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Contribution of Functional Genomics to the Fine Mapping of QTL

Inra Prod.Anim., 23 (4), 343-358

G. LE MIGNON ¹,²,³, Y. BLUM ¹,²,⁴, O. DEMEURE ¹,², C. DIOT ¹,², E. LE BIHAN-DUVAL ⁵, P. LE ROY ¹,², S. LAGARRIGUE ¹,²

1 INRA, UMR598 Génétique Animale, F-35000 Rennes, France

2 Agrocampus Ouest, UMR598 Génétique Animale, F-35000 Rennes, France

3 ITAVI, 28 rue du Rocher, F-75008 Paris, France

4 Agrocampus Ouest, Laboratoire de Mathématiques Appliquées, F-35000 Rennes, France

5 INRA, UR83 Recherches Avicoles, F-37380 Nouzilly, France

Much progress has been made in recent years in the genomics field. The development of technologies -based on miniaturized arrays makes it possible to explore genomes at both structural and functional levels. DNA microarrays allow to genotype several thousands of SNP in a genome, or measure the expression level of several thousands of genes in a tissue. Strategies combining genotypic information with elementary phenotypes (mRNA, proteins or metabolites) open new perspectives in biology research and are grouped under the new concept of « genetical genomics ». We will focus here on the contributions of the « genetical genomics » in the context of QTL detection. Firstly, after defining the concept of expression QTL (eQTL), this article reports the main results on expression QTL mapping reported in the literature. Then, the different methods using expression data to refine or functionally characterize a QTL region are presented and illustrated through some examples on model and livestock species.

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