies that 100% of spontaneous mutations confer resistance to viruses. Furthermore, a previous study on the evolution of viral resistance in the O. tauri and the prasinovirus OtV5 found all 38 independently infected cell lines became resistant to OtV5 [START_REF] Yau | A Viral Immunity Chromosome in the Marine Picoeukaryote, Ostreococcus tauri[END_REF]. We have now repeated this experiment on 24 OmV2 susceptible O. mediterraneus cell lines isolated from the S3 culture. This experiment confirmed that all independently infected lines evolved resistance within seven days in O. mediterraneus too.

In conclusion, precise calculation of the probability of a random spontaneous mutation producing a resistant phenotype, based on the knowledge we have on spontaneous mutation rate in these microalgae, enables us to reject spontaneous point mutations generated by random replication errors as the cause of the acquisition of resistance. S3. Primers used in this study on O. mediterraneus RCC2590 and OmV2. Abbreviations: Seq. S4. Species list and genome versions used for annotation and comparative genomics analysis. For species denoted with asterisk functional annotations (GO annotations and InterPro domains) were retrieved using the Uniprot Gene Association File (downloaded 10/09/2015). For all other species InterPro was ran (January 2016) and mapped to GO terms.

Supplementary Table

Species Source PubmedID

Aureococcus

Introduction

Planktonic photosynthetic eukaryotes of the class Mamiellophyceae (Chlorophyta) include the smallest eukaryotes, with bacterial-sized cells of less than 2 µm diameter.

Environmental surveys based on the sequence of the highly conserved 18S ribosomal gene (18S) eukaryotic barcode (1) revealed their worldwide distribution (2)(3)(4) (5). Their ubiquity, high abundance and turnover suggest they sustain the marine ecosystems in many coastal areas (6) (7).

Many flagellate species in this class were described last century before the advent of molecular biology techniques and their first application to these picoalgae (8); Monomastix 1912 ( 9), Micromonas pusilla 1951 (10), and Mamiella gilva 1964 ( 11), followed by Crustomastix and Dolichomastix 2005 (12). A non-flagellate member was described in 1990 as Bathycoccus prasinos (13) and the non-scaled coccoid Ostreococcus tauri was described in 1995 (14). A thorough phylogenetic analysis of the nuclear and plastid encoded rDNA operon led Marin and Melkonian to define the class Mamiellophyceae, divided into three orders Mamiellales, Dolichomastigales and Monomastigales (15). While twenty-two species are presently described in AlgaeBase ( 16), recent environmental sequencing suggests that many more species have not been yet isolated (5) (17) so that the number of species within this class remains an open question. The relative ease of culture of strains of the picoalgae Bathycoccus , Micromonas , and

Ostreococcus in Keller's and related media (18) fostered their development as new models for cell biology (19)(20) and environmental studies (21) (22). Complete and annotated nuclear genomes have been obtained for eight species to date: O. tauri RCC4221 (23), O. lucimarinus (24), O. sp. RCC809, O. mediterraneus (25), Micromonas pusilla and M. commoda (26), B.

prasinos RCC1105 ( 27), and O. tauri RCC1115 (28).

Despite the progress enabled by lab experiments and sequence analyses, the sexual life cycles of these haploid picoalgae, as well as their interactions with bacteria (29) and viruses (30) in situ remain enigmatic. Single amplified genomes (SAGs) assemblies, produced by multiple displacement amplification (MDA) after extraction from sorted single cells have been previously

reported to contain foreign DNA (31) (32). They may be viewed conceptually as metagenomes, provided they preserve a molecular signature of the ecological context of the cell. SAGs of cells directly sampled from the environment may not only foster knowledge on diversity in microorganisms (33) (34), but also open opportunities for the identification of all kinds of novel biological associations, from predation to parasitism (31) (35).

Here, we investigated 12 Mamiellales' SAGs sampled in the Indian Ocean during the Tara Oceans expedition (36) to explore the biological insights this data provides within an ecogenomic framework. Therefore, we analysed the taxonomic affiliations of the assembled sequence data to discuss the power and challenges of using SAGs to retrieve in-situ ecological information ( 1) from the target sequence data, e.g. Mamiellales sequences, about the mating type of the cells and ( 2) from the non-target sequences identified.

Material and Methods

Data

Single-cells were collected during the Tara Oceans expedition (37) from surface waters in the Indian Ocean at station 39, 41 and 46 (38) and cryopreserved using glycine betaine. Flow cytometric cell sorting, single cell lysis and whole genome amplification by Multiple Displacement Amplification (MDA) (39) were performed at the Bigelow Single Cell Genomics facility (Boothbay, Maine USA), as previously described (40)(41) (42-44)(41-43)(40-42) . The resulting SAGs were screened using universal eukaryotic 18S rDNA PCR primers (45). The 12 SAGs we analysed here were selected for sequencing based on the 18S identities and were sequenced using Illumina HiSeq technology at the Genoscope (33). All SAGs were multiplexed, SAG1 to 6 and SAG7 to 12 were sequenced on two different runs. The raw Illumina data was processed as previously described ( 36): adapters and primers used during library construction were removed from the whole reads and both ends were trimmed for low quality nucleotides (quality value < 20). The longest sequence without adapters and with fewest low quality bases was kept. Sequences between the second unknown nucleotide (N) and the end of the read were also trimmed. Reads shorter than 30 nucleotides after trimming were discarded. These trimming steps were achieved using fastx_clean, an internal software based on the FASTX library. The reads and their mates that mapped onto run quality control sequences (Enterobacteria phage PhiX174 genome, NC_001422.1) were removed using SOAP aligner. The total number of paired-end reads from the processed raw reads ranged between 19 and 36 millions with an average of 26 million reads per SAG.

SAG assembly and taxonomic affiliation of contigs

Individual pair-end read files were assembled using SPAdes v3.9.0 ( 46) and the final assembly statistics were generated with Quast v4. 6.3 (47). Contigs smaller than 400 bp were discarded from downstream analysis. Genome completeness was assessed with BUSCO v3.0.2 using the 303 eukaryotic single copy orthologs dataset ( 48) and compared to the values obtained on the available closely related sequenced genomes (Table 1).

The SAG assemblies were screened for contigs containing the 18S using a blastn homology search using a custom database of 18S extracted from GenBank complemented with 18S genes of Mamiellales extracted from the genome sequence (supplemental table 1). Contigs with a 18S hit were analysed with RNAmmer v1.2 ( http://www.cbs.dtu.dk/services/RNAmmer/ )

and the predicted 18S sequences were aligned with Mamiellales 18SrDNA sequences using MAFFTv7.305b [START_REF] Edgar | MUSCLE: multiple sequence alignment with high accuracy and high throughput[END_REF]. Alignments were trimmed with trimAI v1.2 (-automated1 method) [START_REF] Capella-Gutierrez | trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses[END_REF] and maximum likelihood phylogenetic trees were built under GTR model using RAxML v. 8.2.9

(51) and plotted with FigTree v1.4.3 ( http://tree.bio.ed.ac.uk/software/figtree/ ).

Taxonomic affiliations to separate non-target contigs (foreign DNA) from target (Mamiellophyceae) were performed as follows. Each contig was aligned against GenBank using DIAMOND ( blastx option e-value 1e-5 maximum aligned sequences 100) and the 10 best hits for each contig were kept. The taxonomic affiliation of each contig was retrieved using a custom perl script that fetched the GenBank accession number from the DIAMOND output, and retrieved the taxonomical nodes from the GenBank taxonomy database for each hit (script available upon request). Manual inspection of taxonomic affiliation of contigs containing several open reading frames led to the correction of the taxonomic affiliation for a few contigs affiliated to Archaea on the base of the best blast hit, while most open reading frames along the contig had a best hit against Bacterial sequences. As the complete genome and organellar sequences of Ostreococcus , Bathycoccus , and Micromonas species are present in GenBank, contigs were considered as target if at least one of the 10 best hits belonged to a Mamiellophyceae. We considered following high order taxonomic ranks: Archaea, Bacteria, Fungi, Mamiellophyceae, Metazoa, Oomycetes, Other (when several taxa were mixed in uneven proportions within the 10 best hits), Other protists, Plants (Streptophyta), Unassigned contigs and Virus. To estimate the number of reads recruited to each taxonomic rank in each SAG assembly, we aligned the reads against each assembly with BWA (52) and extracted the read coverage of each contig estimated from the SAMtools mpileup and depth suite [START_REF] Li | The Sequence Alignment/Map format and SAMtools[END_REF].

The sum of contig lengths affiliated to a given group was plotted with ggplots in the R environment [START_REF] Core | R: A language and environment for statistical computing[END_REF].

