Samir Rezki

Claire Campion

Philippe Simoneau

Marie-Agnès Jacques

Ashley Shade

Matthieu Barret
email: matthieu.barret@inra.fr

Eric Nelson

Tim Mauchline
email: tim.mauchline@rothamsted.ac.uk

Tom Curtis
email: tom.curtis@newcastle.ac.uk

Steven Kembel
email: kembel.steven_w@uqam.ca

Assembly of seed-associated microbial communities within and across successive plant generations

Keywords: plant microbiota, seed, neutral processes seed-associated microbial community, heritability, community assembly, dispersion, diversification

come

We wish to submit our manuscript entitled "Assembly of seed-associated microbial communities within and across successive plant generations" for review to Plant and Soil's special issue: Seeds and Microbes. This manuscript is a revised version of manuscript PLSO-D-16-01789 that has been submitted in the special issue Seeds and Microbes of Plant and Soil. We tried to address all the comments made by the reviewers.

The present work assessed the structure and composition of the seed microbiota of radish (Raphanus sativus) across three successive plant generations. The relative importance of niche and neutral processes (ecological drift and dispersal) in the assembly of the seed microbiota is investigated at the individual plant level. Overall we found that seed-associated microbial communities are dominated by few bacterial and fungal taxa whose distributions cannot be explained by neutral processes. However, neutral processes are probably responsible for variation in community composition of the vast majority of rare taxa associated to radish seeds.

We confirmed that all the material presented in the current manuscript is original research and has neither been published nor been submitted for publication elsewhere. We would sincerely appreciate if you would consider this article for review and would welcome any queries you might have regarding our submission.

Authors of this manuscript confirm that all the work presented in the manuscript is original and report no conflicts of interest.

Covering Letter

Yours faithfully, Matthieu Barret

Corresponding author Email: matthieu.barret@angers.inra.fr Tel: +33 2 41 22 57 16 Fax: +33 2 41 22 57 55

Introduction

Plants have co-evolved with complex microbial communities which are known collectively as the plant microbiota. The plant microbiota can promote plant growth and plant health [START_REF] Muller | The Plant Microbiota: Systems-Level Insights and Perspectives[END_REF]. For instance, plant-associated microbial communities can modulate biomass accumulation [START_REF] Sugiyama | Relationships between Arabidopsis genotype-specific biomass accumulation and associated soil microbial communities[END_REF], metabolites production [START_REF] Badri | Potential impact of soil microbiomes on the leaf metabolome and on herbivore feeding behavior[END_REF], drought tolerance [START_REF] Lau | Rapid responses of soil microorganisms improve plant fitness in novel environments[END_REF][START_REF] Rolli | Improved plant resistance to drought is promoted by the root-associated microbiome as a water stressdependent trait[END_REF] and flowering time [START_REF] Wagner | Natural soil microbes alter flowering phenology and the intensity of selection on flowering time in a wild Arabidopsis relative[END_REF][START_REF] Panke-Buisse | Selection on soil microbiomes reveals reproducible impacts on plant function[END_REF][START_REF] Dombrowski | Root microbiota dynamics of perennial Arabis alpina are dependent on soil residence time but independent of flowering time[END_REF]. Moreover, the plant microbiota can also increase host resistance to foliar or root pathogenic agents [START_REF] Busby | Fungal endophytes: modifiers of plant disease[END_REF][START_REF] Ritpitakphong | The microbiome of the leaf surface of Arabidopsis protects against a fungal pathogen[END_REF][START_REF] Mendes | Deciphering the Rhizosphere Microbiome for Disease-Suppressive Bacteria[END_REF][START_REF] Santhanam | Native root-associated bacteria rescue a plant from a sudden-wilt disease that emerged during continuous cropping[END_REF].

Owing to the beneficial effects of the microbiota on plant fitness, the relative importance of different community assembly processes in determining its structure over space and time is of great interest [START_REF] Paredes | Giving back to the community: microbial mechanisms of plantsoil interactions[END_REF]. Community assembly processes could be divided into four main forces, namely dispersal, diversification, drift and selection (Vellend 2010, [START_REF] Nemergut | Patterns and Processes of Microbial Community Assembly[END_REF]. Over recent years many research groups have investigated the importance of selection in determining plant-associated microbial assemblage structure. For instance, it is now widely accepted that rhizosphere bacterial assemblages are partly determined by selection [START_REF] Bulgarelli | Structure and functions of the bacterial microbiota of plants[END_REF]. Indeed, environmental-filtering such as soil physiochemical properties and to a lesser extend host-filtering are involved in variation of bacterial root microbiota profiles [START_REF] Bulgarelli | Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota[END_REF][START_REF] Lundberg | Defining the core Arabidopsis thaliana root microbiome[END_REF][START_REF] Peiffer | Diversity and heritability of the maize rhizosphere microbiome under field conditions[END_REF][START_REF] Edwards | Structure, variation, and assembly of the root-associated microbiomes of rice[END_REF][START_REF] Dombrowski | Root microbiota dynamics of perennial Arabis alpina are dependent on soil residence time but independent of flowering time[END_REF]. Moreover environmental-and hostfiltering are also important drivers of leaf-associated microbiota composition (Bodenhausen et al., 2013[START_REF] Horton | Genome-wide association study of Arabidopsis thaliana leaf microbial community[END_REF][START_REF] Wagner | Host genotype and age shape the leaf and root microbiomes of a wild perennial plant[END_REF]. In comparison to selection, the relative importance of dispersion, diversification and ecological drift in driving assembly of plantassociated microbial communities has not been well investigated. To our best knowledge, only one study has investigated the relative importance of selection, dispersion and ecological drift in the assembly of the leaf microbiota [START_REF] Maignien | Ecological Succession and Stochastic Variation in the Assembly of Arabidopsis thaliana Phyllosphere Communities[END_REF]. According to the results presented in this work, community membership of the phyllosphere microbiota is shaped by selection, while community composition is driven by diversification and ecological drift [START_REF] Maignien | Ecological Succession and Stochastic Variation in the Assembly of Arabidopsis thaliana Phyllosphere Communities[END_REF].

