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. AVAILABILITY AND IMPLEMENTATION: More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

A genomic map of climate adaptation in Mediterranean cattle breeds.

Domestic species such as cattle (Bos taurus taurus and B. t. indicus) represent attractive biological models to characterize the genetic basis of short-term evolutionary response to climate pressure induced by their post-domestication history. Here, using newly generated dense SNP genotyping data, we assessed the structuring of genetic diversity of 21 autochtonous cattle breeds from the whole Mediterranean basin and performed genome-wide association analyses with covariables discriminating the different Mediterranean climate subtypes. This provided insights into both the demographic and adaptive histories of Mediterranean cattle. In particular, a detailed functional annotation of genes surrounding variants associated with climate variations highlighted several biological functions involved in Mediterranean climate adaptation such as thermotolerance, UV protection, pathogen resistance or metabolism with strong candidate genes identified (e.g., NDUFB3, FBN1, METTL3, LEF1, ANTXR2 and TCF7). Accordingly, our results suggest that main selective pressures affecting cattle in Mediterranean area may have been related to variation in heat and UV exposure, in food resources availability and in exposure to pathogens, such as anthrax bacteria (Bacillus anthracis). Furthermore, the observed contribution of the three main bovine ancestries (indicine, European and African taurine) in these different populations suggested that adaptation to local climate conditions may have either relied on standing genomic variation of taurine origin, or adaptive introgression from indicine origin, depending on the local breed origins. Taken together, our results highlight the genetic uniqueness of local Mediterranean cattle breeds and strongly support conservation of these populations.

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.

WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle.

BACKGROUND: The advent and democratization of next generation sequencing and genotyping technologies lead to a huge amount of data for the characterization of population genetic diversity in model and non model-species. However, efficient storage, management, cross-analyzing and exploration of such dense genotyping datasets remain challenging. This is particularly true for the bovine species where many SNP datasets have been generated in various cattle populations with different genotyping tools. DESCRIPTION: We developed WIDDE, a Web-Interfaced Next Generation Database that stands as a generic tool applicable to a wide range of species and marker types ( http://widde.toulouse.inra.fr). As a first illustration, we hereby describe its first version dedicated to cattle biodiversity, which includes a large and evolving cattle genotyping dataset for over 750,000 SNPs available on 129 (89 public) different cattle populations representative of the world-wide bovine genetic diversity and on 7 outgroup bovid species. This version proposes an optional marker and individual filtering step, an export of genotyping data in different popular formats, and an exploration of genetic diversity through a principal component analysis. Users can also explore their own genotyping data together with data from WIDDE, assign their samples to WIDDE populations based on distance assignment method and supervised clustering, and estimate their ancestry composition relative to the populations represented in the database. CONCLUSION: The cattle version of WIDDE represents to our knowledge the first database dedicated to cattle biodiversity and SNP genotyping data that will be very useful for researchers interested in this field. As a generic tool applicable to a wide range of marker types, WIDDE is overall intended to the genetic diversity exploration of any species and will be extended to other species shortly. The structure makes it easy to include additional output formats and new tools dedicated to genetic diversity exploration.

TropGeneDB, the multi-tropical crop information system updated and extended.

TropGeneDB (http://tropgenedb.cirad.fr) was created to store genetic, molecular and phenotypic data on tropical crop species. The most common data stored in TropGeneDB are molecular markers, quantitative trait loci, genetic and physical maps, genetic diversity, phenotypic diversity studies and information on genetic resources (geographic origin, parentage, collection). TropGeneDB is organized on a crop basis with currently nine public modules (banana, cocoa, coconut, coffee, cotton, oil palm, rice, rubber tree, sugarcane). Crop-specific Web consultation interfaces have been designed to allow quick consultations and personalized complex queries. TropGeneDB is a component of the South Green Bioinformatics Platform (http://southgreen.cirad.fr/).

Spatial and temporal diversity of Simulium damnosum s.l. gut microbiota and association with Onchocerca volvulus infection in Cameroon.

