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Comparative genomics is the analysis of genomic relationships among different species and serves as a significant base for evolutionary and functional genomic studies. GreenPhylDB (https://www.greenphyl.org) is a database designed to facilitate the exploration of gene families and homologous relationships among plant genomes, including staple crops critically important for global food security. GreenPhylDB is available since 2007, after the release of the Arabidopsis thaliana and Oryza sativa genomes and has undergone multiple releases. With the number of plant genomes currently available, it becomes challenging to select a single reference for comparative genomics studies but there is still a lack of databases taking advantage several genomes by species for orthology detection. GreenPhylDBv5 introduces the concept of comparative pangenomics by harnessing multiple genome sequences by species. We created 19 pangenes and processed them with other species still relying on one genome. In total, 46 plant species were considered to build gene families and predict their homologous relationships through phylogenetic-based analyses. In addition, since the previous publication, we rejuvenated the website and included a new set of original tools including protein-domain combination, tree topologies searches and a section for users to store their own results in order to support community curation efforts.

International audience; Most sorghum biomass accumulates in stem secondary cell walls (SCW). As sorghum stems are used as raw materials for various purposes such as feed, energy and fiber reinforced polymers, identifying the genes responsible for SCW establishment is highly important. Taking advantage of studies performed in model species, most of the structural genes contributing at the molecular level to the SCW biosynthesis in sorghum have been proposed while their regulatory factors have mostly not been determined. Validation of the role of several MYB and NAC transcription factors in SCW regulation in Arabidopsis and a few other species has been provided. In this study, we contributed to the recent efforts made in grasses to uncover the mechanisms underlying SCW establishment. We reported updated phylogenies of NAC and MYB in 9 different species and exploited findings from other species to highlight candidate regulators of SCW in sorghum. We acquired expression data during sorghum internode development and used co-expression analyses to determine groups of co-expressed genes that are likely to be involved in SCW establishment. We were able to identify two groups of co-expressed genes presenting multiple evidences of involvement in SCW building. Gene enrichment analysis of MYB and NAC genes provided evidence that while NAC SECONDARY WALL THICKENING PROMOTING FACTOR NST genes and SECONDARY WALL-ASSOCIATED NAC DOMAIN PROTEIN gene functions appear to be conserved in sorghum, NAC master regulators of SCW in sorghum may not be as tissue compartmentalized as in Arabidopsis. We showed that for every homolog of the key SCW MYB in Arabidopsis, a similar role is expected for sorghum. In addition, we unveiled sorghum MYB and NAC that have not been identified to date as being involved in cell wall regulation. Although specific validation of the MYB and NAC genes uncovered in this study is needed, we provide a network of sorghum genes involved in SCW both at the structural and regulatory levels.

Sorghum is a crop widely cultivated in southern countries (Africa, Latin America, India) for human and animal consumption. It is also grown in northern countries for animal consumption and increasingly used for energy and biomaterials. These uses often rely on vegetative biomass valorization. Most of this biomass accumulates in secondary cell wall (SCW) of the stems as celluloses and xylans, which are tightly linked to lignins. Being able to monitor precisely the composition of SCW in sorghum can provide a major leverage to optimize its different uses. Understanding how SCW is deposited and regulated would allow breeding programs to develop varieties fitting the expectations of the different value chains. The identification of genes involved in SCW development in sorghum will contribute to improve our ability to optimize its composition and structure. Transcription factors (TF) are key targets because they are often responsible for fine-tuning biological processes. Moreover, they allow deciphering the downstream network. MYB and NAC TF families are already known to be involved in SCW regulation in other model species, but their roles still need to be addressed in sorghum. For this study, we carried out comparative genomics and co-expression network analysis to highlight NAC and MYB genes that are most likely to be involved in SCW regulation in sorghum. Based on these candidates, functional validation experiments are on-going. Firstly, the comparative genomics analysis identified 96 NAC and 170 MYB genes in sorghum. 34 NAC and MYB genes were recognized as orthologs of master regulators of SCW in other species. Moreover, phylogenetic dissimilarities within both families between monocotyledons and dicotyledons pointed out potential differences in SCW regulation between these two groups of angiosperms. Secondly, using transcriptomic data from developing sorghum internodes, we built co- expression networks. Using orthologs of previously identified TF as baits, we were able to generate genes lists potentially involved in the same process of SCW biosynthesis. Genes co- expressed with bait TF showed enrichment in functional categories (GO terms) linked to SCW. They also revealed differences in enriched categories for TF related to primary cell walls or specific compounds of SCW. Some whole co-expression network groups are also enriched in SCW linked categories. It is likely that there are new important SCW involved genes within these candidate gene lists. Taking advantage of genome wide association results, we detected overlaps between the newly identified list of genes and genomic regions controlling stem composition. Some of the sorghum TF roles are being validated by targeted transgenesis (CRISPR-Cas9 and overexpression). In the future, these results will contribute to the management of the diversity of SCW key genes within selection programs for sorghum stems quality improvement.