Microbial entities of the plant microbiota can be either acquired from the surrounding environment (horizontal transmission) or directly from the parent (vertical transmission). To date, the relative contribution of horizontal and vertical transmission in the ultimate composition of the plant microbiota is unclear [START_REF] Shade | Ecological patterns of seed microbiome diversity, transmission, and assembly[END_REF]. On the one hand, recruitment of microbes from the surrounding bulk soil in the rhizosphere strongly support the role of horizontal transmission [START_REF] Bulgarelli | Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota[END_REF][START_REF] Edwards | Structure, variation, and assembly of the root-associated microbiomes of rice[END_REF]. On the other hand, the presence of conserved seed-associated micro-organisms across multiple plant generations (Johnson-Monje & Raizada 2011;Hardoim et al., 2012) suggest that some members of the plant microbiota are vertically transmitted. Although the contribution of the seed-associated microorganisms in shaping the ultimate composition of the plant microbiota is under debate, studying the biological and ecological processes involved in the assembly of seed-associated microbial community can have important implication for plant growth and health. Indeed, the composition of the seed microbiota can contribute to key seed traits such as seed preservation [START_REF] Chee-Sanford | Do microorganisms influence seed-bank dynamics ?[END_REF] or release of seed dormancy [START_REF] Goggin | A potential role for endogenous microflora in dormancy release, cytokinin metabolism and the response to fluridone in Lolium rigidum seeds[END_REF]. Occasionally, seed transmissions of Shiga toxin producers could dramatically impact the sanitary quality of seed samples (King et al., 2011). From an epidemiological angle, seed transmission of plant pathogens serves as a major method of dispersal and is therefore important for predicting disease emergence and spread. Very low degrees of seed contamination by bacterial pathogens can lead to efficient plant colonization [START_REF] Darrasse | Contamination of bean seeds by Xanthomonas axonopodis pv. phaseoli associated with low bacterial densities in the phyllosphere under field and greenhouse conditions[END_REF]. Furthermore, seed transmission of phytopathogens can take place on non-host plants [START_REF] Darrasse | Transmission of Plant-Pathogenic Bacteria by Nonhost Seeds without Induction of an Associated Defense Reaction at Emergence[END_REF][START_REF] Darsonval | The Type III secretion system of Xanthomonas fuscans subsp. fuscans is involved in the phyllosphere colonization process and in transmission to seeds of susceptible beans[END_REF], which can then serve as a reservoir of plant pathogens. Finally, the seed microbiota can have early or late consequences on plant growth and health with decrease of germination rate [START_REF] Nelson | Microbial dynamics and interactions in the spermosphere[END_REF][START_REF] Munkvold | Seed pathology progress in academia and industry[END_REF] or enhancement of ear emergence time [START_REF] Mitter | A new approach to modify plant microbiomes and traits by introducing beneficial bacteria at flowering into progeny seeds[END_REF].

Recent diversity surveys of the seed microbiota showed a high level of variation in microbial assemblages composition [START_REF] Lopez-Velasco | Diversity of the spinach (Spinacia oleracea) spermosphere and phyllosphere bacterial communities[END_REF][START_REF] Links | Simultaneous profiling of seed-associated bacteria and fungi reveals antagonistic interactions between microorganisms within a shared epiphytic microbiome on Triticum and Brassica seeds[END_REF][START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF][START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF][START_REF] Rezki | Differences in stability of seed-associated microbial assemblages in response to invasion by phytopathogenic microorganisms[END_REF]. Based on these previous studies, it seems that selection by the host plant is not a major driver of community assembly [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF][START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF]. In contrast, environmental-filtering is shaping the structure of seedassociated fungal assemblages [START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF]. Since the high variation in community composition observed across seed samples remains difficult to explain solely by environmentalfiltering, other ecological forces such as dispersal, diversification and ecological drift [START_REF] Nemergut | Patterns and Processes of Microbial Community Assembly[END_REF] may play an important role in assembly of the seed microbiota.