Cross-contamination filtering

To remove contigs derived from cross-contamination during the sequencing step, all SAG assemblies from the same Illumina run were compared against all with blastn (e-value cut-off 1e-5). This led to the inclusion of one SAG from a MAST lineage (TOSGAG23-1, GenBank accession ERX1271190) that was multiplexed with SAGs 7-12. Each contig was flagged as candidate contaminant if its alignment length with a contig from another SAG was equal or higher than 95% of the length of its best hit, with a nucleotide identity higher than 99.5%. The number of reads recruited to each candidate contig was used to define the source of the contamination: the SAG containing the contig with the highest read coverage was defined as the source SAG, and the corresponding contigs from the other SAGs were considered as contaminants and discarded.

Annotation of non-target contigs

Because the virus contigs detected in SAGs 8 and 12 had best hits with circular viruses, the contigs were first circularized with the Geneious program v10.0.5 [START_REF] Kearse | Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data[END_REF], and open reading frames (ORF) were predicted with Glimmer [START_REF] Salzberg | Microbial gene identification using interpolated Markov models[END_REF].

The conserved motifs of the viral replicase gene (57) [START_REF] Krupovic | Networks of evolutionary interactions underlying the polyphyletic origin of ssDNA viruses[END_REF] were manually searched by inspection of the predicted amino acids sequence located in the N-terminal endonuclease domain and in the C-terminal superfamily 3 helicase domain using MAFFT v7.305b (--localpair -maxiterate 1000). The best blastp hits to these ORFs were complemented with sequences retrieved from GenBank and the Ocean Atlas genes database (59) (supplemental table 2).

Multiple sequence alignments were performed with MAFFT v7.305b (--localpair --maxiterate 1000) [START_REF] Katoh | MAFFT version 5: improvement in accuracy of multiple sequence alignment[END_REF], and trimmed with trimAI v1.2 (-automated1 method) [START_REF] Capella-Gutierrez | trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses[END_REF]. For each alignment, protein evolution models were selected using ProtTest v3.4.2 [START_REF] Darriba | jModelTest 2: more models, new heuristics and parallel computing[END_REF] with the Akaike Information Criterion (AIC) (LG+I+G for ORF1 and RTREV+I+G+F for ORF2). Phylogenies were built by the maximum likelihood method implemented in RAxML v. 8.2.9 [START_REF] Stamatakis | RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies[END_REF], and plotted in FigTree v1.4.3 ( http://tree.bio.ed.ac.uk/software/figtree/ ).

Screening assemblies for information about mating type

In Ostreococcus species, population genomics analyses have revealed two anciently diverged 500 kb genomic regions with supressed recombination, which are candidate mating type regions (28). As in many bipolar mating type systems, orthologous genes on this mating type locus (MT) cluster phylogenetically by mating type, not by species (28). This is as expected if the origin of mating types predates speciation within this genus, as previously observed in the Volvox genus [START_REF] Ferris | Rapid evolution of sex-related genes in Chlamydomonas[END_REF]. We took advantage of this deep divergence between 23 orthologous genes families of the two mating types, gametologs [START_REF] Garcia-Moreno | Rooting a phylogeny with homologous genes on opposite sex chromosomes (gametologs): a case study using avian CHD[END_REF], to screen the SAG assemblies for homologous sequences. Briefly, orthologous gene families were obtained following an 'all-against-all' protein sequence similarity search, performed with blastp (maximum e-value 1e-4) and gene families were delineated using OrthoFinder (version 2.1.2) [START_REF] Emms | OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy[END_REF]. The dataset consisted of 23 genes in the eight sequenced Mamiellophyceae genomes (28) (26), O. lucimarinus [START_REF] Palenik | The tiny eukaryote Ostreococcus provides genomic insights into the paradox of plankton speciation[END_REF] and O. spp RCC809, O. mediterraneus RCC2590 (25). Protein coding sequences of these genes in the Ostreococcus SAG assemblies were extracted manually from the tblastn nucleotide alignments.

Biogeographic occurrence of Mamiellales SAG-associated sequences

The non-targeted bacterial sequences (supplemental table 3) were searched against 957 manually curated partial assemblies (metagenome-assembled genomes MAG) reconstructed from 93 TARA Oceans metagenomes [START_REF] Delmont | Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes[END_REF], including those stations from the North Indian Ocean the Mamiellophyceae where the SAGs were isolated. A match against a MAG was defined as an alignment of 90% of the length of SAG-associated bacterial contig with a nucleotide identity higher than 98%. Nucleotide identity and total alignment length for each SAG associated bacterial contig were computed from blastn alignments [START_REF] Altschul | Basic local alignment search tool[END_REF].

The geographic occurrences and distribution of the non-target virus sequences was obtained by searching for homologous sequences to the two predicted protein-coding genes, a capsid and a replicase, in the OCEAN GENE ATLAS (59) using blastp (e-value 1e-5).

Amino-acid sequences for each hit were downloaded from the database (supplemental table 2).

This atlas contains a gene catalogue from 243 metagenomes and 441 metatranscriptomes from the Tara Oceans expedition, as well as the metagenomes from the Global Ocean Sequencing (GOS) expedition [START_REF] Villar | The Ocean Gene Atlas: exploring the biogeography of plankton genes online[END_REF].

Results

Completeness of Target Assemblies

Phylogenetic analysis of 18S data retrieved from the de novo assembly was consistent with prior taxonomic affiliations. Ostreococcus SAG 18S sequences retrieved from the de novo assembly clustered with O. spp RCC809. However, while SAG9, 10, 11 sequences were 100% identical to RCC809 (and RCC143), the 18S sequence of SAG11 had one difference to RCC809.

The non-target assemblies recruited 0.01 to 6% of the reads (Table 1). Taxonomic affiliation of total non-target contigs is provided in Figure 3A and varies greatly between SAGs.

For eight SAGs, most non-target reads were recruited to Bacteria, for 2 SAGs, most non-target reads were recruited to Oomycetes, and for 2 SAGs, most reads were recruited to sequences of viral origin. Sequence comparison between non-target assemblies revealed 100% identical sequences shared between SAGs coming from different stations, but sequenced on the same Illumina lane, a suspicious signature suggesting cross-contamination during the amplification and sequencing step (73). This led us to define a cross-contamination filter procedure for all SAGs sequenced within the same run. To find out which of the SAGs was the most likely source of the contamination, we used the number of reads recruited to non-target contigs. The SAG containing the most sequenced reads was considered as the source SAG of the non-target contig.

The taxonomic affiliation of non-target contigs following filtering is presented in Figure 3B. Basically, this led to a 2 to 7-fold reduction of the total non-target assembly length depending on the SAG (Table 2). Following cross-contamination filtering, the maximum percent of reads recruited to non-target sequences dropped from 6% to 1% in SAG8, and became almost negligible (0.002%) in SAG10. The taxonomic affiliation of these filtered non-target sequences could be divided into three groups: Bacteria, Oomycetes/Fungi and Viruses, in order of decreasing frequency.

Most non-target reads were recruited to Bacteria for 11 SAGs and to virus for one SAG (SAG12) (Figure 3B). The non-target bacterial contigs had a large phylogenetic spread (Figure 4A) and while the most common phylum belonged to the Proteobacteria, there was no evidence of any specific bacteria -SAG association from this analysis. To gain more information about the origin of the 83 non-target bacterial sequences, we estimated their similarity with 957 manually curated partial assemblies (metagenome-assembled genomes MAGs) reconstructed from 93

TARA Oceans metagenomes [START_REF] Delmont | Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes[END_REF]. Over one third (32 out of 83) bacterial contigs had more than 98% identity over 90% of their length with a TARA MAG, suggesting indeed that these bacteria belong to the most abundant bacteria sequenced within the TARA Ocean sampling (Figure 4A).

However, only 3 bacterial contigs had a hit against a MAG from the North Indian Ocean, while most hits were against MAGs from the Mediterranean Sea and South East Pacific Ocean.

Therefore, except for the 3 bacterial contigs assembled from SAG3 and SAG4, the bacteria sampled together with the SAG do not represent the most dominant bacteria at the sampling site.

