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MetaQTL is a ANR bioinformatics project 2009-2011 (extended 6 months in 2012) dealing with methods and bioinformatics tools for QTL meta-analysis and integration of meta-QTL, physical maps and genome sequence. URGI platform is one partner of this project.

    ANR funded project ANR-PCS-08-GENO-126

  Over several years, large efforts have been made to produce crop genetic and genomic data at genome scale. To take full advantage of these data, integration is required at various levels of resolution. Quantitative Trait Loci (QTL) mapping can generally be undertaken on different populations and levels of inbreeding. Integrative QTL meta-analysis methods have been developed to take full advantage of existing results to more accurately predict the most probable location of QTL. Methods have also been devised to build consensus map by integrating genetic map and QTL map positions and making it easier to search for co-localization between genes and QTL. These methods have been implemented into the BioMercator software thanks to the previous support of Génoplante and The Generation Challenge program. This tool is widely used by the community but suffers from a number of limitations, that will be addressed in this proposal.. In particular, a new and urgent requirement is to be able to project meta-QTL onto a physical map or genome sequence. This will allow a user to integrate QTL mapping results with genome annotation usually provided by genome browsers that become central tool for research as soon as genomic resources are made available. To promote sharing of results produced with BioMercator, the URGI Gnp Information System need to be extended to 1) store this new data in GnpMap and 2) make them available for query or display at the genetic map and genome levels.

 The new developments proposed in this project aim at benefiting the wide scientific community and also take into account specific requirements for particular plant species. To ensure that this will be addressed adequately, this project will bring together a large panel of public and private researchers working on several crop and forestry species (maize, wheat, peach, apricot, oak, poplar), who will contribute to the definition of the specifications and test of an improved version of BioMercator and GnpIS.

URGI partner contact : Delphine Steinbach at, scientific coordinator for URGI GnpMap-MetaQTL new developments

Duration: 01/01/2009 to 31/12/2012

Coordinator: Johann Joets


Laboratory Address Persons Links
logo INRAE UMR 0320 INRA / Université Paris XI/ AgroParisTech
Ferme du Moulon
91190 Gif-sur-Yvette
Johann Joets, Olivier Sosnowski Ferme du Moulon
Logo_URGI UR URGI INRA Centre de Versailles
Route de Saint-Cyr
78000 Versailles
Erik Kimmel, Dorothée Valdenaire, Delphine Steinbach Unité de Recherche en Génomique Info
Biogeco UMR 1202 BIOGECO / Université Bordeaux 1
Site de Recherches Forêt Bois de Pierroton
69 route d'Arcachon
33612 Cestas Cedex
Antoine Kremer Biodiversité, gènes & communautés
UMR GDEC UMR 1095 Génétique, Diversité et Ecophysiologie des Céréales
INRA Site de Crouël
234 avenue du Brézet
63100 Clermont-Ferrand
Jacques Legouis Génétique, Diversité et Ecophysiologie des Céréales
Equipe Génomique Amont
ZI du Brezet
8 rue des Frères Lumière
63028 Clermont-Ferrand Cedex 2
Frédéric Sapet, Olivier Dugas  
Centre INRA d'Orléans
2163 avenue de la Pomme de Pin
CS 40001 – Ardon
45075 Orléans Cedex 2
Véronique Jorge Unité de Recherche Amélioration, Génétique et Physiologie Forestières
Campus INRA de Bordeaux Aquitaine
71, Avenue Edourd Boutlaux – BP 81
33883 Villenave D'Ornon Cedex
Véronique Decroocq Génomique Diversité Pouvoir Pathogène
Syngenta   Marc Sawkins  


The Plant Genetics Group had developed the first version of the BioMercator software and has conducted several methodological works on map compilation and QTL meta-analysis. More generally this group is involved in many programs aiming at identify maize genome sequence underlying complex genetic traits using omics data. The URGI has developed a complete information system for plant omics and is now focusing on the integration of the data hosted by this environment. Syngenta and Biogemma are private breeding groups highly motivated and involved in many programs using omics data for plant breeding innovation. The other partners are among leading groups for their species of interest; the “Unité d'Amélioration et Physiologie des Arbres Forestiers” for populus, the “INRA/UBP UMR 1095 Génétique, Diversité et Ecophysiologie des Céréales” for wheat, the “Unité Mixte de Recherches Génomique et Diversité du Pouvoir pathogène INRA-Université Bordeaux II” for prunus and the “UMR BIOGECO” for oak.


What is BioMercator ?