The objective of the present work was to assess the relative importance of these ecological processes in the assembly of the seed-associated microbial communities. To do so, we employed a theoretical framework based on neutral theory that has been successfully adapted to interpret the composition of host-associated microbial communities [START_REF] Venkataraman | Application of a neutral community model to assess structuring of the human lung microbiome[END_REF][START_REF] Burns | Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development[END_REF][START_REF] Li | Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets[END_REF]. Instead of considering differences of ecological fitness between community members as the main driver of community assembly (i.e. nichebased theory), neutrality hypothesis assumes that community members are ecologically equivalents. Under this assumption, the extinction of a local individual creates an empty site that is either fill by the offspring of a local individual or by immigration of a new community member. We used radish (Raphanus sativus var. Flamboyant5) as a model system since this plant has a high multiplication rate (one plant produces 500 seeds on average), allowing analysis of the seed microbiota for individual plants. The structure and diversity of seed-associated microbial communities were analysed on seed samples collected on individual plants during three successive generations through community profiling approaches. Based on this profiling, we observed the frequency of taxa occurrence in local communities (seed samples collected on individual plant) and their abundances across the metacommunity (all seed samples collected on the different plants of the same generation) and compared the observed OTU distribution to an estimated OTU distribution calculated with a neutral community model. According to the OTUs distribution, it seems that seed-associated microbial communities are composed of few dominant taxa that are selected by the host or the environment and multiple rare taxa whose distributions can be explained by neutral processes.

Material & Methods

Seed collection

Radish seeds (Raphanus sativus var. Flamboyant5, Vilmorin) were sown in March 2013 at the FNAMS experimental station (47°28'12.42" N, 0°23'44.30" W, Brain-sur-l'Authion, France).

Mature seeds of the first plant generation were collected manually on individual plant and immediately submitted to DNA extraction. To limit border effect, plants located at the border of the experimental plot were not sampled. The remaining seeds in the experimental plot were harvested mechanically with a thresher. Seed samples collected mechanically were stored at 9°C at a relative humidity of 60% for 6 months. These mechanically harvested seeds were used for sowing in the following season. The same procedure was repeated for seeds of the second (2014) and third generation (2015).

DNA extraction was performed on 73 seed samples collected manually from individual plants in 2013 (9 plants), 2014 (32 plants) and 2015 (32 plants). In addition, DNA extraction was performed on 3 subsamples of 1,000 seeds for each seed lot harvested mechanically in 2013, 2014 and 2015 (9 subsamples in total). Seeds were initially soaked in 25 mL of phosphate buffer saline (PBS) supplemented with 0.05% (v/v) of Tween® 20 during 2 hours and 30 minutes at room temperature under constant agitation (140 rpm). Suspensions were centrifuged (6000 x g, 10 min, 4°C) and pellets were resuspended in approximately 2 ml of supernatant and transferred in microtubes. Total DNA was extracted with the Power Soil DNA Kit (MoBio Laboratories) following procedure described earlier [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF].

Libraries construction and sequencing

Community profiling approaches were performed on 82 environmental DNA samples corresponding to seed samples harvested manually (73) or mechanically (9) from three consecutive plant generations. Amplifications of one bacterial marker (gyrB) and one fungal marker (ITS1) were performed with the primer sets gyrB_aF64/gyrB_aR353 [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF] and ITS1F/ITS2 (Buée et al., 2009) following procedures described earlier [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF]. Amplicon libraries were mixed with 5% PhiX control according to Illumina's protocols.

A total of three sequencing runs was performed for this study with MiSeq Reagent Kits v3 (600 cycles).

Data analysis

The choice of gyrB as a bacterial molecular marker is dictated by its lowest taxonomic resolution (species-level) in comparison to classic molecular markers based on the hypervariable regions of the 16S rRNA gene [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF]. In addition, gyrB is a singlecopy gene that encodes the β subunit of the bacterial gyrase, which then limits the overestimation of taxa possessing multiple copies of rrn operons. The occurence of gyrB was investigated in a set of 32,062 bacterial genomic sequences available in the IMG database v4 [START_REF] Markowitz | IMG: the integrated microbial genomes database and comparative analysis system[END_REF] at the time of analysis (10 th December 2015). Coding sequences that belong to the protein family TIGR01059 and KO2470 were defined as GyrB orthologs and retrieved for further analysis (30,627 hits found in 30,175 genomic sequences). The corresponding nucleotidic sequences were aligned against a reference gyrB alignment [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF] with the align.seqs command of mothur 1.36.1 [START_REF] Schloss | Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities[END_REF] using the following parameters : align=gotoh, match=3, mismatch=-2, gapopen=-50, gapextend=-50, ksize=8. Sequences that did not aligned (102) were discarded and only unique sequences (haplotypes) were conserved in the reference alignment (10,427 haplotypes). According to the gANI cliques defined previously by Varghese and collaborators [START_REF] Varghese | Microbial species delineation using whole genome sequences[END_REF], the gyrB marker has the best precision (0.964) and sensitivity (0.955) at a genetic distance of 0.02 (98% identity cutoff).

Sequence analyses were performed as described earlier by [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF] using a sequence curation pipeline [START_REF] Kozich | Development of a dualindex sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform[END_REF] within mothur 1.36.1 [START_REF] Schloss | Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities[END_REF].

