As for many crops, new high-quality grapevine varieties requiring less pesticide and adapted to climate change are needed. In perennial species, breeding is a long process which can be speeded up by gaining knowledge about quantitative trait loci linked to agronomic traits variation. However, due to the long juvenile period of these species, establishing numerous highly recombinant populations for high resolution mapping is both costly and time-consuming. Genome wide association studies in germplasm panels is an alternative method of choice, since it allows identifying the main quantitative trait loci with high resolution by exploiting past recombination events between cultivars. Such studies require adequate panel design to represent most of the available genetic and phenotypic diversity. Assessing linkage disequilibrium extent and panel power is also needed to determine the marker density required for association studies. Starting from the largest grapevine collection worldwide maintained in Vassal (France), we designed a diversity panel of 279 cultivars with limited relatedness, reflecting the low structuration in three genetic pools resulting from different uses (table vs wine) and geographical origin (East vs West), and including the major founders of modern cultivars. With 20 simple sequence repeat markers and five quantitative traits, we showed that our panel adequately captured most of the genetic and phenotypic diversity existing within the entire Vassal collection. To assess linkage disequilibrium extent and panel power, we genotyped single nucleotide polymorphisms: 372 over four genomic regions and 129 distributed over the whole genome. Linkage disequilibrium, measured by correlation corrected for kinship, reached 0.2 for a physical distance between 9 and 458 Kb depending on genetic pool and genomic region, with varying size of linkage disequilibrium blocks. This panel achieved reasonable power to detect associations between traits with high broad-sense heritability (> 0.7) and causal loci with intermediate allelic frequency and strong effect (explaining > 10 % of total variance). Our association panel constitutes a new, highly valuable resource for genetic association studies in grapevine, and deserves dissemination to diverse field and greenhouse trials to gain more insight into the genetic control of many agronomic traits and their interaction with the environment.

As pan-genome approaches are largely employed for bacterial comparative genomics and evolution analyses, but still difficult to be carried out by non-bioinformatician biologists, there is a need for an innovative tool facilitating the exploration of bacterial pan-genomes. PanExplorer is a web application providing various genomic analyses and reports, giving intuitive views that enable a better understanding of bacterial pan-genomes. As an example, we produced the pan-genome for 121 Anaplasmataceae strains (including 30 Ehrlichia, 15 Anaplasma, 68 Wolbachia). PanExplorer is written in Perl CGI and relies on several JavaScript libraries for visualization (hotmap.js, MauveViewer, CircosJS). It is freely available at http://panexplorer.southgreen.fr. The source code has been released in a GitHub repository https://github.com/SouthGreenPlatform/PanExplorer. A documentation section is available on PanExplorer website.

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager.

SNiPlay is a web-based tool for detection, management and analysis of genetic variants including both single nucleotide polymorphisms (SNPs) and InDels. Version 3 now extends functionalities in order to easily manage and exploit SNPs derived from next generation sequencing technologies, such as GBS (genotyping by sequencing), WGRS (whole gre-sequencing) and RNA-Seq technologies. Based on the standard VCF (variant call format) format, the application offers an intuitive interface for filtering and comparing polymorphisms using user-defined sets of individuals and then establishing a reliable genotyping data matrix for further analyses. Namely, in addition to the various scaled-up analyses allowed by the application (genomic annotation of SNP, diversity analysis, haplotype reconstruction and network, linkage disequilibrium), SNiPlay3 proposes new modules for GWAS (genome-wide association studies), population stratification, distance tree analysis and visualization of SNP density. Additionally, we developed a suite of Galaxy wrappers for each step of the SNiPlay3 process, so that the complete pipeline can also be deployed on a Galaxy instance using the Galaxy ToolShed procedure and then be computed as a Galaxy workflow. SNiPlay is accessible at http://sniplay.southgreen.fr.

Rice yellow mottle virus (RYMV) causes high losses to rice production in Africa. Several sources of varietal high resistance are available but the emergence of virulent pathotypes that are able to overcome one or two resistance alleles can sometimes occur. Both resistance spectra and viral adaptability have to be taken into account to develop sustainable rice breeding strategies against RYMV. In this study, we extended previous resistance spectrum analyses by testing the rymv1-4 and rymv1-5 alleles that are carried by the rice accessions Tog5438 and Tog5674, respectively, against isolates that are representative of RYMV genetic and pathogenic diversity. Our study revealed a hypervirulent pathotype, named thereafter pathotype T′, that is able to overcome all known sources of high resistance. This pathotype, which is spatially localized in West-Central Africa, appears to be more abundant than previously suspected. To better understand the adaptive processes of pathotype T′, molecular determinants of resistance breakdown were identified via Sanger sequencing and validated through directed mutagenesis of an infectious clone. These analyses confirmed the key role of convergent nonsynonymous substitutions in the central part of the viral genome-linked protein to overcome RYMV1-mediated resistance. In addition, deep-sequencing analyses revealed that resistance breakdown does not always coincide with fixed mutations. Actually, virulence mutations that are present in a small proportion of the virus population can be sufficient for resistance breakdown. Considering the spatial distribution of RYMV strains in Africa and their ability to overcome the RYMV resistance genes and alleles, we established a resistance-breaking risk map to optimize strategies for the deployment of sustainable and resistant rice lines in Africa.