The cross-contamination filtering removed most of Oomycetes affiliated non-target contigs (Figure 3B), and the source was one uncultured marine Stramenopile (MAST) SAG [START_REF] Mangot | Accessing the genomic information of unculturable oceanic picoeukaryotes by combining multiple single cells[END_REF] sequenced in the same lane as SAG7 to SAG12. The class Oomycetes is also from the Stramenopiles group and form a distant, yet phylogenetically related clade to MASTs, which currently lack representation in reference databases [START_REF] Seeleuthner | Single-cell genomics of multiple uncultured stramenopiles reveals underestimated functional diversity across oceans[END_REF]. Following the cross-contamination filtration step, non-target Oomycete contigs were affiliated to four families (Figure 4B):

Pythiaceae (2 contigs), Albuginaceae (3 contigs) and the more abundant Peronosporaceae (30 contigs) and Saprolegniaceae (33 contigs). Given the available genome size estimations in Oomycetes [START_REF] Mcgowan | Comparative Analysis of Oomycete Genome Evolution Using the Oomycete Gene Order Browser (OGOB)[END_REF] or MASTs [START_REF] Mangot | Accessing the genomic information of unculturable oceanic picoeukaryotes by combining multiple single cells[END_REF], which are larger than 20 Mbp, the size of the largest target Mamiellales, Micromonas (Table 1), the quantity of Oomycetes DNA present within the SAGs 136 precludes any evidence of co-sampling, but rather suggests random capture of DNA during the cell sorting process. leading to smaller ORF1 sequence. The experimental analysis performed would not discriminate whether these sequences arose from single or double stranded DNA. The read coverage of the SAG8 and SAG12 viruses is 50x and 7893x respectively. Assuming MDA amplification did not induce coverage biases between the virus and nuclear genomes, the same average coverage would be expected for viral and nuclear nucleotides. Compared to the average coverage of the nuclear genome, the SAG8 associated virus had a 10-fold lower coverage, while the SAG12 associated virus had a 5-fold higher coverage. This supports the notion that the virus was present in multiple copies (5 copies) within the cytoplasm of SAG12, suggesting an infected state, while there were fewer copies, and may have been under-amplified, in SAG8. The majority of circular DNA viruses were "Circular Replication-associated protein Encoding Single-Stranded DNA"

(CRESS) viruses [START_REF] Zhao | Eukaryotic Circular Rep-Encoding Single-Stranded DNA (CRESS DNA) Viruses: Ubiquitous Viruses With Small Genomes and a Diverse Host Range[END_REF]. They have been found within diverse hosts and marine metagenomes, even though there is not much information regarding their infection strategies. To explore the similarity of the Mamiellales associated circular virus to other CRESS DNA viruses, we performed Maximum likelihood phylogenetic analyses of their predicted capsid (Figure 5C) and predicted replicase (Figure 5D) proteins, together with their retrieved blast hits (e-value cut off 1E-5) both in GenBank and in the TARA-Oceans Gene Atlas. Capsid homologous sequences were found in seven TARA-Oceans metagenomes (Figure 5B) including station 41 in the Indian Ocean, the same station where the Ostreococcus SAG12 was sampled.

Discussion

SAGs have so far been previously used to increase our knowledge of the uncultivable multitude of marine microorganisms ( 40) [START_REF] Seeleuthner | Single-cell genomics of multiple uncultured stramenopiles reveals underestimated functional diversity across oceans[END_REF]. The use of SAGs to discover novel species does not necessitate high genome coverage as only a handful of highly conserved genes is informative to delineate a species. However, partial genome coverage may constitute a greater challenge for the use of SAGs in evolutionary studies. To increase the genome coverage of a target species, data from genetically close SAGs may be merged together (33)(45). This approach has been successfully applied by Vannier et al (33) to the 4 Bathycoccus SAGs and resulted in an assembly estimated to contain 64% of the complete genome. The amino-acid identity between this novel assembly and the reference B. prasinos RCC1105 genome led the authors to conclude that these 4 SAGs belonged to a cryptic novel Bathycoccus species, TOSAG39, which is supported here by the phylogenetic divergence of their mitochondrial genome sequences.

Although combining SAGs produces a more complete genome, individual information about the environment of the sorted single cells, which could indicate potential biological interactions, or even stages of infections in the case of parasites, may be lost.

Although the individual SAGs were estimated to represent a maximum of 27% of the complete genome sequence in Ostreococcus , a search for the presence of 23 gene families located in the mating-type region in Mamiellales enabled us to retrieve orthologous genes for 3

Ostreococcus SAGs. Amino-acid identity between the SAG sequences and the sequences from available genomes indicated that the candidate mating type of the 3 Ostreococcus SAGs was MT+ , like the candidate mating type of the closest reference genome from strain O. sp RCC809 (28). The relative prevalence of the MT+ and MTin natural Ostreococcus blooms remains an open question. To the best of our knowledge, the co-occurrence of strains of the two mating types from the same sample has not yet been reported, but the maximum number of strains isolated from the same sampling point is less than 3 [START_REF] Grimsley | Cryptic sex in the smallest eukaryotic marine green alga[END_REF]. The minimal frequency of sexual reproduction has been estimated indirectly in Ostreococcus tauri from the population polymorphism spectrum, 1 sexual meiosis for 100,000 clonal divisions (28). This low rate may be explained either by a low encounters rate of MT+ and MTstrains in their natural environment, or by a low rate of outcrossing. The identification of informative sequences from the MT locus in 3 of the 4 SAGs demonstrates the utility of the single cell genomics approach for estimating the frequencies of the two mating types within a bloom, provided that a sufficient number of cells is analysed. While the presence of identical MT s in 3 SAG is consistent with clonal reproduction within a bloom, the sample size was too small for a proper estimation of the level of clonality within a bloom.

The estimations of the percentages of reads recruited to the mitochondrion and chloroplast genomes in each SAG attest the ability of single cell sequencing to identify novel candidate associations in the smallest eukaryotic microalgae of the order Mamiellales. Indeed, while organellar copy numbers may reach several thousands of copies in humans [START_REF] Miller | Precise determination of mitochondrial DNA copy number in human skeletal and cardiac muscle by a PCR-based assay: lack of change of copy number with age[END_REF] or Arabidopsis [START_REF] Morley | Chloroplast DNA Copy Number Changes during Plant Development in Organelle DNA Polymerase Mutants[END_REF], bacterial-sized Ostreococcus have a reduced number of organellar genomes, with an average copy number per cell estimated at 4 and 5 for the mtDNA and cpDNA, respectively. As a consequence, the systematic identification of mtDNA and cpDNA sequences from the SAGs provides support to the ability of this strategy to detect genomic sequences of any intracellular symbionts, provided there is no DNA amplification bias as a consequence of differences in genome architecture or cell wall structure between the symbiont and the organellar genome. Alternatively, these sequences might arise from random capture of amplified dissolved DNA in the marine seawater around the isolated picoalgal cells. In a typical sorting run the droplet containing a single cell may contain about 2.8 nL (80), or 2.8 × 10 6 µm 3 . The sample volume within a drop is around 1/1000 of the total volume, or 2.8 × 10 3 µm 3 , whereas a single

Ostreococcus cell contains about 0.5 µm3 of cytoplasm, giving about 6 × 10 3 fold more seawater than cell volume, ample space for the "phycosphere" [START_REF] Seymour | Zooming in on the phycosphere: the ecological interface for phytoplankton-bacteria relationships[END_REF] or dissolved DNA (82) that may be sequenced with the targeted algal cell.

To distinguish between random capture of dissolved DNA and intracellular symbionts, relative read coverage of the non-target to the target genomes provides a rule of the thumb about the likely origin of the non-target sequences. In the present data, we found that most of the non-target sequence data can be traced back to cross-contamination from another SAG, sequenced in the same Illumina run. Filtering out cross-contaminants, the amount of non-target DNA identified -except for the virus sequence -is not compatible with co-sampling of a Mamiellales and a bacteria or Oomycete cell, and rather suggests random capture of dissolved DNA. These associated non-target sequences may nevertheless provide information about the diversity of microorganisms present in the cell's environment. Indeed, Mamiellales are auxotrophic for B vitamins [START_REF] Paerl | Use of plankton-derived vitamin B1 precursors, especially thiazole-related precursor, by key marine picoeukaryotic phytoplankton[END_REF] and have been found to co-occur with diverse bacteria in lab cultures (29) [START_REF] Lupette | Marinobacter dominates the bacterial community of the Ostreococcus tauri phycosphere in culture[END_REF], though no obligate specific association has been yet observed. The taxonomic diversity of the candidate associated bacterial contigs retrieved from the SAG data is thus not surprising.