Briefly, gyrB sequences were aligned against a gyrB reference alignment composed of 10,427 haplotypes. Chimeric sequences were detected and removed from the dataset using the command chimera.uchime [START_REF] Edgar | UCHIME improves sensitivity and speed of chimera detection[END_REF]. Taxonomic affiliation of gyrB sequences was performed with a Bayesian classifier [START_REF] Wang | Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[END_REF] implemented in the classify.seqs command against an in-house gyrB database containing 30,525 representative sequences at a 80% bootstrap confidence score. All sequences not affiliated at the phylum level and containing a predicted stop codon were discarded from the dataset. A de novo clustering method (i.e. average-linkage clustering at a 98% identity cut-off) was performed with the cluster.split command for assigning gyrB sequences to operational taxonomic units (OTUs).

The variable ITS1 regions of the fungal internal transcribed spacer were extracted with the Perl-based software ITSx 1.0.4 (Bengtsson-Palme et al., 2013). Reference-based clustering was performed with UCLUST 1.2.22 algorithm [START_REF] Edgar | Search and clustering orders of magnitude faster than BLAST[END_REF] at a 97% identity cut-off against the UNITE 7.1 database [START_REF] Abarenkov | The UNITE database for molecular identification of fungi -recent updates and future perspectives[END_REF].

Observed richness (number of OTUs) and evenness (estimated with Simpson's reciprocal index) were calculated with the R package phyloseq [START_REF] Mcmurdie | phyloseq : An R package for reproductible interactive analysis and graphics of microbiome census data[END_REF] on OTU tables rarefied to 5,000 sequences per sample. Differences in richness and evenness between variables were assessed by one-way ANOVA with post-hoc Tukey's HSD test.

Differences in community membership and composition between plant generations

were assessed with Jaccard and Bray-Curtis indices, respectively. Jaccard and Bray-Curtis indices were calculated on OTU tables transformed to even sampling depth (OTU count divided by the number of read per sample and multiply by 1,000,000). Principal coordinate analysis (PCoA) was used for ordination of Jaccard and Bray-Curtis distances. Permutational multivariate analysis of variance (PERMANOVA; [START_REF] Anderson | A new method for non-parametric multivariate analysis of variance[END_REF] was carried out to assess the importance of the plant generation on seed-associated microbial community profiles. To quantify the contribution of the plant generation in microbial community profiles, canonical analysis of principal coordinates was performed with the function capscale of the R package vegan 2.4.2 (Oksanen, 2017) followed with PERMANOVA with the function adonis. Changes in relative abundance of OTUs between the different plant generations (2013, 2014 and 2015) were assessed with likelihood ratio test (LRT) with the R package DESeq2 1.14.1 [START_REF] Anders | Differential expression analysis for sequence count data[END_REF]. OTU with a corrected p-value < 0.01 and a log2FC > |2| were considered as differentially abundant between the different plant generations.

Testing the importance of neutral processes in community assembly

The role of neutral processes in assembly of seed-associated microbial communities was estimated by fitting the Sloan neutral community model for prokaryotes [START_REF] Sloan | Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data[END_REF] to the observed OTU distribution. The conceptual framework on which is based this model is as follow: a large community (a.k.a metacommunity), which is composed of all micro-organisms associated to seed samples collected on all plants located in the same experimental plot, serves as a source of immigrants to a local community that is composed of micro-organisms associated to one seed sample collected from one individual plant. Since neutrality hypothesis assumes that community members are ecologically equivalents, changes in structure of the local community is due to the death of an individual that is either replaced by an immigrant or by local reproduction.

We assessed the capability of the Sloan neutral community model for prokaryotes to estimate the distribution of seed-associated micro-organisms. The Sloan model estimates the rate of immigration (m) into the local community by comparing OTU frequency across multiple samples [START_REF] Sloan | Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data[END_REF]. The Sloan model predicts that abundant entities in the large community are widespread across samples since their dispersions could occur by chance, while rare members are more likely to be lost by drift in the local community. We used a custom R script written by Burns and collaborators for fitting the Sloan neutral community model to OTU distribution [START_REF] Burns | Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development[END_REF]. The fit of Sloan model was compared with the fit of a binomial distribution model using the Akaike information criterion of each model [START_REF] Burns | Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development[END_REF].

Binomial distribution model is used for assessing the importance of random sampling on community structure in absence of drift and dispersal limitation [START_REF] Sloan | Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data[END_REF].

The validity of prediction of neutral community models with barcoding datasets has been recently assessed by Sommeria-Klein and collaborators (2016). According to this study, neutral-model inference is affected by the number of reads per sample, which should be smaller than the number of sampled individuals (Sommeria- [START_REF] Sommeria-Klein | Inferring neutral biodiversity parameters using environmental DNA data sets[END_REF]. This limitation could be easily tested by subsampling the number of reads and assessing that the estimators of immigration are unchanged. The number of sequences per sample was then rarefy to 1,000 and 5,000 counts before fitting both neutral community models.

Results

The assembly of radish seed-associated microbial communities was monitored across three plant generations (2013, 2014 and 2015) through community profiling approach. A total of 73 seed samples were collected manually from individual plant in 2013 (9 plants), 2014 (32 plants) and 2015 (32 plants). Seeds of the remaining plants in the experimental plot were harvested with a threshing machine and used for sowing the following year. Since manual and mechanical harvesting can result in differences in composition of seed-associated microbial community, three subsamples of 1,000 mechanically-harvested seeds per year (9 subsamples in total) were also subjected to community profiling, therefore resulting in 82 seed samples in total.

