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Open Access Research article

Integrating genome annotation and QTL position to identify candidate genes for productivity, architecture and water-use efficiency in Populus spp

Romain Monclus2, Jean-Charles Leplé1, Catherine Bastien1, Pierre-François Bert16, Marc Villar1, Nicolas Marron45, Franck Brignolas23 and Véronique Jorge1*

Author Affiliations

1 INRA, UR0588 Amélioration Génétique et Physiologie Forestières (AGPF), F-45075, Orléans, France

2 UFR-Faculté des Sciences, UPRES EA 1207 Laboratoire de Biologie des Ligneux et des Grandes Cultures (LBLGC), Université d'Orléans, F-45067, Orléans, France

3 INRA, USC1328 Arbres et Réponses aux Contraintes Hydriques et Environnementales (ARCHE), F-45067, Orléans, France

4 INRA, UMR1137 Écologie et Écophysiologie Forestières (EEF), F-54280, Champenoux, France

5 Université de Lorraine, UMR 1137, Ecologie et Ecophysiologie Forestières (EEF), Faculté des Sciences, F-54500, Vandœuvre-lès-Nancy, France

6 Present address: INRA, UMR1287 Ecophysiologie et Génomique Fonctionnelle de la Vigne, F-33882, Villenave d'Ornon, France

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BMC Plant Biology 2012, 12:173  doi:10.1186/1471-2229-12-173

Published: 26 September 2012

Abstract

Background

Hybrid poplars species are candidates for biomass production but breeding efforts are needed to combine productivity and water use efficiency in improved cultivars. The understanding of the genetic architecture of growth in poplar by a Quantitative Trait Loci (QTL) approach can help us to elucidate the molecular basis of such integrative traits but identifying candidate genes underlying these QTLs remains difficult. Nevertheless, the increase of genomic information together with the accessibility to a reference genome sequence (Populus trichocarpa Nisqually-1) allow to bridge QTL information on genetic maps and physical location of candidate genes on the genome. The objective of the study is to identify QTLs controlling productivity, architecture and leaf traits in a P. deltoides x P. trichocarpa F1 progeny and to identify candidate genes underlying QTLs based on the anchoring of genetic maps on the genome and the gene ontology information linked to genome annotation. The strategy to explore genome annotation was to use Gene Ontology enrichment tools to test if some functional categories are statistically over-represented in QTL regions.

Results

Four leaf traits and 7 growth traits were measured on 330 F1 P. deltoides x P. trichocarpa progeny. A total of 77 QTLs controlling 11 traits were identified explaining from 1.8 to 17.2% of the variation of traits. For 58 QTLs, confidence intervals could be projected on the genome. An extended functional annotation was built based on data retrieved from the plant genome database Phytozome and from an inference of function using homology between Populus and the model plant Arabidopsis. Genes located within QTL confidence intervals were retrieved and enrichments in gene ontology (GO) terms were determined using different methods. Significant enrichments were found for all traits. Particularly relevant biological processes GO terms were identified for QTLs controlling number of sylleptic branches: intervals were enriched in GO terms of biological process like ‘ripening’ and ‘adventitious roots development’.

Conclusion

Beyond the simple identification of QTLs, this study is the first to use a global approach of GO terms enrichment analysis to fully explore gene function under QTLs confidence intervals in plants. This global approach may lead to identification of new candidate genes for traits of interest.