International audience; Background : Non-specific Lipid Transfer Proteins (nsLTPs) are widely distributed in the plant kingdom and constitute a superfamily of related proteins. Several hundreds of different nsLTP sequences—and counting—have been characterized so far, but their biological functions remain unclear. It has been clear for years that they present a certain interest for agronomic and nutritional issues. Deciphering their functions means collecting and analyzing a variety of data from gene sequence to protein structure, from cellular localization to the physiological role. As a huge and growing number of new protein sequences are available nowadays, extracting meaningful knowledge from sequence–structure–function relationships calls for the development of new tools and approaches. As nsLTPs show high evolutionary divergence, but a conserved common right handed superhelix structural fold, and as they are involved in a large number of key roles in plant development and defense, they are a stimulating case study for validating such an approach. Methods : In this study, we comprehensively investigated 797 nsLTP protein sequences, including a phylogenetic analysis on canonical protein sequences, three-dimensional structure modeling and functional annotation using several well-established bioinformatics programs. Additionally, two integrative methodologies using original tools were developed. The first was a new method for the detection of (i) conserved amino acid residues involved in structure stabilization and (ii) residues potentially involved in ligand interaction. The second was a structure–function classification based on the evolutionary trace display method using a new tree visualization interface. We also present a new tool for visualizing phylogenetic trees. Results : Following this new protocol, an updated classification of the nsLTP superfamily was established and a new functional hypothesis for key residues is suggested. Lastly, this work allows a better representation of the diversity of plant nsLTPs in terms of sequence, structure and function.

International audience; The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches. Central to the QfO effort is proper benchmarking of methods and services, as well as design of standardized datasets and standardized formats to allow sharing and comparison of results. Simultaneously, analysis pipelines have been improved, evaluated and adapted to handle large datasets. All this would not have occurred without the long-term collaboration of Consortium members. Meeting regularly to review and coordinate complementary activities from a broad spectrum of innovative researchers clearly benefits the community. Highlights of the meeting include addressing sources of and legitimacy of disagreements between orthology calls, the context dependency of orthology definitions, special challenges encountered when analyzing very anciently rooted orthologies, orthology in the light of whole-genome duplications, and the concept of orthologous versus paralogous relationships at different levels, including domain-level orthology. Furthermore, particular needs for different applications (e.g. plant genomics, ancient gene families and others) and the infrastructure for making orthol-ogy inferences available (e.g. interfaces with model organism databases) were discussed, with several ongoing efforts that are expected to be reported on during the upcoming 2017 QfO meeting.