Arthropod microbiota plays an important role in host physiology, and there is growing interest in using vector symbionts to modify vector competence and control parasite transmission. This study aims to characterise the blackfly Simulium damnosum s.l. gut microbiota and to explore possible associations with various bio-ecological determinants of the Onchocerca volvulus establishment and the transmission in blackfly. Adult female blackflies were caught in three Cameroonian health districts belonging to different bioecological zones endemic for onchocerciasis. Flies were dissected and qPCR screened for Onchocerca volvulus infection. The diversity of the blackflies gut microbiota was assessed by high-throughput sequencing of the V3-V4 hypervariable region of the bacterial 16S ribosomal RNA. Subsequent metataxo-genomic, multivariate, and association analysis were used to investigate the variables that influence the microbiota diversity. Transmission index rates ranging from 20.7 to 6.0 % and 6.2-2.0 % for infection and infectivity rates, respectively, indicate ongoing transmission of onchocerciasis across all surveyed health districts. The identified bacterial taxa were clustered into four phyla, five classes, and 23 genera. The S. damnosum s.l. gut microbiota was dominated by Wolbachia and by Rosenbergiella in Wolbachia-free Simulium. Significant differences were observed in the diversity of S. damnosum s.l. microbiota concerning parity status (P = 0.007), health district of origin (P = 0.001), and the presence of the Onchocerca volvulus. Simulium from the Bafia health district also showed increased bacterial diversity between two consecutive years (P = 0.001). Four bacterial taxa, including Serratia, were associated with the absence of the O. volvulus infection. These results indicate that S. damnosum s.l. from different onchocerciasis foci in Cameroon, exhibit distinguishable gut microbial compositions which are dynamic over time. Some bacterial species are associated with the O. volvulus infection and could be further investigated as biological target/tool for vector modified-based onchocerciasis control.

Managing High-Density Genotyping Data with Gigwa.

Next 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.

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.fr.

Bacteriome Diversity of Blackflies' Gut and Association with Onchocerca volvulus, the Causative Agent of Onchocerciasis in Mbam Valley (Center Region, Cameroon).

Vector control using larvicides is the main alternative strategy to address limits of preventive chemotherapy using ivermectin for the control of onchocerciasis. However, it remains substantially limited by implementation difficulties, ecological concerns and the resistance of vector populations. Therefore, efficient and environmentally safe alternative control strategies are still needed. This study explores the composition of the blackfly bacteriome and its variability in the presence of Onchocerca volvulus infection, in order to determine their potential as a novel vector control-based approach to fight onchocerciasis. An entomological survey of a collection of samples was performed in the Bafia health district, a historical endemic focus for onchocerciasis in Cameroon. A total of 1270 blackflies were dissected and the infection rate was 10.1%, indicative of ongoing transmission of onchocerciasis in the surveyed communities. Sequencing process of blackflies' gut DNA for bacteria screening revealed 14 phyla and 123 genera, highlighting the diversity of gut blackflies bacterial communities. Eight bacteria formed the core of blackfly bacteriome and Wolbachia was the predominant genus with 73.4% of relative abundance of blackflies' gut bacterial communities. Acidomonas and Roseanomas genera were significantly abundant among infected blackflies (p = 0.01), whereas other genera such as Brevibacterium and Fructobacillus were associated with the absence of infection (p = 0.0009). Differences in gut bacterial distribution of blackflies according to their infection status by the parasite suggest a causal relationship between the bacteriome composition and the onset of blackflies' infection by O. volvulus or vice versa. Blackfly native bacteria are then potentially involved in infection by O. volvulus, either by facilitating or preventing the parasite infestation of the vector. These bacteria represent an interesting potential as a biological tool/target for a novel approach of vector control to fight onchocerciasis.

Modulation of trypanosome establishment in Glossina palpalis palpalis by its microbiome in the Campo sleeping sickness focus, Cameroon.

The purpose of this study was to investigate factors involved in vector competence by analyzing whether the diversity and relative abundance of the different bacterial genera inhabiting the fly's gut could be associated with its trypanosome infection status. This was investigated on 160 randomly selected G. p. palpalis flies - 80 trypanosome-infected, 80 uninfected - collected in 5 villages of the Campo trypanosomiasis focus in South Cameroon. Trypanosome species were identified using specific primers, and the V4 region of the 16S rRNA gene of bacteria was targeted for metabarcoding analysis in order to identify the bacteria and determine microbiome composition. A total of 261 bacterial genera were identified of which only 114 crossed two barriers: a threshold of 0.01% relative abundance and the presence at least in 5 flies. The secondary symbiont Sodalis glossinidius was identified in 50% of the flies but it was not considered since its relative abundance was much lower than the 0.01% relative abundance threshold. The primary symbiont Wigglesworthia displayed 87% relative abundance, the remaining 13% were prominently constituted by the genera Spiroplasma, Tediphilus, Acinetobacter and Pseudomonas. Despite a large diversity in bacterial genera and in their abundance observed in micobiome composition, the statistical analyzes of the 160 tsetse flies showed an association with flies' infection status and the sampling sites. Furthermore, tsetse flies harboring Trypanosoma congolense Savanah type displayed a different composition of bacterial flora compared to uninfected flies. In addition, our study revealed that 36 bacterial genera were present only in uninfected flies, which could therefore suggest a possible involvement in flies' refractoriness; with the exception of Cupriavidus, they were however of low relative abundance. Some genera, including Acinetobacter, Cutibacterium, Pseudomonas and Tepidiphilus, although present both in infected and uninfected flies, were found to be associated with uninfected status of tsetse flies. Hence their effective role deserves to be further evaluated in order to determine whether some of them could become targets for tsetse control of fly vector competence and consequently for the control of the disease. Finally, when comparing the bacterial genera identified in tsetse flies collected during 4 epidemiological surveys, 39 genera were found to be common to flies from at least 2 sampling campaigns.

