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Génétique Quantitative et Évolution - Le Moulon

- ABI - SOFT group

Missions

ABI-Soft team aims to develop, deploy and provide analysis tools and databases useful for scientists of the lab. The team also provides support to development projects carried out by the research teams of the lab. Abi-Soft aims also to make them available to the plant science community through the French national forge for research and higher education (SourceSup or forgemia) and efficient deployment solutions (virtual machines, containers). The team is also in charge of the training of the scientists (local and their partners) to use the tools developed.
ABI-Soft works in close collaboration with the ABI-SYS team which maintains the infrastructure hosting the local instances of our applications.

Currently, ABI-Soft develops several data management tools (Thaliadb, SHiNeMaS and DiverCILand) and analysis tools (BioMercator and OptimaRs) that are components of a global information system dedicated to plant breeding.

Current projects

ThaliaDB

In collaboration with GQMS team. ThaliaDB is a web application with its database that manages plant accessions, seeds lots, SNP markers, genotyping rawddata and field phenotyping elaborated data. This tool is useful for lab data management, for data curation, to prepare datasets for genome wide assocation studies or genomic selection analysis and for data sharing with partners and external data repositories (Dataverse).

ThaliaDB screen

ThaliaDB screen

The software development started in 2004, two versions were developped in JAVA langage. A new version (V3) in Python/Django framework/PostgreSQL/MongoDB started in 2015 for maize species and is now installed at QGE-Le Moulon. It is used to manage data produced by GQMS team and their partners in the frame of scientific projects, such as Amaizing at national, or at european projects (DROPS). Other instances will be deployed for other species and projects in the following months, in collaboration with external partners.

Links to the project :

SHiNeMaS

SHiNeMaS screen

SHiNeMaS screen

In collaboration with DEAP team. SHiNeMaS (Seeds History Management and Network System) is a web application and its database (Python/Django/PostGreSQL) that manages relationships between seeds distributed in an network of farms and their field phenotypic evaluation results in several environments (climate, soil), (See figure left). The tool is used today for the management of data of several projects on bread wheat, in a context of participative science, agroecology and organic agriculture. Other instances on other species are in development in collaboration with external partners such as the members of the RSP (‘Réseau des Semences paysannes’), the collaboration with RSP started in 2003.

Links to the project :

DiverCILand

DiverCILand

DiverCILand

DiverCILand, for Diversity of Crops In Landscape, is a data management web application. The development started in 2019, in the context of the European Horizon 2020 RustWatch project. This project aims to establish a stakeholder driven early-warning system to improve preparedness and resilience to emerging rust diseases on wheat in Europe. DiverCILand makes possible to store varieties description and manage DUS and VCUS data, description data of cultivated landscape and also genetic data on variety characterization. DiverCILand offers a set of visualization interfaces with variety card, containing accession information, interfaces presenting life cycles of varieties and varieties deployment. The power of DiverCILand is its ability to generate maps based on varietal deployment in Europe. In the context of the RustWatch project, this tool therefore allows to centralize, manage and capitalize on data useful to study wheat resistance to rust epidemics in Europe.

Links to the project :

Biomercator

In collaboration with GQMS team.

Biomercator screen

Biomercator screen

Biomercator, an analysis tool (JAVA) useful for gene discovery involved in the variation of agronomical traits. It allows displaying genetic maps and genome annotation data (markers, QTLs). It provides tools for making meta-analysis of QTLS. The first version was published by A. Arcade, A. Labourdette, M. Falque, B. Mangin, F. Chardon, A. Charcosset, and J. Joets, in Bioinformatics 2004. The version 3 was published by O. Sosnowski, A. Charcosset, and J. Joets in Bioinformatics 2012.
The new version currently in development (V5) will provide tools to explore GWAS analyses.

Links to the project :

OptimaRs

OptimaRs is a decision support tool to conduct Marker-Assisted Selection programmes.

OptimaRs screen

OptimaRs screen

The main goal of OptimaRs is to help breeders in implementing their Marker-Assisted Selection (MAS) project. With the possibility to consider a multi-allelic context, it opens new prospects to further accelerate genetic gain by assembling favorable alleles issued from diverse parents.

OptimaRs includes in a Graphical User Interface (GUI), three different modules corresponding to the different steps of a selection programme :

Using information given by markers located in the vicinity of the estimated QTL positions, probabilities of favorable parental QTL allele transmission are computed in different MAS schemes and mating designs (intercrossing, selfing, backcrossing, double haploids, RIL) with the possibility of considering generations without genotypic information (step 1). Then strategies are proposed to select the best plants (step 2), and efficiently intermate them based on the expected value of their progenies (step 3).