A new challenge in breeding programs is to integrate information from genomics and that from QTL analysis, in order to identify sequences controlling the variation of important traits. Thus, discovering co-locations between candidate genes and QTLs is an essential step. Despite the outburst of genomic databases, constructing an integrative genetic map compiling genes, QTLs and other loci gathered from multiple maps remains a manual and tedious task. Those QTLs detected in independent experiments and located in a same region of a chromosome might be in fact several estimations of the position of one single QTL. This assertion can be verified by means of appropriate statistical tools such as meta-analysis, which consists in combining data from diverse sources in a single study. Meta-analysis is a useful tool to synthesize dense QTL information and to refine QTL position.
 BioMercator is a stand-alone application which automatically performs these tasks. (1) BioMercator offers a user-friendly graphical map browser. Genetic map and QTL data are loaded from text files. (2) BioMercator performs automatic compilations of several genetic maps. A consensus genetic map can be built from multiple individual maps by iterative projection of QTLs, genes and other loci. (3) BioMercator computes meta-analysis of QTLs. This statistical method determines the most likely number of "real" QTLs represented by n QTLs detected in independent experiments for the same trait or related ones. Finally, the graphical interface allows to visualize co-locations between consensus QTLs and genes.

What is MetaQTL ?

MetaQTL is a suite of programs designed to carry out meta-analysis of QTL mapping experiments. A QTL mapping experiment consists in a genetic linkage map and a set of QTL which have been detected and positioned onto the genetic linkage map. These programs can perform various tasks, including reformatting, analyzing data and visualizing the results of the analyses. Presently the programs can handle data from backcross, intercrosses and recombinant inbreds, as well as a few other experimental designs.
 Since the last decade, the advent of molecular markers have accelerated the pace of discovering the loci which are implied in quantitative trait variation. QTL mapping usually begins with the collection of genotypic (based on molecular markers) and phenotypic data from a segregating population. First, from the genoptypic data the markers are both ordered and positioned on a genetic map using standard linkage mapping approaches. Secondly, refinement of analytical methods have enabled to detect one ore several QTL on each chromosome. Nevertheless due to the limiting number of individuals and generations in usual experiment this approach generally leads to QTL locations with a confidence interval (CI) around 10 cM which in plant generally corresponds to a thousand of genes or more. Due to its relative simplicity and its compelling concept QTL mapping has been widely used and more and more QTL detection results are now available in public databases (e.g in maize at
 One of the main purpose of these databases was to facilitate the comparison of different QTL detection results by providing both standard description of these results and ontologies. Relevance of comparative analysis of QTL studies have been illustrated by several authors. However these studies often relied on simple descriptive statistics.

What is GnpIS ?

GnpIS is the URGI global information system bridging plant genomics and genetic data.

  • One objectiv of MetaQTL project and URGI partnership, was to improve GnpIS and its genetic mapping database module called GnpMap, to manage metaQTL analysis data.
  • The second objectiv was to connect Biomercator tool to this new module with the idea to generate and to submit automatically metaqtl analysis results to GnpIS and also to be able to export automatically existing GnpIS QTLs maps to BioMercator tools.

Results achieved : 

  • Since 2012: a new version of GnpIS-GnpMap database module for dealing QTLs and MetaQTLs experiments: ( to manage MetaQTL analysis : a database schema and a query interface to query MetaQTLs.
  • A data submission format file (in excel) to submit data this database (, See: Mapping excel file.
  • An exchange format file (in XML) to export automatically data from GnpIS to BioMercator tool
  • Since october 2011: a new version of Biomercator (V3 and V4)
  • A paper for Biomercator V3: O. Sosnowski & al.
  • A presentation of BioMercator V4 made at Plant and Animal Genome conference in 2011
  • A poster presented at the ANR Plant genomics Meeting in April 2012
  • A poster presented at the next Bioinformatics french conference JOBIM in Rennes in July 2012: 
  • Integration of experiments results coming from the meta-analysis of QTLs (meta-QTLs) in the URGI information system GnpIS: Dorothée Valdenaire, Erik Kimmel, Olivier Sosnowsky, Johann Joets, Hadi Quesneville and Delphine Steinbach

Project Status:

  • Work on this project is now closed. 
  • Work was published in D. Steinbach et al. Database 2013 (see complete reference below)
  • Tools are ready to be used in various new projects such as currently Amaizing, Breedwheat.. and continued to be developped according to new user needs by URGI GnpIS information system team 

 For interest on GnpIS-MetaQTL : please contact: Delphine Steinbach at and Johann Joets at for information on Biomercator tool.



  • Goffinet B., Gerber S. Quantitative trait loci: a meta-analysis. Genetics. 2000 May;155(1):463
  • Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, JoetsJ. BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics. 2004 Sep 22;20(14):2324-6.
  • Veyrieras J.B., Goffinet B. and Charcosset A. MetaQTL: a package of new computational methods for the meat-analysis of QTL mapping experiments. BMC Bioinformatics 8(1):49, 2007.
  • Delphine Steinbach, Michael Alaux, Joelle Amselem, Nathalie Choisne, Sophie Durand, Raphael Flores, Aminah-Olivia Keliet, Erik Kimmel, Nicolas Lapalu, Isabelle Luyten, Célia Michotey, Nacer Mohellibi, Cyril Pommier, Sébastien Reboux, Dorothée Valdenaire, Daphné Verdelet and Hadi Quesneville : GnpIS, an information system to integrate genetic and genomic data from plants and fungi : Database, Vol. 2013, Article ID bat058, doi:10.1093/database/bat058

Update: 16 Jan 2014
Creation date: 26 Apr 2010