The presence of a novel CRESS-like DNA virus came as a surprise. Single-stranded DNA (ssDNA) viruses with circular genomes, with sizes from ~1700 bases, are the smallest viruses known to infect eukaryotes [START_REF] Rosario | Diverse circovirus-like genome architectures revealed by environmental metagenomics[END_REF]. Several previous metagenomic studies have identified many novel genomes similar to ssDNA circular viruses through data-mining of public marine metagenomes (85)( 86), but with no hints about their putative hosts. Previously described CRESS viral hosts range from plants (87) (Geminiviridae, Nanoviridae), bleached kelp macroalgae [START_REF] Beattie | Novel ssDNA Viruses Detected in the Virome of Bleached, Habitat-Forming Kelp Ecklonia radiata[END_REF], vertebrates (89) (Circoviridae), fungi, insects (Genomoviridae) [START_REF] Krupovic | Genomoviridae: a new family of widespread single-stranded DNA viruses[END_REF], and crustaceans [START_REF] Rosario | Virus discovery in all three major lineages of terrestrial arthropods highlights the diversity of single-stranded DNA viruses associated with invertebrates[END_REF]. In protists, CRESS viruses were discovered in SAGs targeting Picobiliphytes (31) and in Bacillariophyceae diatoms, where they have been isolated and their lytic effect could be demonstrated [START_REF] Shirai | Isolation and characterization of a single-stranded RNA virus infecting the marine planktonic diatom Chaetoceros tenuissimus Meunier[END_REF]. The Mamiellales associated circular viruses described here are among the smallest viral genomes described to date infecting the smallest photosynthetic eukaryotes.

In conclusion, sorting of these 12 Mamiellales SAGs by flow cytometry relied on the choice of appropriate volumes to favour isolation of one cell, and the "phycosphere" around cell had been subjected to turbulent mixing with the cytometer sheath fluid, thus limiting the suitability of this technique for identification of cell-to-cell interactions. Independent ways of finding such associations are necessary, one of which may be to pick off single cells using micromanipulation (see (35) phylogenetic profile to confirm the mating type affiliations. Since we also identified specific GFs for each mating type group, this GFs can also be used to infer the mating type giving the presence/absence of minus and plus specific genes, both in culture and in the environment.

Furthermore these specific gene sets can be used to track the expression profiles in controlled experiments aimed to help in understanding the gene and phenotype differences between MTs in culture and to evaluate differences in the process of life cycle.

Remaining questions regarding this subject to be answered in the future are:

-Are there sex-determining regions in the most basal Mamiellophyceae, such as in the orders Dolichomastigales and Monomastigales?

-Did mating types evolved independently in other Mamiellophyceae lineages?

-How can the mating process in Mamiellales algae be triggered in laboratory conditions?

In the third chapter, we characterized the genomes of the earliest branching member of suggesting a bet-hedging strategy for their coexistence. Our results indicated the possibility of finding viruses with unusual lifestyles when sequencing host genomes, in these cases, an co-existent virus, which did not lyse the whole population of cells.

Questions remaining regarding this subject to be answered in the future are:

-What is the natural polymorphism of SOC chromosomes in environmental O.

mediterraneus ?

-What is the environmental distribution of OmV2 viruses and is there any cophylogeny between host and virus?

-Are there other examples of algal-virus interactions that parallel to our observed system?

And lastly, in the fourth chapter, we interrogated 12 single amplified genomes (SAGs) of Ostreococcus , Bathycoccus and Micromonas which were isolated in the Indian Ocean in the Tara Oceans Expedition. We asked whether these genomes (8 unpublished), contained metagenomes and signatures of putative biological interactions. We approached this question by analysing the fraction of sequences that did not belong to Mamiellales, and also by looking for mating type core genes which could indicate the presence and ratio of different mating types in a bloom. This work resulted in the article "Single cell ecogenomics reveals mating types of individual cells and ssDNA viral infections in the smallest photosynthetic eukaryotes", where we integrated the main subjects of this PhD thesis, sexual interactions through mating types and viral interactions.

By investigating which fraction of these single amplified genomes contained sequences that were not from the target sequence, we described two novel complete viral genomes from the group of ssDNA circular viruses, an indication that even with the limitations of SAGs, they can be used to infer such putative interactions, and in this case novel organisms since these viruses appears to represent a novel viral family and among the smallest viral genomes described to date.

Remaining questions regarding this subject to be addressed in the future are:

-Can we isolate the new viruses identified here in order to characterize their morphological characteristics and their effects in Mamiellales hosts?

-Are there novel and different Mamiellales viruses, other than Prasinoviruses or other than DNA and RNA genome architectures?

-Can we experimentally verify the role of viruses in triggering mating process in Mamiellales?

In general, in order to answer all of these questions opened by our research into mating type evolution and viral interactions in Mamiellophyceae algae, posed at the end of each chapter perspective, there is primarily a need to sequence more genomes from this group. The focus should be on specimens from the lesser studied orders of Monomastigales, and Dolichomastigales, as well to try to isolate new viruses that possibly infect them, then sequencing their genomes. Secondarily, once there is new data, to study experimentally in depth those organisms under a wide range of conditions, focusing on their transcriptional responses, especially to try to investigate the empirical conditions necessary to perform mating process.

Lastly, there is a need to better understand their ecological adaptation and local interactions through the seasons in the global ocean. Now that we have provided some genomic insights into those organismal interactions, by describing the evolution of one of the oldest sex-determining regions in green algae, novel mating type strains, and indicating unknow players, such as as new viruses, this is an ideal time to expand the knowledge on Mamiellophyceae green algae, on their interplay and life cycles through evolutionary timeframes.

LIST OF FIGURES:

Figure 2 .

 2 Figure 2. The new eukaryotic tree of life: This summarized tree is based on a consensus of recent phylogenomic studies. Colored groupings correspond to the current "supergroups". Unresolved branches among lineages are shown as multifurcations. Broken lines reflect lesser uncertainties about the monophyly of certain groups. Lineages which contain "algae" are depicted as dark green stars. Figure adapted from Burki et al. (2019).

Figure 3 .

 3 Figure 3. Examples of protist diversity: Dinoflagellate (a); Chlorophyte (green algae) (b); Ciliate (c); Euglenid (d);

Figure 4 .

 4 Figure 4. Distribution and life cycles focused in eukaryotic algae: Cladogram of eukaryotes highlighting groups that contain algae, indicated by colored text at branch tips. Gray dashed branches are polyphyletic taxa that are grouped together for simplicity. Solid black circles next to each algal clade indicate direct evidence of sex for one or more clade members, and open circles indicate indirect evidence based on presence of sex-related genes in one or more clade members. Modified from Umen and Coelho (2019).

Figure 5 .

 5 Figure 5. Examples of direct evidence for sex interactions (mating) in protists: Difflugia sp. (Amoebozoa) (a); Tetrahymena sp. (Ciliate) (b); Coleps sp. (Ciliate) (c); Chlamydomonas sp. (Chlorophyta) (d); Sellaphora auldreekie Diatom (Stramenopila) (e). Figure adapted from:flickr.com/photos/microagua/2869529517/sizes/m/ (a);

Figure 6 .

 6 Figure 6. Alice and the Red Queen running but getting nowhere: Illustration by John Tenniel from the first edition of Lewis Carroll "Alice Through The Looking Glass", chapter two -The Garden of Live Flowers. Source:

  . The genus with the most genomic resources in the Mamiellophyceae is Ostreococcus (Chrétiennot-Dinet et al. 1995), with 17 genomes sequenced from four species (Blanc-Mathieu et al. 2017); Palenik 2017; Yau et al. 2019) and 4 new genomes amplified from single cells isolated from the Indian Ocean (Benites et al. 2019) . The majority of core meiotic genes were comprised in the first version of the genome of O. tauri OTTH0595 (Derelle et al. 2006) thus suggesting that the genetic basis of sexual reproduction was present. A few years later, indirect evidence of crossing-over and chromosomal segregation was provided from population genetic data in a natural population of 19 strains (Grimsley et al. 2010), implying a cryptic sexual stage in O. tauri .

  , to basal Mamiellales such as Mantoniella, but also included several Micromonas strains from novel species, such as M . bravo and M . polari s. In total, at least one homologous gene was recovered for each GF (with an average of 11 GFs per transcriptome) in 28 out of 33 transcriptomes (fig.4). Legend figure 4: Presence-absence matrix of best BLAST hits (BBH) of core MT gene families in each Mamiellophyceae transcriptome. Species' names of sequenced strains (left column) as inferred from 18S rRNA sequence analysis extracted from the transcriptome (supplementary figure S8, Supplementary Material online). The color of each rectangle indicates the taxonomic affiliation of the BBH (color key on the right). Transcriptomes containing genes with a BBH affiliated to a different species are highlighted in gray.

Legend figure 5 :

 5 Unrooted maximum-likelihood phylogenetic trees of core MT GF (A) and (B) including homologous sequences from Ostreococcus lucimarinus MMETSP0939 (strain BCC118000) and O . mediterraneus MMETSP0929 (strain RCC2572). Candidate mating type genes MT+ are in red, MT -in blue. Topology (A) clusters genes according to mating type, whereas topology (B) corresponds to the species phylogeny. Ultrafast bootstrap support values are indicated on branches. Abbreviations: OT4221 ( O . tauri RCC4221), OT1115 ( O . tauri RCC1115), OL ( O . lucimarinus ), OLMMETSP0939 ( O . lucimarinus BCC118000), O809 ( O . sp RCC809), OM ( O . mediterraneus RCC2590), OMMMETSP0929 ( O . mediterraneus RCC2572) B1105 ( Bathycoccus prasinos RCC1105), MC299 ( Micromonas commoda RCC299), MPU ( M . pusilla ).