Link to the project (version C++) :

Please contact Yannick De Oliveira, for more details and partnership on any project.

Previous staff

  • Nesrine Mouhoubi (2020-2021), Master Data Science Paris-Saclay University
  • Laetitia Courgey (2018-2020), Master MIAGE Paris Dauphine University (SHiNeMaS, ThaliaDB)
  • Alice Beaugrand (2016-2018), Master 2 University Paris-Saclay, then CDD (SHiNeMaS, ThaliaDB)
  • Artur Robieux (2018), Master 2 University Paris-Saclay (ThaliaDB)
  • Marine Daniel-Dit Andrieu (2017), Master 2 University Paris-Saclay (Phenofield-Validator)
  • Mélanie Polart-Donat (2017), Master 2 University Paris-Saclay (SHiNeMaS)
  • Eva Dechaux (2017), Master 2 University Paris-Saclay (SHiNeMaS)
  • Lan-Anh Nguyen (2016), DUT Université d’Auvergne, (ThaliaDB)
  • Olivier Akmansoy (2016), Ecoles des Mines Douai (ThaliaDB)
  • Aichatou Aboubacar-Amadou (2016), Master 2 Univ. Reims (SHiNeMaS)
  • Lydia Aït-Brahim (2014 – 2016), Master 2 Université Paris-Saclay, then CDD (Biomercator)
  • Guy Ross Assoumou (2012 – 2015), CDD IE/Software engineer (ThaliaDB)
  • Jocelyn Chêne (2015), Master 2 Univ. Nantes (ANR Bakery project)
  • Laura Burlot (2014), Master 2 Univ. Lyon, then CDD IE/ software engineer (SHiNeMaS)
  • Marie Lefebvre (2014), Master2 Univ. Nantes (SHiNeMaS)
  • Darkawi Madi (2012), Master 2 (SHiNeMaS)

Members

  • Yannick De Oliveira Engineer (INRAE)
  • Franck Gauthier Engineer (INRAE)
  • Pierre Montalent Engineer (INRAE)
  • Elise Peluso Licence student (INRAE)
  • Mélanie Polart-Donat Engineer (INRAE)

Former members

Delphine Steinbach Research Engineer (1970), Laetitia Courgey Master Apprentissage (2018-2020)

Publications

  • Vidal A., Gauthier F. , Rodrigez W., Guiglielmoni N., Leroux D., Chevrolier N., Jasson S., Tourrette E., Martin OC., Falque M.. (2022) SeSAM: software for automatic construction of order-robust linkage maps. BMC Bioinformatics, 1 (23) 499
  • De Oliveira Y. , Burlot L., Dawson JC., Goldringer I., Madi D., Rivière P., Steinbach D., van Frank G., Thomas M.. (2020) SHiNeMaS: a web tool dedicated to seed lots history, phenotyping and cultural practices. Plant Methods, 1 (16) 98
  • Lopez Arias DC., Chastellier A., Thouroude T., Bradeen J., Van Eck L., De Oliveira Y. , Paillard S., Foucher F., Hibrand-Saint Oyant L., Soufflet-Freslon V.. (2020) Characterization of black spot resistance in diploid roses with QTL detection, meta-analysis and candidate-gene identification. Theor Appl Genet,
  • Urien C., Legrand J., Montalent P. , Casaregola S., Sicard D.. (2019) Fungal Species Diversity in French Bread Sourdoughs Made of Organic Wheat Flour. Front. Microbiol., (10) 201
  • Alaux M., Rogers J., Letellier T., Flores R., Alfama F., Pommier C., Mohellibi N., Durand S., Kimmel E., Michotey C., Guerche C., Loaec M., Lainé M., Steinbach D., Choulet F., Rimbert H., Leroy P., Guilhot N., Salse J., Feuillet C., Paux E., Eversole K., Adam-Blondon AF., Quesneville H., International Wheat Genome Sequencing Consortium. (2018) Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biol, 1 (19) 111
  • Adam-Blondon AF., Alaux M., Durand S., Letellier T., Merceron G., Mohellibi N., Pommier C., Steinbach D., Alfama F., Amselem J., Charruaud D., Choisne N., Flores R., Guerche C., Jamilloux V., Kimmel E., Lapalu N., Loaec M., Michotey C., Quesneville H., van Dijk ADJ.. (2017) Mining Plant Genomic and Genetic Data Using the GnpIS Information System. , (1533) 103-117
  • Perronne R., Makowski D., Goffaux R., Montalent P. , Goldringer I.. (2017) Temporal evolution of varietal, spatial and genetic diversity of bread wheat between 1980 and 2006 strongly depends upon agricultural regions in France. Agriculture, Ecosystems & Environment, (236) 12-20