Bacterial and fungal assemblage profiles were estimated after assignation of gyrB and ITS1 sequences to operational taxonomic units (OTUs). Overall, 43,102 bacterial OTUs and 25,618 fungal OTUs were detected across all seed samples. While the number of observed bacterial OTUs was not significantly different between manual-and mechanically-harvested seed samples, fungal richness was significantly higher in mechanically-harvested seed samples (P < 0.01, one-way ANOVA with post hoc Tukey's HSD test, Fig. S1). However, this increase in fungal richness did not impact evenness (as assessed with Simpson's reciprocal index, Fig. S1). As the level of alpha-diversity associated to seed samples used for sowing (mechanically harvest) was comparable to the alpha-diversity of seed samples collected from individual plants, the harvesting method is not involved in variation of microbial community composition across years. Therefore, to investigate variation in seed-associated microbial assemblages between individual plants, only seed samples collected manually were considered in the subsequent analyses.

Assembly of the seed microbiota over successive plant generations

The assembly patterns of radish seed microbiota was monitored among samples collected manually in 2013, 2014 and 2015. First, we compared microbial richness and evenness over the three plant generations (Fig. 1). A significant increase in bacterial and fungal richness (Fig. 1A and Fig. 1B) was observed for samples collected in 2015 vs. those collected the previous years (P < 0.01, one-way ANOVA with post hoc Tukey's HSD test). However, this increase in microbial richness was not associated with significant differences in microbial evenness over the successive plant generations (Fig. 1C and Fig. 1D).

Similarity in community membership and community composition was estimated through calculation of Jaccard and Bray-Curtis similarity indices, respectively.Ordination of Jaccard and Bray-Curtis similarity indices with principal coordinate analysis (PCoA) revealed a significant clustering (PERMANOVA, P < 0.001) of seed-associated fungal communities according to the plant generation (Fig. 2A and Fig. 2B). In contrast, seed-associated bacterial communities were only significantly clustered for the third plant generation (P < 0.001; Fig. 2 C and Fig. 2D). Jaccard ordinations had higher explanatory value and more discrete clustering by year than Bray-Curtis, suggesting that inter-annual differences in community structure can be attributed to patterns in the presence and absence of taxa (e.g. many taxa observed exclusively in one year). The relative contribution of the plant generation in community profiles was further investigated through canonical analysis of principal coordinates (CAP) followed by PERMANOVA. According to CAP analyses, the plant generation explained 22% and 32% of variation in bacterial and fungal community membership and 27% and 39% of bacterial and fungal community composition (PERMANOVA, P < 0.001).

To determine if some OTUs were specifically associated with one particular generation, we performed likelihood ratio tests (LRT) with DESeq2 on OTU table. LRT revealed that the relative abundances of 25 bacterial OTUs were significantly different (pvalue ≤ 0.01 and log2FC ≥ |2|) between the first and second plant generations (Fig. S2A). The number of significant bacterial OTUs with differences in relative abundant increases to 62 between the second and third plant generation (Fig. S2E). Significant changes in relative abundances of 69 and 125 fungal OTUs were also detected between 2013 vs 2014 and 2014 vs 2015, respectively (Fig. S2B and Fig. S2F). In conclusion, differences in richness, diversity, community membership, community composition and OTUs relative abundance indicate a significant contribution of plant generation and/or harvest year on the structure of seed-associated microbial communities.

Assembly of seed-associated microbial communities among individual plants within the same harvest year

Results obtained in the previous subsection have shown that plant generation and/or harvest year are important drivers of the structure of the seed microbiota. However, variation in richness (Fig. 1) and community composition (Fig. 3) of the radish seed microbiota were observed between seed samples collected the same year on distinct individual plants. Overall, the radish seed microbiota is mainly composed of 2 bacterial genera, namely Pantoea and Pseudomonas (Fig. 3A), and 2 fungal genera: Alternaria and Cladosporium (Fig. 3B). While the presence of these microbial genera in seed samples was relatively conserved across individual, their relative abundances were variables (Fig. 3A and Fig. 3B).

To further evaluate variation in community membership and composition of the radish seed microbiota, we counted the number of OTUs that were conserved among all individual plants (core microbiome, Shade & Handelsman 2012). Among the 43,102 bacterial OTUs detected in the gyrB dataset, only three were observed in all seed communities. These three bacterial OTUs are affiliated to Pantoea agglomerans, Pseudomonas viridiflava and Erwinia tasmaniensis (Table 1). Regarding fungal communities, nineteen fungal OTUs among 25,618 OTUs detected were conserved in all seed samples. Among these 19 fungal OTUs, 14 were affiliated to the Alternaria genus (Table 1).

Although, the core fraction of the radish seed microbiota was relatively restricted in OTU number, it was composed of highly abundant taxa, representing on average 70% and 87% of all bacterial and fungal reads, respectively. Despite their strong conservations across individuals, the relative abundance of the core members of the radish seed microbiota varies greatly between seed samples (Fig. S3). For instance the relative abundance of bacterial OTU00001, which is affiliated to P. agglomerans, ranges from 7% to 82% within seed samples collected in 2014 (Fig. S3A). Shift in relative abundance of fungal OTUs was also important between seed samples, with variation from 4% to 43% for OTU00002 (Cladosporium) in 2014 (Fig. S3B). This variability of community composition in seed samples collected from the same plant genotype grown on the same experimental plot, suggest that non-selective processes such as dispersal, drift and diversification may be involved in community assembly of the seed microbiota.

