Biology subjects

Tranchant-Dubreuil, C.

Publications and source records attributed to Tranchant-Dubreuil, C..

7 recordsLinked to original sources

bioRxiv2025

GraTools, an user-friendly tool for exploring and manipulating pangenome variation graphs

BackgroundPangenome variation graphs (PVGs), which represent genomic diversity through multiple genomes alignment, are powerful tools for studying genomic variations in populations. However, current tools often lack integration, efficiency, or require format conversions, to use them, hindering their usability. ResultsHere, we introduce GraTools, a member of the GraSuite [1], and a fast and user-friendly command-line tool for manipulating PVGs using the original GFA file. After a one-time graph import, GraTools enables rapid subgraph extraction, FASTA sequence retrieval, and comprehensive analyses, including core/dispensable genome ratio calculation or group-specific segment identification. The import step results in conversion in standard data formats (BAM/BED), enabling the reuse of well-optimized existing tools, allowing an efficient storage and the querying of the PVGs large complex data structures. Scalability is ensured by a modular architecture supporting parallel processing and asynchronous I/O operations. GraTools supports coordinates defined on both the primary reference as well as from alternative genomes within the graph without re-import, and its outputs can be easily visualized or manipulated using external tools. Using an Asian rice pangenome graph (13 accessions), we demonstrate its ability to easily extract subgraphs, compute depth statistics, and identify subspecies-specific segments. An intuitive command-line interface, a real-time execution feedback and a detailed logging system make this tool suitable for a wide range of applications, from population genetics to breeding and genomic medicine, for both biologists and bioinformaticians. ConclusionsThrough its unified graph manipulation interface, GraTools offers an interesting alternative to the few existing tools for manipulating PVGs, facilitating rapid, efficient and flexible downstream analyses. It is available as an open-source tool (GNU GPLv3), with its documentation available at https://gratools.readthedocs.io.

bioinformatics↗

bioRxiv2023

The genome and population genomics of allopolyploid Coffea arabica reveal the diversification history of modern coffee cultivars

Coffea arabica, an allotetraploid hybrid of C. eugenioides and C. canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000-610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred [~]30.5 kya, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

genomics↗

bioRxiv2023

A strongly improved assembly of the pearl millet reference genome using OxfordNanopore long reads and optical mapping

Pearl millet (Pennisetum glaucum (L.)) R. Br. syn. Cenchrus americanus (L.) Morrone) is an important crop in South Asia and sub-Saharan Africa which contributes to ensure food security. Its genome has an estimated size of 1.76 Gb and displays a high level of repetitiveness above 80%. A first assembly was previously obtained for the Tift 23D2B1-P1-P5 cultivar genotype using short-read sequencing technologies. This assembly is however incomplete and fragmented with around 200 Mb unplaced on chromosomes. We report here an improved quality assembly of the pearl millet Tift 23D2B1-P1-P5 cultivar genotype obtained with an approach combining Oxford Nanopore long reads and Bionano Genomics optical maps. This strategy allowed us to add around 200 Mb at the chromosome-level assembly. Moreover we strongly improved continuity in the order of the contigs and scaffolds wihtin the chromosomes, particularly in the centromeric regions. Notably, we added more than 100 Mb around the centromeric region on chromosome 7. This new assembly also displayed a higher gene completeness with a complete BUSO score of 98.4% using the Poales database. This more complete and higher quality assembly of the Tift 23D2B1-P1-P5 genotype now available to the community will help in the development of research on the role of structural variants, and more broadly in genomics studies and the breeding of pearl millet.

genomics↗

bioRxiv2022

FrangiPANe, a tool for creating a panreference using left behind reads

We present here FrangiPANe, a pipeline developed to build panreference using short reads through a map-then-assemble strategy. Applying it to 248 African rice genomes using an improved CG14 reference genome, we identified an average of 8 Mb of new sequences and 5,290 new contigs per individual. In total, 1.4 G of new sequences, consisting of 1,306,676 contigs, were assembled. We validated 97.7% of the contigs of the TOG5681 cultivar individual assembly from short reads on a newly long reads genome assembly of the same TOG5681 cultivar. FrangiPANe also allowed the anchoring of 31.5% of the new contigs within the CG14 reference genome, with a 92.5% accuracy at 2kb span. We annotated in addition 3,252 new genes absent from the reference. FrangiPANe was developed as a modular and interactive application to simplify the construction of a panreference using the map-then-assemble approach. It is available as a Docker image containing (i) a Jupyter notebook centralizing codes, documentation and interactive visualization of results, (ii) python scripts and (iii) all the software and libraries requested for each step of the analysis. We foreseen our approach will help leverage large-scale illumina dataset for pangenome studies in GWAS or detection of selection.