CompPhy2 is a real time collaborative web platform for visualization, comparison and annotation of phylogenetic trees with a responsive user friendly interface. It is the only phylogenetic web platform allowing several users to work synchronously or asynchronously on a same dataset. CompPhy2 brings new features such as side by side comparison, tree annotation, custom display, supertree inference

International audience; CompPhy2 is a real time collaborative web platform for visualization, comparison and annotation of phylogenetic trees with a responsive user friendly interface. It is the only phylogenetic web platform allowing several users to work synchronously or asynchronously on a same dataset. CompPhy2 brings new features such as side by side comparison, tree annotation, custom display, supertree inference

AGAP : équipe ID / GE2pop; Leucine-Rich Repeats Receptor-Like Kinase (LRR-RLK) genes represent a large and complex gene family in plants, mainly involved in development and stress responses. These receptors are composed of an LRR-containing extracellular domain (ECD), a transmembrane domain(TM) and an intracellular kinase domain (KD). To provide new perspectives on functional analyses of these genes in model and non-model plant species, we performed a phylogeneticanalys is on 8,360 LRR-RLK receptors in 31 angiosperm genomes (8 monocots and 23dicots). We identified 101 orthologous groups (OGs) of genes being conserved among almost all monocot and dicot species analyzed. We observed that more than 10% of these OGs are absent in the Brassicaceae species studied. We show that the ECD structural features are not always conserved among orthologs, suggesting that functions may have diverged in some OG sets. Moreover, we looked at targets of positive selection footprints in 12 pairs of OGs and noticed that depending on the subgroups, positive selection occurred more frequently either in the ECDs or in the KDs.

Analysis and visualization of massive genomics datasets are an ongoing trend in plant sciences. The South Green Bioinformatics platform provides an ecosystem of tools that were originally developed as independent entities to fulfill the need for specific projects or crops, but have evolved over time to generic tools to comprehensively study crop genomics. We have built a large panel of public information systems dedicated to specialized datasets (markers, genes, gene families, transcriptomes, genotypes, phenotypes, etc.) and crop-specific resources called Genome Hubs. Target users of bioinformatic analytical workflows are usually divided between people who use command-line and those who do not. We addressed both categories by offering complementary solutions, like Galaxy-based and command-line applications. Various groups used the South Green infrastructure to obtain their data and results, and were able to publish high-quality biological information, on Coffee genome, Banana, Cocoa, African rice or large transcriptome resources. Tools developed for these studies are adaptable to a wide range of other organisms.

To face global warming and fossil fuel depletion crisis, plant biomass will provide a renewable source of energy, materials and chemicals. Accordingly, agriculture will have to adapt not only to avoid competition between food-feed and non-food non-feed uses but also to ensure the economical and environmental sustainability of these productions. In this context, we are developing an integrative strategy merging genetics, breeding, material sciences, energy production, animal nutrition and socio economic analyses to accelerate the development of multipurpose sorghum value chains for both Mediterranean and tropical semi-arid conditions (West Africa). As a first step, new products (biocomposites) and uses (biomethane production) are being developed. Then the plant traits impacting the production and quality of the different end-products and uses are being identified taking advantage of the genetic diversity of sorghum. As a third step, the set-up of these key traits in the plant is being analyzed in order to describe their patterns of development / accumulation, their susceptibility to environmental constraints and provide some insights regarding their molecular determinism. Taking advantage of these functional information, the genomic regions impacting the key traits are being deciphered and used to develop new breeding tools and breeding strategies. In parallel, to maximize the probability to convert scientific results in local impacts, the different stakeholders of the value chains are being mobilized and territorial analyses aiming to assess the relevance of the different value chains are performed.

UMR AGAP : équipe IDUMR AGAP : équipe ID; Comparative genomics of gene families in relation with metabolic pathways for gene candidates highlighting. JOBIM 2016 : Journées ouvertes de biologie informatique et mathématiques

AGAP : équipe ID; National audience; CompPhy v2 : une plate-forme collaborative pour visualiser et comparer des phylogénies.