2

  Department of Marine Biology and Oceanography, Institute of Marine Sciences (ICM), CSIC, Barcelona, Spain. 3 Ghent University, Department of Plant Biotechnology and Bioinformatics, Technologiepark 927, 9052 Ghent, Belgium. Introduction Phytoplankton-virus interactions are major determinants of geochemical cycles in the oceans. Viruses are responsible for the redirection of carbon and nutrients away from macro-organisms back towards microorganisms via the lysis of their hosts in a process coined the 'viral shunt'. Resolving the mechanisms underlying these interactions and their significance to phytoplankton dynamics represents one of the major challenges for future projections of ocean ecosystems under climate change (1)(2).

  Susceptible hosts are infected by viral particles present in the environment, which ultimately leads to the lysis of the infected cell and the release of v S new viral particles that survive in the environment at a rate s V . While reproducing asexually at rates a s and a r , S algae produce a fraction e r of R cells, while R algae generate a fraction e s of S cells.

Fig. 3 .

 3 Fig. 3. Model predictions of microalga-virus population dynamics. (A) Model parameters with and without virus. (B) Simulation of the evolution of the number of microalga cells during 40 days, viruses are introduced after 13 days and the system converged to its Virus/Microalga equilibrium behaviour after 18 days, aS = 1.75, aR = 1.7, eS = eR = 0.01. (C) Evolution of the proportion of Susceptible (S) and Resistant (R) microalga, initial S and R values have been set to reflect equilibrium proportion without virus.

  at which S and R cells produce 1 -e R a S 1 -e S a R new progeny cells of the same kind as themselves. In such circumstances, the S/R ratio equals which, for presumably small switching rates ( , ) and considering a cost to a /(λ ) e S R f ree -A e S e R resistance, i.e. , leads to a larger fraction of S cells in the population, as shown in Figure a S > a R

Fig. 5 .

 5 Fig. 5. Phylogenomic analysis of prasinovirus OmV2. (A) Whole genome alignment of OmV2 compared to the Ostreococcus tauri virus, OtV5. Genomic regions with 60-100% nucleotide identity are joined by red blocks with higher identity indicated by darker red. Genes are coloured according to functional groups. (B) Maximum likelihood phylogenetic tree of amino acid sequences of the DNA polymerase B gene from prasinoviruses infecting the genera Ostreococcus, Micromonas and Bathycoccus . The tree was rooted with Paramecium bursaria chlorovirus (PBCV1) ( Chlorovirus ) with the connecting branch truncated for display. The red circle highlights the position of OmV2. Circles at the nodes represent bootstrap support of 50-70% (white), 70-90% (grey) and 90-100% (black). The scale bar shows substitutions per site. (C) Cladogram representing the relationships between the fully sequenced prasinovirus clades from 85 core genes. Coloured circles mark the branching positions of the percentage of the OmV2 orthologs.

F

  , forward primer sequence; Seq. R, reverse primer sequence; SOC, small outlier chromosome; BOC, big outlier chromosome; DNApol, viral DNA polymerase B; MCP, viral Major Capsid Protein.

FIG3-

  FIG3 -Taxonomic affiliations of non-target sequences. (a) Percent of raw read number (b) Percent of reads following cross-contamination read filtering.

FIG4-

  FIG4 -Taxonomic affiliation inferred from best blast hits (1 × 10-5 cut-off ) of Bacterial contigs (a) at level of the phylum; Oomycetes contigs at level of family (b) (sum of contig lengths per taxa in each SAG is indicated by bubble size). Length of contig recruited to TARA MAGs from TARA metagenomes is indicated by bubble colour.

  Ostreococcus genus, O. mediterraneus , and O. mediterraneus virus 2 (OmV2) that was sequenced together with it hosts indicating coexistence in order to understand the nature and the dynamics in this algal-virus association. This investigation resulted in the article "Virus-host coexistence in phytoplankton through the genomic lens".Main activities performed for this work and directly related to this PhD thesis concerned analysis of the virus, first in the electron microscopical inspection of host-virus cultures to count the number of infected cells and to estimate the percentage of infection, and then the virus genome analysis and phylogenomics. By inspecting individual phylogenies of core genes of OmV2 in relation to other related viruses we found that contrary to the position of O. mediterraneus which is basal to other Ostreococcus , the majority of OmV2 gene phylogenies clustering with O. tauri viruses. This is also incongruent to the position of the main viral marker POLB which shows a more basal placement of OmV2, indicating the possibility of host coinfection by different viruses or gene transfer events. We also proposed a mathematical model for the dynamics between the O. mediterraneus and its virus OmV2 in natural communities,

CHAPTER 1 : 1 Figure 1 . 2 Figure 2 . 3 Figure 3 . 5 Figure 4 . 7 Figure 5 . 8 Figure 6 . 10 Figure 7 . 15 Figure 8 .Figure 9 . 23 Figure 10 .Figure 11 .Figure 12 .Figure 13 .Figure 14 . 34 Figure 15 .CHAPTER 2 : 42 Figure 1 . 52 Figure 2 . 54 Figure 3 .Figure 4 . 56 Figure 5 .Figure 6 .

 111223354758610715892310111213143415242152254345656 Figure 1. Organismal interactions in marine environments…………………………………...……………………....2 Figure 2. The new eukaryotic tree of life.…………...……………………………………………………………..….3 Figure 3. Examples of protist diversity ..…………….…………………………….…………………………………..5Figure 4. Distribution and life cycles in eukaryotic algae ……..……………………………………………………....7 Figure 5. Examples of direct evidence for sex interactions (mating) in protists …...………………………………....8 Figure 6. Alice and the Red Queen running but getting nowhere ………………..…………………………………..10 Figure 7. Mating type model for Chlamydomonas and phylogenetic distribution of RWP-RK genes …..…………..15 Figure 8. Electron microscopy micrographs depicting examples of algal viruses ....……………………….……..…21 Figure 9. Phylogenetic relationships of selected algal viruses …..……………….…………………………………..23 Figure 10. Mamiellophyceae diversity depicted by light microscopy observations ..…………………………..……26 Figure 11. Integrative and comparative circular view of Mamiellales reference genomes ....…………………….…29 Figure 12. General characteristics of O. tauri RCC4221 chromosomes……………………….. .………………..…30 Figure 13. General characteristics of M. pusilla CCMP1545 and M. commoda RCC299 chromosomes ..……….…31 Figure 14. Genetic structure of the two candidate MTs in O. tauri on chromosome 2…..…………………………..34Figure 15. Negative staining technique depicting examples of Prasinoviruses particles …...……………………..…37

Figure 7 .CHAPTER 3 : 75 Figure 1 . 81 Figure 2 . 85 Figure 3 .Figure 4 .Figure 5 .CHAPTER 4 :Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .CHAPTER 2 :

 73751812853454123452 Figure 7. GC3 content of genes from core MT GFs (dark green) versus standard chromosome genes (light green) in Mamiellophyceae species…...………………...………………...………………...…………….……….….…...……62

  The most intriguing pattern came from Ostreococcus mediterraneus MMETSP0929 (strain RCC2572) and O. lucimarinus MMETSP0939 (strain BCC118000) transcriptomes.While both dataset displayed hits for almost all core genes (17 out of 23), the taxonomic affiliation of the best BLAST hits (BBH) disagreed with the 18S taxonomic affiliation and suggested affiliation to a different species of the opposite mating type ( supplementary fig.S8, Supplementary Material online). In O . mediterraneus MMETSP0929, 14 out of 17 BBH were affiliated to species from the opposite MT groups ( MT -) as O . tauri and O . lucimarinus , and not to the reference genome O . mediterraneus RCC2590 MT+ . Likewise, 15 out of 17 BBH of O .

lucimarinus MMETSP0939 came from MT + genomes, and not from the MT -O. lucimarinus reference genome. Maximum likelihood phylogenies of the genes from these GFs including these genes extracted from the transcriptomes were built to confirm the BBH taxonomic affiliation ( supplementary fig. S9 , Supplementary Material online). From the 17 BBH GFs, 12 passed the alignment length threshold (see methods), of which 10 phylogenies included both O . mediterraneus MMETSP0929 and O . lucimarinus MMETSP0939, and two phylogenies included only O . lucimarinus MMETSP0939. From these, 11 GF phylogenies were consistent with ancient MT+ and MTdivergence (examples in fig. 5A), while one phylogeny regrouped genes according to species (fig. 5B).

table S1 ,

 S1 Supplementary Material online) was loaded into a custom version of the pico-PLAZA framework[START_REF] Vandepoele | pico-PLAZA, a genome database of microbial photosynthetic eukaryotes[END_REF] to define and analyze gene families. Following an

	'all-against-all' protein sequence similarity search, performed with BLASTP ( Proost et al. 2009 )
	(version 2.6.0+, maximum e-value threshold 10 -4 , keeping up to 2,500 hits), gene families (GFs)
	were delineated using OrthoFinder version 2.1.2 ( Emms and Kelly 2015 ).
	The MT boundary coordinates of Ostreococcus tauri (RCC4221 and RCC1115) were
	used to gauge BOC regions in each reference genome (supplementary table S1, Supplementary
	Material online). Mating type GFs candidates were defined as gene families built upon O. tauri

(RCC4221 and RCC1115) gene sets with validated homologous groups of ortholog and paralog genes located in the low GC regions in eight available genomes. For each gene (CDS) located on

  in total; supplementary table S6, Supplementary Material online) retrieved from the MMETSP(Keeling et al. 2014, Johnson et al.