Neutral processes are involved in intra-annual community assembly of the seed microbiota

In order to investigate the relative role of dispersal and ecological drift in shaping seedassociated microbial community, we used a conceptual framework based on neutral theory. In this conceptual framework, every seed sample harvested from one individual plant represents a local community that is part of a larger metacommunity corresponding to all seed samples collected on the different plants of the same generation. Based on the microbial community profiles obtained with gyrB and ITS1 sequences, we observed the frequency of OTU occurrence in local communities and their abundance across the metacommunity.

First, the fit of the Sloan model to the observed OTU distribution was used for assessing the relative importance of dispersal limitation and ecological drift. Since neutral-model inference is affected by the number of reads per sample [START_REF] Sommeria-Klein | Inferring neutral biodiversity parameters using environmental DNA data sets[END_REF], the number of sequences per sample was either rarefy to 1,000 or 5,000 counts before fitting the Sloan neutral community model [START_REF] Sloan | Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data[END_REF]. Both rarefaction procedures did not significantly impact the estimated migration rate (Table 2). Hence the largest dataset (5,000 counts per sample) was used in subsequent analyses. Overall, the estimated migration rate was more important for seed-associated fungal communities in comparison to seed-associated bacterial communities (Table 2). The goodness of fit of Sloan model was estimated for each plant generation by root-mean square error (RMSE, Fig. 4). Frequency of bacterial and fungal OTUs occurrence within local community was adequately described the neutral model for seed collected in 2014 and 2015 with RMSE < 0.1 (Fig. 4). Larger differences between observed OTUs occurrence and predicted OTUs occurrence were reported for microbial communities associated to seed harvested in 2013 (RMSE = 0.12 and 0.14 for bacterial and fungal OTU datasets, respectively). This increase in RMSE values could be explained by the limited number of samples employed (n =9) in 2013. In order to estimate the effect of dispersal and drift on local microbial community structure, we compared the fit of the Sloan model to the fit of a binomial distribution model. Binomial distribution model is used for assessing the importance of random sampling on community structure in absence of drift and dispersal limitation [START_REF] Sloan | Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data[END_REF]. According to Akaike information criterion (AIC), both models performed equally well (Table 2), therefore suggesting that dispersal, ecological drift and random sampling are involved in local assembly of seed-associated bacterial communities.

To identify microbial taxa that are potentially subjected to deterministic processes, we compared the observed OTU frequency to the predicted OTU frequency by Sloan model. OTUs that are found more frequently than estimated could represent microbial taxa that are positively selected by the host or the environment, whereas OTUs that are less frequent than expected could represent taxa negatively selected. Using the 95% confidence interval of the Sloan neutral model we detected bacterial and fungal taxa that depart from the estimated neutral distributions (Fig. 4). Interestingly only a subset of microbial taxa consistently diverged from neutral distribution across the three plant generation (Table 3). A total of three bacterial OTUs related to the Pseudomonas fluorescens group were less frequent than expected by Sloan neutral model (Table 3), and could represent taxa that under negative selection. In contrast, one bacterial and five fungal OTUs possessed a higher observed frequency for each plant generation. These putative positively-selected taxa correspond to one bacterial endophyte affiliated to Plantibacter flavus and 5 OTUs related to the Alternaria genus (Table 3) that are not part of the radish seed core microbiota.

Discussion

Seeds are involved in the transmission of microorganisms from one plant generation to another and consequently may act as the initial inoculum source for the plant microbiota [START_REF] Truyens | Bacterial seed endophytes: genera, vertical transmission and interaction with plants[END_REF][START_REF] Barret | Plant microbiota affects seed transmission of phytopathogenic microorganisms[END_REF]. From an epidemiological point of view, seed transmission of phytopathogenic microorganisms represents an important mean of pathogen dispersion and is therefore significant in emergence of disease [START_REF] Nelson | Microbial dynamics and interactions in the spermosphere[END_REF]. For these reasons, exploring (i) the transmission of seed-microbial communities across multiple generations and (ii) the processes involved in community assembly is of interest to control plant diseases [START_REF] Shade | Ecological patterns of seed microbiome diversity, transmission, and assembly[END_REF].

In the present study, we investigated the structure of microbial communities associated to several seed samples collected on different plant individuals during three successive plant generations. Based on the molecular markers employed in this work, seed microbiota composition and structure were distinct between plant generations. These differences in community structure across successive generations may solely be due to annual fluctuations in local weather conditions. Indeed, it is well accepted that climatic changes influence the composition of soil and plant-associated microbial communities [START_REF] Compant | Climate change effects on beneficial plantmicroorganism interactions[END_REF][START_REF] Classen | Direct and indirect effects of climate change on soil microbial and soil microbial-plant interactions: What lies ahead?[END_REF]. Other variables such as the type of cultivated plants that surrounded the experimental plots could also be involved in the observed variation in community composition.

Recent work indicates that emigration of epiphytic bacteria and fungi from plants surfaces are important local sources of airborne micro-organisms and therefore of the surrounding plants [START_REF] Lymperopoulou | Contribution of Vegetation to the Microbial Composition of Nearby Outdoor Air[END_REF]. Although the same experimental plot was employed during the course of this study, cultivated plant species in the immediate vicinity of the radish plants were not controlled between the different years and could account for the observed diversity.