Abscisic acid (ABA) pathway is aphytohormone universally conserved in land plants which coordinates several aspects of the plant response to water deficit such as root architecture, seed dormancy and regulation of stomatal closure. A mechanism of ABA signal transduction has been proposed, evolving intracellular ABA receptors (PYR/PYL/RCARs) interacting with PP2Cs phosphatases and SnRK2 protein kinases regulating this tripartite protein system. Rationale. The goal of this study was to identify and characterize for the first time the orthologs genes of this tripartite system in Coffea canephora. Methods. For this purpose, protein sequences from Arabidopsis, citrus, rice, grape, tomato and potato were chosen as query to search orthologous genes in the Coffee Genome Hub (http://coffee-genome.org/). Differential expression in tissues as leaves, seeds, roots and floral organs was checked through in silky analyses. In vivo gene expression analyses were also performed by RT-qPCR in leaves and roots of drought-tolerant (DT 14, 73 and 120) and drought-susceptible (Ds 22) C canephora Conilon clones submitted or not) to drought. Results. This approach allowed the identification and characterization of 17 candidate genes (9 PYL/RCARs, 6 PP2Cs and 2 SnRK2s) in C. canephora genome. The protein motifs identified in predict coffee sequences enabled characterize these genes as family's members of PYL/RCARs receptors, PP2Cs phosphatases or SnRK2 kinases of the ABA response pathway. These families were functionally annotated in the C. canephora genome. In vivo analyses revealed that eight genes are up-regulated under drought conditions in both leaves and roots tissues. Among them, three genes coding phosphatases were expressed in all (DT and Ds) clones therefore suggesting that they were activated as a general response to cope with drought stress. However, two other phosphatase coding genes were up-regulated only in the DT clones, suggesting that they constituted key-genes for drought tolerance in these clones. The DT clones also showed differential gene expression profiles for five other genes therefore reinforcing the idea that multiple biological mechanisms are involved drought tolerance in C. canephora. Conclusions and Perspectives. All these evidences will help us to identify the genetic determinism of drought tolerance through ABA pathway essential to obtain molecular markers that could be used in coffee breeding programs. (Texte intégral)

The study of gene families is an important field of comparative genomics, allowing, by the analysis of evolutionary history, to identify homology relationships, gene losses and to help in annotation transfers. The addition of metabolic information improves the identification of candidate genes by addition of functional and gene network data. We propose new web systems to facilitate and improve the analysis of gene family for the search of candidate genes in plants. GenFam* is dedicated to the manual and precise analysis of gene families and includes specific workflows running under a Galaxy platform, allowing to gather several data sources, analysis and visualization tools, in order to (i) build custom families (ii) run analysis workflows dedicated to the analysis of gene families (iii) visualize analysis results and functional evidences through a dedicated visualization dashboard. In complement to the integration of data sources, tools and visualizations, we also suggest a new way to find evidences for the identification of evolutionary events through syntenic analyses. The IDEVEN algorithm is based on the study of syntenic blocks linked to a gene family to identify speciation, Whole Genome Duplication (WGD) events, and other duplications in a family history. The identified events will be reported on the phylogeny and aim to bring complementary evidences to have a clearer view of the evolutionary history of a gene family. To extend this tool to the analysis of multiple gene families and integrate metabolic pathways data, this tool has been integrated in genesPath, which will allow a deep identification and highlighting of candidate genes of interest for a specific project called “Biomass For the Future (BFF)”. This online tool will be soon available and could be notably used for searching candidate genes involved in biosynthesis of lignin and cellulose in various plant species (such as maize and sorghum).