	2019) and 1KP (Matasci et al 2014; accessed through https://github.com/ropensci/onekp)
	datasets, using tblastx (maximum e-value 1e-4) with the following filters: alignment length >50
	and amino acid identity > 60%. CDS from each Mamiellophyceae MMETSP transcriptome were
	predicted using TransDecoder (Haas et al. 2013) described in sup. material) with the
	re-assembled version of MMETSP (Johnson et al. 2019, https://zenodo.org/record/251828).
	In-depth phylogenetic analyses of individual hits from O . mediterraneus strain RCC2572

(MMETSP0929), O . lucimarinus strain BCC118000 (MMETSP0939), Micromonas MMETSP

  1,2* , Marc Krasovec 1 , L. Felipe Benites 1 , Stephane Rombauts3,4 , Mathieu Groussin 5 , Emmelien Vancaester3,4 , Jean-Marc Aury 6 , EvelyneDerelle 1,7 , Yves Desdevises 1 , Marie-Line Escande 1 , Nigel Grimsley 1 , Julie Guy 6 , Hervé Moreau 1 , Sophie Sanchez-Brosseau 1 , Yves van de Peer3,4,8 , KlaasVandepoele 3,4 , Sebastien Gourbiere 9 , Gwenael Piganeau 1* .

	Affiliations

1 Sorbonne Université, CNRS, UMR 7232 Biologie Intégrative des Organismes Marins BIOM, Observatoire Océanologique, F-66650 Banyuls-sur-Mer, France.

  mM boric acid, 1 mM EDTA at pH 8) with 2 mm of plug from each sample loaded into the wells. Electrophoresis was run in the CHEF-DR III (Bio-Rad) system at 14°C, 3 V cm -1 with 120°pulse angle for 45 h with a switch time of 90 s, followed by 27 h at a switch time of 140 s. After PFGE, DNA was visualised by immersing the gel in a solution of ethidium bromide. The gel was moved to flat-bottomed dish and enough 0.4 M NaOH was added to cover the gel for chemical denaturation of the DNA by incubation for 30 min at room temperature with agitation. Then the gel was washed three times for 10 min in a 6 ×

	SSC solution (20 × SSC, 3 M NaCl, 0.3 M Na 3 citrate, pH 7). Finally, the gel was dehydrated
	under vacuum (Hoefer inc. GD2000, Richmond, CA, USA).
	PCR (GoTaq, Promega) was used to amplify specific regions of the SOC, BOC, OmV2
	and the 18S rRNA gene (see Supplementary Table S3 for primer sequences) for use as DNA
	probes with the following conditions: initial denaturation for 2 min at 94°C; 30 cycles of
	denaturation for 30 s at 94°C, annealing for 30 s at 55°C, and extension for 45 s at 72°C; final
	extension for 5 min at 72°C. The PCR product was cleaned with Wizard®, Promega, SV Gel and

PCR Clean-Up System. The amplicons were randomly labelled with [α-32P]CTP (Perkin-Elmer ref BLU008H250UC) according to the manufacturer's instructions (Prime-a-Gene kit, Promega ref U1100) for use as a DNA probes. Dried gels were equilibrated in sufficient hybridisation buffer (6× SSC, 5× Denhardt's solution, 0.1% (v) sodium dodecyl sulphate, 10 μg•mL -1 tRNA)

  genome and predicted genes from O. mediterraneus RCC2590 were loaded into a

	sequence similarity search, both TribeMCL (version 10-201) and OrthoMCL (version 2.0, mcl
	inflation factor 3.0) were used to delineate gene families and subfamilies, respectively.
	Phylogenomic analysis of the O. mediterraneus nuclear genome was performed by
	concatenating the amino acid sequence from 188 single copy orthologs by TribeMCL within the
	Chlorophyta genomes ( O. mediterraneus , O. tauri , O. lucimarinus, O. sp RCC809, Micromonas
	pusilla strain CCMP1545, Micromonas sp RCC299, Bathycoccus prasinos , Arabidopsis
	thaliana , Chlamydomonas reinhardtii , Coccomyxa subellipsoidea C-169, Chlorella variabilis
	NC64A, Oryza sativa , Physcomitrella patens and Volvox carteri ) aligned using MUSCLE
	(version 3.8.31). This resulted in alignment of 148,028 positions of which 88,784 were
	informative. Similarly the phylogenetic topology across Mamiellales was determined by
	concatenating the alignment of 2,161 single copy genes, generated using MUSCLE, resulting in
	an alignment of 1,267,142 positions of which 444,911 were informative. The phylogenetic trees
	were generated using RaxML (version 8.2.8) (model PROTGAMMAWAG) with 100 bootstrap
	replicates.
	custom instance of pico-PLAZA (bioinformatics.psb.ugent.be/plaza/versions/pico-plaza/)
	containing 38 eukaryotic genomes (including Metazoa, Fungi, Chlorophyta, Embryophyta,
	Rhodophyta, Haptobionta and Stramenopiles, Supplementary Table S4). Following an
	'all-versus-all' BLASTP (version 2.2.27+, e-value threshold 10 -5 , max hits 500) protein

table 1 .

 1 in this issue), but the technical challenge of performing this for picoeukaryotes < 2 µm in size, such those in the Mamiellales, remain very challenging. Nevertheless, we showed here that -provided careful filtration of contaminations between dataset is performed -SAGs provide in-situ ecological information that would be lost in conventional isolation and culture processes, which select for the fastest growing cells in laboratory culture medium. GenBank accession numbers of 18S sequences used for phylogeny.

	Conventional culture-based approaches of strains and viruses are required to demonstrate the
	outcome of interactions by co-culture (93) and remain an essential tool for deciphering both
	intercellular and virus-host interactions in aquatic environments and interpreting environmental
	sequencing data.

table 3 .

