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International audience; Background: The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results: Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions: This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.

Banana is a fruit crop with a complex diversity pattern resulting from a complex domestication scheme. Due to the availability of plant genome sequences and to the accessibility of next-generation genotyping technologies, Genome-Wide Association Studies (GWAS) have been increasingly performed in crop plants as a start to resolve genetic architecture of traits. The GWAS method was developed to perform association studies between phenotypes such as diseases and genotypes in Humans and is now successfully applied to many plants and animals to support the breeding process. However, there are prerequisites for such methods as it has been designed for populations of diploids organisms which follow the mendelian genetics model (i.e. “infinite” population and panmixia). In banana, the most popular cultivars are triploids, often hybrids between different species, and due to the absence of seeds in the fruit, a wide amount of the diversity observed ensues from the clonal diversification of a few initial genotypes. Therefore, the application of such approach to the crop is challenging and innovative. We selected a set of 106 diploid accessions with pure M. acuminata background avoiding clone duplicates and generated the appropriate molecular markers to support GWAS for any given trait. Finally, we validated the approach on the major domestication syndrome in banana, the seedless phenotype, and identified six candidate regions in which are located two strong candidate genes for female sterility. (Texte intégral)

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)

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)