UMR AGAP - équipe ID - Intégration des données; GenFam est un système intégratif d'analyse de familles de gènes. Ce système permet (i) de créer des familles de gènes de génomes complets, (ii) d’exécuter une analyse phylogénétique de cette famille à travers le gestionnaire de workflows Galaxy afin de définir les relations d'homologie, (iii) d'étudier des événements évolutifs à partir de blocs de synténie précalculées avec le workflow SynMap de la plateforme de génomique comparative (CoGe) et (iv) d’intégrer ces résultats dans l'interface de visualisation synthétique. La première application de GenFam est d’identifier des gènes candidats pour la tolérance aux stress environnementaux. Il nécessite de mettre en évidence la présence de séquences régulatrices cis spécifiques de la réponse aux stress (de type ABRE, DRE). Dans ce contexte, nous avons besoin d’intégrer de nouveaux outils afin de découvrir et chercher des sites de fixation de facteurs de transcription (Transcription Factor Binding Sites, TFBS) dans les séquences promotrices des gènes membre de la famille étudiée. Ce workflow Galaxy va, d'une part, sélectionner les régions flanquantes en 5' ou en 3' des gènes d'intérêts selon le choix de l'utilisateur. D'autre part, les régions flanquantes sont analysées afin de découvrir et rechercher les motifs de séquences régulatrices cis spécifiques de la réponse aux stress avec des méthodes complémentaires comme MEME, STIF, PHYME. Ces résultats ainsi que l’annotation fonctionnelle des gènes étiquetés comme étant impliqués dans la réponse au stress seront intégrés dans l’interface de visualisation. Ce travail doit permettre une réflexion sur la notion d'orthologie fonctionnelle et effectuer une recherche translationnelle depuis les espèces modèles jusqu'aux espèces d'intérêt agronomique (i.e identifier des gènes candidats pour la réponse au stress du caféier à partir d'informations fonctionnelles connues chez Arabidopsis).

International audience; In 2015, the South Green Bioinformatics Platform http://www.southgreen.fr/ is a network of 35 bioinformaticians from five biology research institutes working with two High - Performance Computing Data Centres to develop and use new tools for NGS/ Omic analytics of tropical and Mediterranean crops under projects studying relationsh ip between genetic diversity, agronomic performance and response to selection. South Green is affiliated to the South regional centre of the French Institute of Bioinformatics (the French node of the European research infrastructure, ELIXIR). This communit y and the HPC data centres are all located in Montpellier, which facilitates close collaboration and significant pooling to best meet the biologists' demands of our research units. Since 2004, we developed web - based applications with both generic and in - ho use components, for databases, analysis workflows and web interfaces, in order to: manage genetic and phenotypic information ( e.g. TropGeneDB), analyse molecular markers and genetic diversity ( e.g. SNiPlay), assemble transcriptomes ( e.g. ESTtik) map RNA - Se q ( e.g. ARCAD), annotate and compare genomes ( e.g. GNPAnnot), reconstruct evolutionary history of gene families by phylogenomics ( e.g. GreenPhyl). We also participate to the analysis of numerous crop species, that requires computing and storage facilities as well as interoperable information systems, such as rice ( e.g. OryGenesDB), wheat, sorghum, sugarcane, banana (Banana Genome Hub), palms, yam, coffee (CGH), rubber, cacao (CocoaGenDB), cotton, apple, grapevine, olive, eucalyptus, cassava. To face the dat a deluge, we must increase our analytics capabilities. We document our operation at both, administrator/ developer and user/ scientist level, to provide high quality services and reproducible research. We pool into working groups on key themes such as GBS, at both, developer (extreme pair programming) and user (interdisciplinary knowledge exchange) level. We provide training sessions each year. Finally, we implemented several instances of the Galaxy workflow manager and encapsulated our tools. These instanc es serve as a catalyst for massive NGS analyses but it remains to increase storage capacity and improve data management plans. (Résumé d'auteur)