 3 Taxonomic affiliation of non-target bacterial sequences for each SAG.

	SAG	Contig_name	Contig _length	BBH	Taxnomic_Affili ation	e-value
	SAG1 NODE_1039_length_403_cov_0.813218 403	Alphaproteobacteria bacterium MarineAlpha9_Bin7	Proteobacteria	9.90E-25
	SAG1 NODE_104_length_7693_cov_56.7194	7693	Prochlorococcus marinus	Cyanobacteria	4.10E-111
	SAG1 NODE_141_length_5335_cov_3.20625	5335	Bacillus jeotgali	Firmicutes	7.80E-85
	SAG1 NODE_216_length_2817_cov_2.26684	2817	Planktothrix agardhii	Cyanobacteria	1.00E-22
	SAG1 NODE_306_length_1604_cov_3.94319	1604	Verrucomicrobiae bacterium Tous-C4TDCM	Verrucomicrobia 2.20E-19
	SAG1 NODE_314_length_1496_cov_1.11103	1496	Microcystis aeruginosa	Cyanobacteria	1.40E-60
	SAG1 NODE_333_length_1395_cov_1.31716	1395	Spirosoma endophyticum	Bacteroidetes	1.00E-31
	SAG1 NODE_428_length_1000_cov_1.60423	1000	Fibrobacter sp. UWR3	Fibrobacteres	6.90E-19
	SAG1 NODE_586_length_729_cov_1.22997	729	Aeromonas	Proteobacteria	7.30E-18
	SAG1 NODE_688_length_615_cov_1.36786	615	Paenibacillus donghaensis	Firmicutes	5.70E-32
	SAG2 NODE_172_length_5205_cov_670.192	5205	Burkholderia multivorans	Proteobacteria	2.90E-07
	SAG2 NODE_343_length_2138_cov_27.0101	2138	Candidatus Nealsonbacteria bacterium RIFCSPLOWO2_01_FULL_43_32	Candidatus Nealsonbacteria 3.20E-13
	SAG2 NODE_360_length_1961_cov_10.0876	1961	Streptococcus	Firmicutes	2.80E-16
	SAG2 NODE_597_length_900_cov_7.95621	900	Deltaproteobacteria bacterium HGW-Deltaproteobacteria-17	Proteobacteria	8.20E-19
	SAG3 NODE_117_length_6472_cov_3.77762	6472	Bacteroidia bacterium	Bacteroidetes	3.30E-37
	SAG3 NODE_172_length_3394_cov_2.59179	3394	Bacillus jeotgali	Firmicutes	1.70E-69
	SAG3 NODE_261_length_1710_cov_1.63746	1710	Coprobacillus sp. 8_1_38FAA	Firmicutes	3.60E-07
	SAG3 NODE_279_length_1608_cov_78.5177	1608	Chryseobacterium sp. Leaf201	Bacteroidetes	5.90E-12
	SAG3 NODE_611_length_632_cov_2.06932	632	Cellvibrionales bacterium TMED47 Proteobacteria	1.90E-06
	SAG3 NODE_654_length_590_cov_1.89907	590	Thermoanaerobacterium saccharolyticum	Firmicutes	2.10E-39
	SAG3 NODE_980_length_404_cov_0.82808	404	Alphaproteobacteria bacterium MarineAlpha6_Bin5	Proteobacteria	3.20E-23
	SAG4 NODE_134_length_5831_cov_2.68369	5831	Bacillus jeotgali	Firmicutes	8.60E-85
	SAG4 NODE_301_length_1576_cov_1.85404	1576	Coprobacillus sp. 8_1_38FAA	Firmicutes	4.30E-07
	SAG4 NODE_630_length_630_cov_1.89739	630	Nitratireductor indicus	Proteobacteria	2.00E-08
	SAG5 NODE_122_length_1358_cov_1.88411	1358	Alphaproteobacteria bacterium RIFCSPHIGHO2_12_FULL_63_12 Proteobacteria	5.50E-11
	SAG5 NODE_142_length_1241_cov_1.66358	1241	Leptolyngbya sp. 'hensonii'	Cyanobacteria	8.90E-24
	SAG5 NODE_147_length_1212_cov_1.42005	1212	Spirosoma endophyticum	Bacteroidetes	2.30E-64
	SAG5 NODE_155_length_1155_cov_1.91545	1155	Synechococcus sp. PCC 7502	Cyanobacteria	1.20E-06
	SAG5 NODE_156_length_1155_cov_1.61273	1155	Rickettsiales bacterium	Proteobacteria	1.30E-24
	SAG5 NODE_19_length_7132_cov_7.80882	7132	Bacteroidia bacterium	Bacteroidetes	3.60E-37
	SAG5 NODE_248_length_844_cov_1.7803	844	Mycobacterium sp.	Actinobacteria	2.20E-10
	SAG5 NODE_272_length_789_cov_85709.4	789	Microcystis aeruginosa DIANCHI905	Cyanobacteria	3.20E-19
	SAG5 NODE_293_length_758_cov_2.19346	758	Bacteria		7.40E-82
	SAG5 NODE_35_length_4023_cov_2.81048	4023	Bacillus jeotgali	Firmicutes	2.70E-82
	SAG5 NODE_368_length_637_cov_1.15979	637	Nostoc sp. NIES-4103	Cyanobacteria	5.40E-09
	SAG5 NODE_489_length_526_cov_1.3121	526	Nostoc linckia	Cyanobacteria	2.50E-07
	SAG5 NODE_521_length_500_cov_1.18876	500	Moraxella oblonga	Proteobacteria	4.70E-08
						156

Table 1 .

 1 Classification, description, and quantities of genes and gene families (GFs) in O. tauri RCC4221 (MT-) and RCC1115 ( MT+ ) strains…….………….………….………….………….………….……………..…….….………..49 CHAPTER 3: Virus-host coexistence in phytoplankton under genomic lens ……………………………………..…….75

Table 1 .

 1 Comparison of the genomic features of sequenced Mamiellophyceae.…………………………..………....81 CHAPTER 4: Single cell ecogenomics reveals individual mating types and ssDNA viral infections in the smallest photosynthetic eukaryotes …………………………………………………………………...……………….……...121

Table 1 .

 1 Assembly statistics of 12 SAGs and statistics of reference genomes from the order Mamiellales……………………………….……….……………………………………………………….…..……130

Table 2 .

 2 Summary statistics of assemblies per taxonomic affiliation categories, assembly length and percent of reads recruited…………………….……….……….……….……….………………………………...………..……..…..132

Table 3 .

 3 Summary statistics of cpDNA and mtDNA manual assemblies from combined SAG sequence data……….………….……….……….……….……….……….……….……….……….……….……………...…133

VIB Center for Plant Systems Biology, Technologiepark 927, 9052 Ghent, Belgium.

Massachusetts Institute of Technology, Department of Biological Engineering, 500 Technology Square NE47-378, Cambridge, MA 02139.

Genoscope, Institut de biologie François-Jacob, Commissariat à l'Energie Atomique (CEA), Université Paris-Saclay, Evry, France.

Univ Brest, CNRS, IRD, Ifremer, LEMAR, F-29280 Plouzane, France.

Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria 0028, South Africa.

Laboratoire Génome et Développement des Plantes, Université de Perpignan Via Domitia, UMR5244, 52 Avenue Paul Alduy, 66860 Perpignan, France *gwenael.piganeau@obs-banyuls.fr, syau@icm.csic.es

ACKNOWLEDGMENTS

Acknowledgments: We are grateful to the Genotoul bioinformatic platform for access to the computer cluster, the GeT sequencing platform for the PacBio sequencing, the Gordon and Betty Moore Foundation for sequencing transcriptomes, and the BIOPIC platform for access to the cytometers and microscopes. We would like to acknowledge Adrien Cadoudal and Frederic Sanchez for performing an additional resistance evolution experiment of 24 independent lines of S3 inoculated with OmV2 to confirm systematic resistance acquisition in O. mediterraneus . Our thanks to Alice Penrose and Yohan Gourbiere for their help in the manual annotation of O. mediterraneus and visual inspection of TEM screens. We would like to apologize for the relevant references we could not include due to space limitations.

Acknowledgments

We would like to thank Tom Delmont and Olivier Jaillon from the Genoscope for information about the SAGs, Lilian Caesar for help with the figures, and the Genotoul platform ( www.genotoul.fr ) for cluster availability for bioinformatics analysis and Genoscope for sequencing. We are grateful to Fabien Burki for making a perl script for extracting taxonomic affiliation from DIAMOND outputs available.

Tara Oceans (which includes both the Tara Oceans and Tara Oceans Polar Circle expeditions) would not exist without the leadership of the Tara Expeditions Foundation and the continuous support of 23 institutes ( http://oceans.taraexpeditions.org ). We further thank the commitment of the following sponsors: CNRS (in particular Groupement de Recherche GDR3280 and the Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans-GOSEE), European Molecular Biology Laboratory (EMBL), Genoscope/CEA, The French Ministry of Research, and the French Government 'Investissements d'Avenir' programmes OCEANOMICS (ANR-11-BTBR-0008), FRANCE GENOMIQUE (ANR-10-INBS-09-08), MEMO LIFE (ANR-10-LABX-54), and PSL* Research University (ANR-11-IDEX-0001-02), Gordon and Betty Moore Foundation (award #3790) and the US National Science Foundation (awards OCE#1536989 and OCE#1829831) to MBS, as well as the Ohio Supercomputer for computational support. We also thank the support and commitment of agnès b. and Etienne Bourgois, the Prince Albert II de Monaco Foundation, the Veolia Foundation, Region Bretagne, Lorient Agglomeration, Serge Ferrari, Worldcourier, and KAUST. The global sampling effort was enabled by countless scientists and crew who sampled aboard the Tara from 2009-2013, and we thank MERCATOR-CORIOLIS and ACRI-ST for

providing daily satellite data during the expeditions. We are also grateful to the countries who graciously granted sampling permissions. The authors declare that all data reported herein are

Funding: This research was funded by the ANR grants REVIREC ANR-12-BSV7-0006-01, DECOVIR ANR-12-BSV7-0009 and PHYTNESS ANR-13-JSV6-0005. EV is funded by BOF project GOA 01G01715 and FB is funded by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. H2020-MSCA-ITN-2015-675752.

Abstract

Virus-microbe interactions in the ocean are commonly described by 'boom and bust' dynamics, whereby a numerically dominant microorganism is lysed and replaced by a virus-resistant one.

