C02
Forest Tree GnpIS: an Information System Dedicated to Forest Tree Genetics, Genomics and Phenomics

Date: Saturday, January 14, 2017
Time: 1:45 PM
Room: California
Célia Michotey , URGI, INRA, Université Paris-Saclay, Versailles, France
Christel Anger , INRA - GBFOR, Orléans, France
François Ehrenmann , INRA, Cestas, France
Véronique Jorge , INRA - AGPF, Orléans, France
Odile Rogier , INRA - AGPF, Orléans, France
Catherine Bastien , INRA - AGPF, Orléans, France
Christophe Plomion , INRA - BIOGECO, Cestas, France
Christian Pichot , INRA - URFM, Avignon, France
Hadi Quesneville , INRA - URGI, Versailles, France
Anne-Francoise Adam-Blondon , INRA - URGI, Versailles, France
Due to the major technological advances both in genomics and phenomics, it is now possible to quickly obtain large amounts of data at low cost. One of the consequences is the critical need for data management, with the opportunity to make these datasets interoperable, thus enhancing their reuse and enrichment.

GnpIS is an original information system (IS) able to manage these data. It is designed to integrate and link genetic, genomic and phenomic data into a single environment, allowing researchers to explore information from different angles.

“Forest tree GnpIS” is a GnpIS focused on forest tree data. These resources are accessible through a web portal (https://urgi.versailles.inra.fr/gnpis/) whose main entry point is a tool using keywords for data discovery and dedicated tools facilitating more specific queries and data retrieval.

In order to make data submission easier for research teams, workflows are implemented to automate data flow between local sources, GnpIS and other international IS if necessary. This way, data from several forest tree species have been integrated into the Forest tree GnpIS (e.g. 16800 accessions, 18 phenotyping trials, 13700 markers and 1000 QTLs, cf. https://urgi.versailles.inra.fr/Species/Forest-trees/Database-overview). I will show you how to navigate through these data and more precisely: 1) from a genome browser and its annotation access genetic maps (via markers and QTLs), 2) from a QTL of interest get the phenotyping results of its trait and select the accessions with the most interesting results, 3) refine your selection by studying an accession pedigree and genotyping results.