While generation-specific variation was observed within seed-associated microbial communities, highest variation was found between seed samples collected the same year on different individual plants. As most diversity surveys of seed-associated microbial communities are performed on seed samples consisting of multiple plant entities [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF][START_REF] Links | Simultaneous profiling of seed-associated bacteria and fungi reveals antagonistic interactions between microorganisms within a shared epiphytic microbiome on Triticum and Brassica seeds[END_REF][START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF], this source of variation is usually ignored. Overall only three bacterial OTUs and 19 fungal OTUs were detected in all seed samples collected in this work.

These core OTUs are affiliated to bacterial (e.g. Pantoea agglomerans or Pseudomonas viridiflava) and fungal taxa (Alternaria or Cladosporium) frequently associated to seed of various plant species [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF][START_REF] Hodgson | Vertical transmission of fungal endophytes is widespread in forbs[END_REF][START_REF] Links | Simultaneous profiling of seed-associated bacteria and fungi reveals antagonistic interactions between microorganisms within a shared epiphytic microbiome on Triticum and Brassica seeds[END_REF][START_REF] Rezki | Differences in stability of seed-associated microbial assemblages in response to invasion by phytopathogenic microorganisms[END_REF][START_REF] Truyens | Bacterial seed endophytes: genera, vertical transmission and interaction with plants[END_REF].

The fluctuations in microbial community composition observed between seed samples collected on different plant individuals could be explained by neutral-based processed. The Sloan neutral model employed in this work was able to predict the distribution of microbial taxa across seed-associated microbial communities, suggesting that ecological drift and dispersal generate a significant amount of diversity. Given the small value of estimated migration rate for seed-associated bacterial communities (m = 0.04), it seems that ecological drift is an important driver of bacterial community assembly. The importance of ecological drift in community assembly has been previously reported in communities (i) under weak host selection and (ii) where the vast majority of taxa are in low relative abundances [START_REF] Nemergut | Patterns and Processes of Microbial Community Assembly[END_REF]. These two features are frequently encountered in seed-associated bacterial communities.

Indeed, the overall composition of seed-associated bacterial communities is not shaped by the host genotype [START_REF] Barret | Emergence Shapes the Structure of the Seed Microbiota[END_REF][START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF]. Moreover, seed-associated microbial communities are composed of few abundant entities and a multitude of low-abundance members [START_REF] Rezki | Differences in stability of seed-associated microbial assemblages in response to invasion by phytopathogenic microorganisms[END_REF] that might be prone to extinction at the local level.

Regarding fungal taxa, it seems that the estimated migration rate is responsible for the observed variation in structure of seed-associated fungal communities. This results is not in accordance with the biogeographical diversity observed for fungal communities, which has been primarily related to dispersal limitation of these micro-organisms [START_REF] Peay | Dimensions of biodiversity in the Earth mycobiome[END_REF]. However, at a finer spatial scale, such as the experimental plot employed over the course of this study, dispersal limitation should be rather limited and passive dispersion of spore-forming organisms by water or wind facilitated, therefore resulting in stochastic distribution. Owing to the observed composition of seed-associated fungal communities, the influence of ecological drift in community assembly is probably less plausible for fungal taxa. Indeed, seed-associated fungal communities are composed of multiple highly-abundant entities that are partly selected by the environment [START_REF] Klaedtke | Terroir is a key driver of seed-associated microbial assemblages[END_REF].

Although the observed distribution of most microbial OTUs followed the estimated distribution of Sloan neutral model, some OTUs deviated clearly from the model. The taxa that are more widespread than expected could represented microbial entities that are positively selected by the host or the environment. Among those taxa, one bacterial OTU related to Plantibacter flavus, a bacterial endophyte of several plant species [START_REF] Lumactud | Bacterial endophytes isolated from plants in natural oil seep soils with chronic hydrocarbon contamination[END_REF], and 5 fungal OTUs related to the Alternaria genus were consistently overrepresented in every plant generations. In addition to these taxa, the core members of the radish seed microbiota detected in every seed samples over the three plant generations metacommunity are probably indicative of non-neutral processes. This is especially true for highly abundant OTUs such as Pantoea agglomerans that represents on average more than 50% of all reads or to a lesser extend for fungal OTUs related to Cladosporium and Alternaria.

In conclusion, the present work highlighted a low heritability of the seed microbiota during successive plant generations. This low level of heritability could be explained in part by the importance of neutral based processes in community assembly. Neutral processes related to ecological drift might be important for the structure of seed-associated bacterial communities, while dispersion is potentially involved in assembly of the fungal fraction of the seed microbiota. These findings are important for developing biocontrol-based strategies. Indeed, if neutral processes are the main drivers of community assembly, then one might expect that earlyarriving taxa would prevent or limit colonization of late-arriving ones, especially if resource use between these taxa greatly overlaps. Therefore, inoculation of plant at flowering stage with micro-organism having a high overlap in resource use with the phytopathogenic agent(s) is likely to restrict seed transmission of the plant pathogen. The efficiency of this strategy will be of course strongly linked to the competitive potential of the selected bacterial strains. The core members of the seed microbiota were assessed with gyrB and ITS1 sequences for bacterial and fungal entities, respectively. OTUs with a lower (-1) and higher (+1) frequency than expected by the Sloan neutral are indicated. All reported values were consistent across years.