plant biology↗

bioRxiv2020

Aquaporins are main contributors of root hydraulic conductivity in pearl millet

Pearl millet is a key cereal for food security in arid and semi-arid regions but its yield is increasingly threatened by water stress. Physiological mechanisms consisting in saving water or increasing water use efficiency can alleviate that stress. Aquaporins (AQP) are water channels contributing to plant hydraulic balance that are supposedly involved in these mechanisms by mediating root water transport. However, AQP remain largely uncharacterized in pearl millet. Here, we studied AQP function in root water transport in two pearl millet lines contrasting for water use efficiency (WUE). We observed that these lines were also contrasting for root hydraulic conductivity (Lpr) and AQP contribution to Lpr, the line with lower WUE showing significantly higher AQP contribution to Lpr. To investigate the AQP isoforms contributing to Lpr, we developed genomic approaches to first identify the entire AQP family in pearl millet and second study the plasma membrane intrinsic proteins (PIP) gene expression profile. We identified and annotated 33 AQP genes in pearl millet among which ten encoded PIP isoforms. PgPIP1-3 and PgPIP1-4 were significantly more expressed in the line showing lower WUE, higher Lpr and higher AQP contribution to Lpr. Overall, our study suggests that AQP from the PIP1 family are the main contributor of Lpr in pearl millet and are possibly associated to whole plant water use mechanisms. This study paves the way for further investigations on AQP functions in pearl millet hydraulics and adaptation to environmental stresses. The newly sequenced nucleotide sequences reported in this article have been submitted to GenBank under the submission number 2333840 (TPA grp467567). Assignment of GenBank accession number is in process.

plant biology↗

bioRxiv2020

Genome wide association study pinpoints key agronomic QTLs in African rice Oryza glaberrima

BackgroundAfrican rice, Oryza glaberrima, is an invaluable resource for rice cultivation and for the improvement of biotic and abiotic resistance properties. Since its domestication in the inner Niger delta ca. 2500 years BP, African rice has colonized a variety of ecologically and climatically diverse regions. However, little is known about the genetic basis of quantitative traits and adaptive variation of agricultural interest for this species. ResultsUsing a reference set of 163 fully re-sequenced accessions, we report the results of a Genome Wide Association Study carried out for African rice. We investigated a diverse panel of traits, including flowering date, panicle architecture and resistance to Rice yellow mottle virus. For this, we devised a pipeline using complementary statistical association methods. First, using flowering time as a target trait, we demonstrated that we could successfully retrieve known genes from the rice flowering pathway, and identified new genomic regions that would deserve more study. Then we applied our pipeline to panicle- and resistance-related traits, highlighting some interesting QTLs and candidate genes (including Rymv1 for resistance and SP1, Ghd7.1, APO1 and OsMADS1 for panicle architecture). Lastly, using a high-resolution climate database, we performed an association analysis based on climatic variables, searching for genomic regions that might be involved in adaptation to climatic variations. ConclusionOur results collectively provide insights into the extent to which adaptive variation is governed by sequence diversity within the O. glaberrima genome, paving the way for in-depth studies of the genetic basis of traits of interest that might be useful to the rice breeding community.

plant biology↗

bioRxiv2018

TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses

The advent of NGS has intensified the need for robust pipelines to perform high-performance automated analyses. The required softwares depend on the sequencing method used to produce raw data (e.g. Whole genome sequencing, Genotyping By Sequencing, RNASeq) as well as the kind of analyses to carry on (GWAS, population structure, differential expression). These tools have to be generic and scalable, and should meet the biologists needs.\n\nHere, we present the new version of TOGGLe (Toolbox for Generic NGS Analyses), a simple and highly flexible framework to easily and quickly generate pipelines for large-scale second-and third-generation sequencing analyses, including multi-threading support. TOGGLe comprises a workflow manager designed to be as effortless as possible to use for biologists, so the focus can remain on the analyses. Embedded pipelines are easily customizable and supported analyses are reproducible and shareable. TOGGLe is designed as a generic, adaptable and fast evolutive solution, and has been tested and used in large-scale projects with numerous samples and organisms. It is freely available at http://toggle.southgreen.fr/ under the GNU GPLv3/CeCill-C licenses) and can be deployed onto HPC clusters as well as on local machines.

bioinformatics↗