International audience; Chaperone/usher (CU) assembly pathway is used by a wide range of Enterobacteriaceae to assemble adhesive surface structures called pili or fimbriae that play a role in bacteria-host cell interactions. In silico analysis revealed that the genome of Klebsiella pneumoniae LM21 harbors eight chromosomal CU loci belonging to γκп and ϭ clusters. Of these, only two correspond to previously described operons, namely type 1 and type 3-encoding operons. Isogenic usher deletion mutants of K. pneumoniae LM21 were constructed for each locus and their role in adhesion to animal (Intestine 407) and plant (Arabidopsis thaliana) cells, biofilm formation and murine intestinal colonization was investigated. Type 3 pili usher deleted mutant was impaired in all assays, whereas type 1 pili usher deleted mutant only showed attenuation in adhesion to plant cells and in intestinal colonization. The LM21ΔkpjC mutant was impaired in its capacity to adhere to Arabidopsis cells and to colonize the murine intestine, either alone or in co-inoculation experiments. Deletion of LM21kpgC induced a significant decrease in biofilm formation, in adhesion to animal cells and in colonization of the mice intestine. The LM21∆kpaC and LM21∆kpeC mutants were only attenuated in biofilm formation and the adhesion abilities to Arabidopsis cells, respectively. No clear in vitro or in vivo effect was observed for LM21∆kpbC and LM21∆kpdC mutants. The multiplicity of CU loci in K. pneumoniae genome and their specific adhesion pattern probably reflect the ability of the bacteria to adhere to different substrates in its diverse ecological niches.

Sorghum is among the world's most important cereals in terms of human and animal nutrition. It is also currently identified as a promising crop to support the emerging bio-economy value chains that include energy production, biomaterials and molecules for food-feed and non-food-feed applications. In this context, the development of varieties adapted to the different end-uses is critical to provide the industries with relevant feedstock. Breeding sorghum for existing and emerging markets requires several steps, from the definition of “Industrial Ideotypes” down to the identification of “Molecular Ideotypes” in order to speed up the breeding process and optimize the genetic gains per unit of time. Firstly, expectations of the industrials in terms of composition and properties of the sorghum biomass for the different applications (“Industrial ideotypes”) have to be defined. Secondly, “Industrial ideotypes” have to be translated in “Biological ideotypes” which refers to the properties of the raw sorghum material in terms of composition and structure. Third, high-throughput phenotyping tools compatibles with genetic analyses and breeding constraints have to be developed. Fourth, strategies to disentangle the genetic determinism of the “Biological Ideotypes” have to be set up. And fifth, relevant breeding schemes able to provide new hybrids and relevant parents have to be initiated. We will illustrate this process through two examples related to the production of sorghum biocomposites and the optimization of sorghum biogas production. For both targets, we will show how, through the use of the sorghum genetic diversity, traits affecting the final product properties were identified. We will then illustrate the efforts that are currently developed to tackle the challenges linked to high-throughput phenotyping. We will finally show how these phenotyping tools are used on diverse association panels and multiparental designs to identify the genomic regions affecting the traits of interest and develop new hybrids and elite parents. Funding acknowledgement: This research is supported through the Biomass For the Future project (funded by ANR) and the BIOSORG project supported by the Agropolis (Labex Agro) and Cariplo foundations.

Unraveling the genetic diversity held in genebanks on a large scale is underway, given the advances in NGS-based technologies that produce high-density genetic markers for a large number of samples at low cost. As SNP markers are being mapped on the reference genomes, it is important to develop interoperable system for managing both genomic data and genetic resources. The latter are often managed through bespoke information systems. The Musa Germplasm Information System (MGIS), the main banana genetic resource website, has recently been developed to address those needs in a convenient and flexible way. First of all, we decided to head for a generic database schema, such as CHADO, and to use a robust content management system such as Drupal as the web interface. The Tripal module provides the "glue" between these two parts and drastically reduces development time. Using this trio, we were able to quickly recreate in few months a complete and scalable site and expand it with new features. We now have a germplasm management system allowing collection browsing, and accession browsing, searching and ordering. Accession passport data have been enriched by geographical data, phenotyping characterization data, and information from diversity studies based on molecular markers and SNPs. As a first-use case, such genotyping studies allow linking with the Banana Genome Hub (BGH) website to explore these data in the genome context. (Texte intégral)