Table &

Figure 1 :

 1 Figure 1: Diversity of seed-associated microbial communities

Figure 2 :

 2 Figure 2: Microbial community similarities between seed samples harvested from three

Figure 3 :

 3 Figure 3: Variation in relative abundance of microbial communities

Figure 4 :

 4 Figure 4: Fit of the Sloan neutral model

Figure 1

 1 Figure 1Click here to download colour figureFig1.eps

  Figure 2

Figure 4

 4 Figure 4Click here to download colour figureFig4.eps

Table 1 : Frequency and relative abundance of the core members of the seed microbiota

 1

	OTU	Median relative	Taxonomic affiliation
		abundance (%)
	Bacterial OTUs
	Otu000001	57.88	Pantoea agglomerans
	Otu000002	8.71	Pseudomonas viridiflava
	Otu000004	4.10	Erwinia tasmaniensis
	Fungal OTUs
	OTU00001	29.35	Alternaria
	OTU00002	24.98	Cladosporium
	OTU00003	13.49	Alternaria
	OTU00004	2.77	Alternaria
	OTU00005	2.28	Mycosphaerella
	OTU00006	2.03	Filobasidiales
	OTU00007	1.95	Alternaria
	OTU00008	1.91	Alternaria
	OTU00012	1.34	Alternaria
	OTU00009	1.16	Alternaria
	OTU00010	1.11	Stemphylium
	OTU00015	1.06	Alternaria
	OTU00013	1.05	Alternaria
	OTU00014	0.83	Alternaria
	OTU00019	0.47	Alternaria
	OTU00021	0.41	Filobasidium
	OTU00023	0.34	Alternaria
	OTU00033	0.24	Alternaria
	OTU00036	0.21	Alternaria

Table 2 : Fitting the Sloan neutral model to the radish seed microbiota 794

 2

	Datasets	Samples N	OTUs	m	RMSE	RMSE	AIC Sloan AIC
						Sloan	binomial		binomial
	ITS1_2013_1000	9	1000	236	0.83 + 0.17	0.13	0.08	-292	-508
	ITS1_2013_5000	9	5000	712	0.78 + 0.10	0.12	0.07	-977	-1840
	ITS1_2014_1000	32	1000	501	0.47 + 0.08	0.09	0.09	-954	-974
	ITS1_2014_5000	32	5000	1434	0.41 + 0.05	0.08	0.09	-3136	-3071
	ITS1_2015_1000	32	1000	650	0.79 + 0.09	0.07	0.05	-1696	-1982
	ITS1_2015_5000	32	5000	2169	0.75 + 0.07	0.06	0.05	-5801	-6942
	gyrB_2013_1000	9	1000	232	0.18 + 0.07	0.17	0.20	-169	-141
	gyrB_2013_5000	9	5000	640	0.12 + 0.02	0.14	0.20	-666	-384
	gyrB_2014_1000	32	1000	633	0.03 + 0.01	0.08	0.14	-1342	-780
	gyrB_2014_5000	31	5000	1906	0.04 + 0.01	0.07	0.13	-4440	-2575
	gyrB_2015_1000	32	1000	1044	0.02 + 0.01	0.07	0.12	-2664	-1545
	gyrB_2015_5000	32	5000	3813	0.04 + 0.01	0.06	0.10	-10118	-7147
	795
	796

Table 3 : OTUs that deviated from the Sloan model frequency

 3

				2013-2014-
	OTUs	Kingdom	Taxonomic affiliation	2015
	Otu000015	Bacteria	Pseudomonas trivialis	-1
	Otu000018	Bacteria	Pseudomonas fluorescens	-1
	Otu000019	Bacteria	Pseudomonas fluorescens	-1
	Otu000074	Bacteria	Plantibacter flavus	+1
	OTU00112	Fungi	Alternaria alternata	+1
	OTU00131	Fungi	Alternaria infectoria	+1
	OTU00133	Fungi	Alternaria infectoria	+1
	OTU00148	Fungi	Alternaria alternata	+1
	OTU00156	Fungi	Alternaria alternata	+1

Acknowledgments

This research was supported by grant awarded by the Region des Pays de la Loire (metaSEED, 2013 10080) and the Michigan State University Plant Resilience Institute. The authors wish to thanks Gloria Torres-Cortes for manuscript assessment, Emmanuelle Laurent, Julie Gombert and Vincent Odeau (Fédération Nationale des Agriculteurs Multiplicateurs de Semences -FNAMS) for their help with all the field experiments, Aude Rochefort for the preparation of the sequencing library and Muriel Bahut from the platform ANAN of SFR Quasav for launching the MiSeq runs.

Conflict of interest

Matthieu Barret and Philippe Simoneau are Guest Editors of the special issue. This does not, however, interfere with the reviewing process.

Supplemental Information

Article title: Assembly of the seed microbiota within and across successive plant generations Authors: Samir Rezki, Claire Campion, Philippe Simoneau, Marie-Agnès Jacques, Ashley Shade and Matthieu Barret