A digital catalog of high‐density markers for banana germplasm collections

Global production of bananas, among the top 10 food crops worldwide, is under threat. Increasing the use of germplasm conserved in genebanks is crucial. However, the lack of or difficult access to genetic diversity information limits the efficient utilization of these valuable resources. Here, we present a digital catalog of high‐density markers for banana germplasm conserved at the international banana collection. By facilitating access to subsets of genetic diversity information, the catalog has potential to maximize conservation and use of climate‐ready varieties and to optimize breeding strategies. The catalog is extendable with data from any banana collection and the software is easily deployable in other crop genebanks

Whole blood transcriptome profiles of trypanotolerant and trypanosusceptible cattle highlight a differential modulation of metabolism and immune response during infection by Trypanosoma congolense

Animal African trypanosomosis, caused by blood protozoan parasites transmitted mainly by tsetse flies, represents a major constraint for millions of cattle in sub-Saharan Africa. Exposed cattle include trypanosusceptible indicine breeds, severely affected by the disease, and West African taurine breeds called trypanotolerant owing to their ability to control parasite development, survive and grow in enzootic areas. Until now the genetic basis of trypanotolerance remains unclear. Here, to improve knowledge of the biological processes involved in trypanotolerance versus trypanosusceptibility, we identified bovine genes differentially expressed in five West African cattle breeds during an experimental infection by Trypanosoma congolense and their biological functions. To this end, whole blood genome-wide transcriptome of three trypanotolerant taurine breeds (N’Dama, Lagune and Baoulé), one susceptible zebu (Zebu Fulani) and one African taurine x zebu admixed breed (Borgou) were profiled by RNA sequencing at four time points, one before and three during infection. As expected, infection had a major impact on cattle blood transcriptome regardless of the breed. The functional analysis of differentially expressed genes over time in each breed confirmed an early activation of the innate immune response, followed by an activation of the humoral response and an inhibition of T cell functions at the chronic stage of infection. More importantly, we highlighted overlooked features, such as a strong disturbance in host metabolism and cellular energy production that differentiates trypanotolerant and trypanosusceptible breeds. N’Dama breed showed the earliest regulation of immune response, associated with a strong activation of cellular energy production, also observed in Lagune, and to a lesser extent in Baoulé. Susceptible Zebu Fulani breed differed from other breeds by the strongest modification in lipid metabolism regulation. Overall, this study provides a better understanding of the biological mechanisms at work during infection, especially concerning the interplay between immunity and metabolism that seems differentially regulated depending on the cattle breeds

The Banana Genome Hub: a community database for genomics in the Musaceae

The Banana Genome Hub provides centralized access for genome assemblies, annotations, and the extensive related omics resources available for bananas and banana relatives. A series of tools and unique interfaces are implemented to harness the potential of genomics in bananas, leveraging the power of comparative analysis, while recognizing the differences between datasets. Besides effective genomic tools like BLAST and the JBrowse genome browser, additional interfaces enable advanced gene search and gene family analyses including multiple alignments and phylogenies. A synteny viewer enables the comparison of genome structures between chromosome-scale assemblies. Interfaces for differential expression analyses, metabolic pathways and GO enrichment were also added. A catalogue of variants spanning the banana diversity is made available for exploration, filtering, and export to a wide variety of software. Furthermore, we implemented new ways to graphically explore gene presence-absence in pangenomes as well as genome ancestry mosaics for cultivated bananas. Besides, to guide the community in future sequencing efforts, we provide recommendations for nomenclature of locus tags and a curated list of public genomic resources (assemblies, resequencing, high density genotyping) and upcoming resources—planned, ongoing or not yet public. The Banana Genome Hub aims at supporting the banana scientific community for basic, translational, and applied research and can be accessed at https://banana-genome-hub.southgreen.f

BrAPI-an application programming interface for plant breeding applications

Motivation: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases

Managing high-density genotyping data with Gigwa

International audienceNext generation sequencing technologies enabled high-density genotyping for large numbers of samples. Nowadays SNP calling pipelines produce up to millions of such markers, but which need to be filtered in various ways according to the type of analyses. One of the main challenges still lies in the management of an increasing volume of genotyping files that are difficult to handle for many applications. Here, we provide a practical guide for efficiently managing large genomic variation data using Gigwa, a user-friendly, scalable and versatile application that may be deployed either remotely on web servers or on a local machine

metaXplor: an interactive viral and microbial metagenomic data manager

International audienceBackground: Efficiently managing large, heterogeneous data in a structured yet flexible way is a challenge to research laboratories working with genomic data. Specifically regarding both shotgun- and metabarcoding-based metagenomics, while online reference databases and user-friendly tools exist for running various types of analyses (e.g., Qiime, Mothur, Megan, IMG/VR, Anvi'o, Qiita, MetaVir), scientists lack comprehensive software for easily building scalable, searchable, online data repositories on which they can rely during their ongoing research. Results: metaXplor is a scalable, distributable, fully web-interfaced application for managing, sharing, and exploring metagenomic data. Being based on a flexible NoSQL data model, it has few constraints regarding dataset contents and thus proves useful for handling outputs from both shotgun and metabarcoding techniques. By supporting incremental data feeding and providing means to combine filters on all imported fields, it allows for exhaustive content browsing, as well as rapid narrowing to find specific records. The application also features various interactive data visualization tools, ways to query contents by BLASTing external sequences, and an integrated pipeline to enrich assignments with phylogenetic placements. The project home page provides the URL of a live instance allowing users to test the system on public data. Conclusion: metaXplor allows efficient management and exploration of metagenomic data. Its availability as a set of Docker containers, making it easy to deploy on academic servers, on the cloud, or even on personal computers, will facilitate its adoption

SNiPlay3: a web-based application for exploration and large scale analyses of genomic variations

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. (Résumé d'auteur

Additional file 1: Figure S1. of WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle

Sample BSON documents illustrating variant and genotyping data storage. The two typical kinds of database records, i.e. Variant document and VariantRunData document, contain variant-level information and run-level genotyping data, respectively. Because storage is made in such a way that dictionary keys are repeated for each record, we defined them as short as two characters in order to keep disk space usage reasonable. Flexibility is illustrated by the use of lists and dictionaries, which can grow without the need to redefine a fixed model. (PDF 160 kb