Important research efforts are made to characterize mechanisms of biological interest, such as stress tolerance, through gene family studies. The identification of these families allows the functional annotation of genes, as genes belonging to one family are supposed to have similar or related functions. We have developed an online comparative genomics application, GenFam, allowing the user to build custom gene families based on several data sources, to run analysis workflows, and to gather results into a synthetic visualization. It allows displaying functional evidences and evolutive history information through widely used tools and the new algorithm IDEVEN. This algorithm is complementing phylogenetic analyses by using syntenic block data and synonymous mutation rates (dS). The system contains additional modules oriented towards stress response study, such as (differential) gene expression data, functional annotations (gene ontologies), and the identification of specific stress-related cis elements in the promoter regions. The aim of this work is to facilitate knowledge representation and functional inference for scientists working on gene families, and an easier way to link stress-related evidences within a gene family tree. It can therefore highlight adaptive evolution within gene families in relation to stress-prone environments and identify candidate genes for drought tolerance in non-model crops by translational studie.

Global climate changes are becoming more unpredictable and abiotic stress, such as drought and high temperatures, are key factors that affect coffee plant development and production. Although the strategies for drought adaptation in perennial plants are complex, there is genetic variability within the Coffea genus that could be used to increase tolerance. Drought tolerant clones of Coffea canephora have been characterized as vigorous plants with high productivity throughout years under water deficit. Recently, novel intracellular ABA receptors (PYL/RCARs) involved in sensing and signaling of this hormone were identified. A mechanism of ABA transduction was proposed, involving PYR/PYL/RCARs receptors interacting with PP2Cs phosphatases and SnRK2 protein kinases. The goal of this study was to identify and characterize orthologous genes of this tripartite system in C.canephora. For this purpose, protein sequences from Arabidopsis, citrus, rice, grape, and tomato were chosen as query to search orthologous genes in sequence databases. This approach allowed the identification and characterization of 24 candidate genes (9 PYL/RCAR, 6 PP2Cs and 9 SnRK2s) in C. canephora genome. The protein domains identified in the predicted coffee sequences enabled to characterize these genes as family's members of receptors (PYR/PYL/ RCAR), phosphatases (PP2Cs) or kinases (SnRK2) of ABA response pathway. Phylogenetic analysis allowed the classification of coffee-polypeptide sequences between subclasses and subfamilies. The gene structures of these three gene families were functionally annotated in Coffee Genome Hub (http://coffee-genome.org/). Tissue (leaf, seed, root and floral organ) differential expression was verified through in silico analyses. Regarding drought conditions, data from root transcriptome showed contrasting gene expression for those genes between the tolerant (Cc14, Cc73 and Cc120) and susceptible(Cc22)clones of C. canephora. By comparing gene expression profiles of only drought tolerant(Cc14, Cc73 and Cc120) clones, differential responses were observed suggesting the existence of multiple biological mechanisms for drought tolerance in coffee. All those evidences will help to identify the genetic determinism of drought tolerance essential to obtain molecular markers that could be used in coffee breeding programs.

Background: Recurrent gene duplication and retention played an important role in angiosperm genome evolution. It has been hypothesized that these processes contribute significantly to plant adaptation but so far this hypothesis has not been tested at the genome scale.[br/] Results: We studied available sequenced angiosperm genomes to assess the frequency of positive selection footprints in lineage specific expanded (LSE) gene families compared to single-copy genes using a dN/dS-based test in a phylogenetic framework. We found 5.38% of alignments in LSE genes with codons under positive selection. In contrast, we found no evidence for codons under positive selection in the single-copy reference set. An analysis at the branch level shows that purifying selection acted more strongly on single-copy genes than on LSE gene clusters. Moreover we detect significantly more branches indicating evolution under positive selection and/or relaxed constraint in LSE genes than in single-copy genes.[br/] Conclusions: In this – to our knowledge –first genome-scale study we provide strong empirical support for the hypothesis that LSE genes fuel adaptation in angiosperms. Our conservative approach for detecting selection footprints as well as our results can be of interest for further studies on (plant) gene family evolution.