Here, we isolated a microalga strain and its infective dsDNA virus whose dynamics are characterized instead by parallel growth of both the microalga and the virus. Experimental evolution of clonal lines revealed that this viral production originates from the lysis of a minority of virus-susceptible cells, which are regenerated from resistant cells. Whole genome sequencing demonstrated that this resistant-susceptible switch involved a large deletion on one chromosome.

Mathematical modeling explained how the switch maintains stable microalga-virus population dynamics consistent with their observed growth pattern. Comparative genomics confirmed an ancient origin of this "accordion" chromosome despite a lack of sequence conservation.

Altogether, our results show how dynamic genomic rearrangements may account for a previously overlooked coexistence mechanism in microalgae-virus interactions.

Genome sequencing and assembly

Genome library preparation, sequencing, assembly and optical mapping were performed by GENOSCOPE (www.genoscope.cns.fr). Two libraries were prepared and sequenced using the Illumina Hi-Seq platform; a paired-end (PE) read library of insert size 272 bp and a mate-pair (MP) library of 5 230 bp insert size. DNA sequence reads were assembled using ALL-PATHS-LG assembler (46). At this stage, 99 scaffolds were obtained that aligned with eukaryotic sequences. Optical mapping was performed to further place the O. mediterraneus scaffolds in their correct order on the chromosome. This resulted in 19 optically mapped scaffolds corresponding to nuclear chromosomes and several low GC scaffolds corresponding to fragments of the SOC, organelles and OmV2. The organelles were assembled using ABySS from the Illumina Hi-Seq PE reads using the MP library for scaffolding (abyss-pe, lib = 'PE', mp = 'MP', k = 85, n = 10). Organelle genome completeness was evaluated by alignment to the complete organelle sequences of O. tauri . The two large contigs of the OmV2 genome obtained from the Illumina sequencing were scaffolded together manually using the assembly and visualisation tools available from the Geneious software www.geneious.com).

To resolve the highly repetitive SOC sequence, genomic DNA from RCC2590 and the evolved line MA3 were re-sequenced with the SMRT Technology PacBio RS II by the GetPlaGe sequencing platform in Toulouse, France as previously described (19). The raw data was assembled using HGAP3 (v2.3.0). The PacBio assemblies were checked manually with assembly and visualisation tools available from the Geneious software to identify the scaffolds corresponding to the SOC. Both RCC2590 and MA3 SOCs were assembled from telomere to telomere, the former comprising 5 scaffolds and the latter a single scaffold.

Genome annotation

Briefly, gene models were predicted using Eugene (release 4.1; eugene.toulouse.inra.fr).

Transcript information was provided to the gene-caller as follows: one paired-end Illumina RNAseq dataset was assembled into transcript contigs using a DBG assembly approach with high Kmer sizes to boost specificity during the assembly. Six O. mediterraneus strains

Analysis of the evolution of GC content

To reconstruct genomic GC contents along the tree of Ostreococcus , we used an ancestral sequence reconstruction approach to reconstruct genes sequences at the codon level and compute their GC contents at the tree nodes. We included 3 outgroups ( B. prasinos , M. pusilla CCMP1545 and M. commoda RCC299) in the reconstruction of ancestral GC contents of the four Ostreococcus lineages and selected all 2,161 single-copy genes universally present in these seven genomes as determined from the comparative genomic analysis.

We aligned all 2,161 universal single-copy protein families at the codon level with MACSE using default parameters and trimmed alignments for badly aligned positions with BMGE using a BLOSUM62 substitution matrix and other parameters set to their default values.

To both reduce computational burden and produce confidence intervals in estimates of ancestral GC contents, we employed a jackknife approach to subsample the 2,161 alignments and to build 100 concatenates containing each 100 randomly sampled genes. Each concatenate has an average size of 104,290 nucleotide positions (± 8,644), representing on average 34,763 codons, and so is expected to contain a sufficient amount of phylogenetic information to reconstruct ancestral GC contents. We further verified that these concatenates are faithful representations of each genome in terms of GC contents. We computed correlation coefficients between the average GC contents computed across all 2,161 genes and the GC contents of each of the 100 concatenates. We observed that all correlation coefficients were higher than 0.972, showing that these 100 jackknife sub-samples have the same properties than the original population of 2,161 genes, which allows us to infer ancestral genomic GC contents.

We first reconstructed the phylogenetic tree of each of the 100 concatenates to verify that each concatenate contains the same phylogenetic information on the relationships between the seven considered species. We built trees with FastTree (v. 2.1.8) using a GTR model and the CAT approximation with 20 categories to model the variation of evolutionary rates across sites.

Each phylogenetic reconstruction yielded a tree consistent with the reference species tree of the seven species. We used this topology to reconstruct ancestral sequences on all concatenates. We used the Yang and Nielsen (YN) substitution model for codons with different base frequencies at the three codon positions (F3x4) to model codon evolution. As the seven species have genomic Eight complete fully annotated 13 to 22 Mb genomes from three genera, Ostreococcus , Bathycoccus and Micromonas , are available from previously isolated clonal cultured strains and provide an ideal resource to explore the scope and challenges of analysing Single Cell Amplified Genomes (SAGs) isolated from a natural environment. We assembled data from 12 SAGs sampled during the Tara Oceans expedition to gain biological insights about their in-situ ecology, which might be lost by isolation and strain culture. Although the assembled nuclear genomes were incomplete, they were large enough to infer the mating types of four Ostreococcus SAGs. The systematic occurrence of sequences from the mitochondria and chloroplast, representing less than 3% of the total cell's DNA, intimates that SAGs provide suitable substrates for detection of non-target sequences, such as those of virions . Analysis of the non-Mamiellophyceae assemblies, following filtering out cross-contaminations during the sequencing process, revealed two novel 1.6 and 1.8 kb circular DNA viruses, and the presence of specific Bacterial and Oomycete sequences suggests that these organisms might co-occur with the Mamiellales. The SAG target assemblies recruit the overwhelming majority of reads, from a minimum of 82% of reads in SAG8 to 99.96% in SAG9 (Table 2). Target assemblies are fragmented and summed up to a maximum of 4.2 Mb (SAG2), corresponding to a maximum of one fourth of the expected genome size (SAG2, Bathycoccus , SAG10, Ostreococcus ). This modest genome representation is also reflected by the BUSCO analysis, with a maximum of 28.7 % of represented genes (SAG9), to 1% in SAG6, where the target sequences are overwhelmingly fully and freely available from the date of publication, with no restrictions, and that all of the analyses, publications, and ownership of data are free from legal entanglement or restriction by the various nations whose waters the Tara Oceans expeditions sampled in. This article is contribution number 91 of Tara Oceans. LFB was funded by the EU Horizon 2020 research and innovation programme, under the Marie Skłodowska-Curie grant agreement No. H2020-MSCA-ITN-2015-675752. We would also like to acknowledge three anonymous referees for constructive comments on a previous version of this manuscript.

Additional Information

Ethics

Not applicable.

Data Accessibility

SAGs assemblies analysed in this manuscript have been submitted to GenBank under BioProject PRJNA549236 with accession numbers VIAS00000000 (SAG1); VIAT00000000 (SAG2); VIAU00000000 (SAG3); VIAV00000000 (SAG4); VIAW00000000 (SAG5); VIAX00000000 (SAG6); VIAY00000000 (SAG7); VIAZ00000000 (SAG8); VIBA00000000 (SAG9); VIBB00000000 (SAG10); VIBC00000000 (SAG11); VIBD00000000 (SAG12) . Mitochondrial assemblies have been submitted to GenBank under accession MN243825 (Os_mt_TOSAG41), MN243826 (Mi_mt_TOSAG46), plastidial assemblies under accession MN243827 (Os_cp_TOSAG41) and MN243828 (Mi_cpTOSAG46).

Authors' Contributions

LFB and GP performed bioinformatics analyses. NP and MS performed single cell sorting and prior species' taxonomic affiliation. KL performed SAG sequencing. GP, LFB and NG designed the study.

All authors contributed to manuscript writing and editing.

Competing Interests

We have no competing interests.

Abstract

Mamiellophyceae algae are the basis of coastal marine environments. Despite their ecological importance, the aspects related to their organismal interactions remain enigmatic.

Single cell genomes (SCGs) from uncultivated samples can identify biotic associations, from sex to parasitism. In protists, sex is determined by the mating types ( MTs ), which are present in

Ostreococcus . Here, we used genetic data to answer: How did MTs evolve in this group? Can we find interaction signals in the SCGs? The analysis of the MT genes suggests an old divergence of the Ostreococcus MTs , and the presence of new MTs . Finally, using SCGs, we identified new viruses associated with Ostreococcus . We provide here a framework for the evolution of sex in this class and, using SCGs, we have identified new associations in environmental Mamiellophyceae.

Résumé