metaXplor: an interactive viral and microbial metagenomic data manager.

BACKGROUND: 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.

The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon.

BACKGROUND: A number of reports have demonstrated the role of insect bacterial flora on their host's physiology and metabolism. The tsetse host and vector of trypanosomes responsible for human sleeping sickness (human African trypanosomiasis, HAT) and nagana in animals (African animal trypanosomiasis, AAT) carry bacteria that influence its diet and immune processes. However, the mechanisms involved in these processes remain poorly documented. This underscores the need for increased research into the bacterial flora composition and structure of tsetse flies. The aim of this study was to identify the diversity and relative abundance of bacterial genera in Glossina palpalis palpalis flies collected in two trypanosomiasis foci in Cameroon. METHODS: Samples of G. p. palpalis which were either negative or naturally trypanosome-positive were collected in two foci located in southern Cameroon (Campo and Bipindi). Using the V3V4 and V4 variable regions of the small subunit of the 16S ribosomal RNA gene, we analyzed the respective bacteriome of the flies' midguts. RESULTS: We identified ten bacterial genera. In addition, we observed that the relative abundance of the obligate endosymbiont Wigglesworthia was highly prominent (around 99%), regardless of the analyzed region. The remaining genera represented approximately 1% of the bacterial flora, and were composed of Salmonella, Spiroplasma, Sphingomonas, Methylobacterium, Acidibacter, Tsukamurella, Serratia, Kluyvera and an unidentified bacterium. The genus Sodalis was present but with a very low abundance. Globally, no statistically significant difference was found between the bacterial compositions of flies from the two foci, and between positive and trypanosome-negative flies. However, Salmonella and Serratia were only described in trypanosome-negative flies, suggesting a potential role for these two bacteria in fly refractoriness to trypanosome infection. In addition, our study showed the V4 region of the small subunit of the 16S ribosomal RNA gene was more efficient than the V3V4 region at describing the totality of the bacterial diversity. CONCLUSIONS: A very large diversity of bacteria was identified with the discovering of species reported to secrete anti-parasitic compounds or to modulate vector competence in other insects. For future studies, the analyses should be enlarged with larger sampling including foci from several countries.

Gigwa v2-Extended and improved genotype investigator.

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.

Benchmarking database systems for Genomic Selection implementation.

MOTIVATION: With high-throughput genotyping systems now available, it has become feasible to fully integrate genotyping information into breeding programs. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able to collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize it in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs, one would need an efficient genotyping data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems. RESULTS: We found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix. AVAILABILITY: http://gobiin1.bti.cornell.edu:6083/projects/GBM/repos/benchmarking/browse.

Using TropGeneDB: A Database Containing Data on Molecular Markers, QTLs, Maps, Genotypes, and Phenotypes for Tropical Crops.

TropGeneDB ( http://tropgenedb.cirad.fr ) is a web database that manages genomic, genetic, and phenotypic information on tropical crops. It is organized on a crop basis with currently nine public modules: banana, cocoa, coconut, coffee, cotton, oil palm, rice, rubber tree, and sugarcane. TropGeneDB contains data on molecular markers, quantitative trait loci (QTLs), genetic and physical maps, genotyping and phenotyping studies, and information on genetic resources (geographic origin, parentage, collection). Crop-specific web interfaces have been designed to allow quick consultations as well as personalized complex queries.

Gigwa-Genotype investigator for genome-wide analyses.

BACKGROUND: Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions. DESCRIPTION: Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats. CONCLUSIONS: The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.