The study of plant tolerance to stress is a crucial issue for crops improvement and stability in constrained environments. Gene family analysis is an important way to understand complex processes underlying stress response in crops. Several tools exist to study families and propose automatically clustered families or curated published families. We observed that automatic clustering, efficient for global analyses, is rarely sufficient for precise studies: i) families can be spread in several cluster, or ii) intrusive sequences are represented in clusters of interest. That is why biologists need most of the time to manually constitute their families. In response to this need, we propose to develop an integrative system that will allow to gather sequences from different sources for a customized family. This system will integrate several tools used for family construction and analysis. Currently, the prototype allows to query in-house Chado database (banana, coffee) and to import personal data with a web interface using the Drupal CMS. Multi-species analyzes are available using Galaxy workflows manager. Eventually, this system will be linked to a stress response oriented database. This database will propose a set of controlled vocabularies, some known stress resistance factors and other indicators to ease the identification of mechanisms implied in plant stress resistance. Beside that, this system will be generic for all type of gene families, and will propose a synthetic and dynamic view to offer to researchers an easy and intuitive way to curate their families. (Texte intégral)

La plateforme South Green dispense depuis 2011 une formation annuelle en analyse de séquences pour l'amélioration des plantes, en utilisant le système Galaxy comme plateforme pédagogique. Cette formation est ouverte à un public le plus large possible : industriels semenciers, personnels académiques, doctorants, et étudiants en agronomie. Le programme est adapté chaque année à l'état de l'art en bioinformatique, et recouvre un panorama large, allant du traitement de données brutes, à la génomique et protéomique comparative, en passant par l'annotation. Les attendus sont : i) la formation d'élèves ingénieurs agronomes et leur éveil à la bioinformatique, ii) un gain en autonomie de collègues académiques tant doctorants que permanents, iii) le renfort du lien entre nos laboratoires et le monde industriel, et iv) un échange entre ces communautés pour favoriser des collaborations, des stages ou des contrats (valorisation, bourses CIFRE...). La session 2014 s'est déroulée du 10 au 14 février. Elle a formé 12 personnes (4 étudiants, 2 privés, 6 publics). La synthèse d'évaluation met en évidence une formation très satisfaisante, remplissant pleinement ses objectifs. La prochaine session devrait prendre en considération les points d'amélioration, en particulier l'allègement du module annotation au profit du module analyse post-NGS.

With the increasing number of plant genomes being sequenced, a major challenge is to accurately transfer annotations from well characterized genomes to newly obtained sequences. GreenPhylDB is a database designed for comparative and functional genomics based on complete genome-derived gene sequences. The database currently includes gene families of protein sequences from 22 plant species, including socio-economically important crops like rice, sorghum, maize, cassava and banana. Genes from all these species are organized in clusters based on sequence similarity. The clusters are manually annotated (i.e. properly named and classified) and sequences included in each cluster are characterized by phylogenetic analysis in order to elucidate evolutionary relationships (e.g. orthologs, super-orthologs, in/out-paralogs) among genes. GreenPhyl provides a reliable and stable catalog of gene families useful for annotation on new genome sequences in plants. With its improved user interface, the new release of GreenPhyl keeps the previous gene clustering quality and introduces additional features such as specific search engines (quick search, deep search, InterPro domain combination and GO family browser). The GreenPhyl's pipeline relies on RapGreen, a new version of the RAP reconciliation tool (Dufayard et al, 2005) that allows us to root gene trees and infer orthology relationships between sequences of a family. GreenPhyl version 3 is available at http://www.greenphyl.org and is a collaborative resource of SouthGreen (southgreen.cirad.fr), a bioinformatics platform applied to the genetic and genomic resources analyses of the South and Mediterranean plants.