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This article is part of the supplement: Proceedings of the 12th European workshop on QTL mapping and marker assisted selection

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A strategy for QTL fine-mapping using a dense SNP map

Joaquim Tarres1*, François Guillaume12 and Sébastien Fritz3

Author Affiliations

1 UR337 Station de Génétique Quantitative et Appliquée, INRA, Jouy-en-Josas F-78350, France

2 Institut de l'élevage, Paris F-75595, France

3 Union Nationale des Coopératives agricoles d'Elevage et d'Insémination Animale, Paris F-75595, France

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BMC Proceedings 2009, 3(Suppl 1):S3  doi:10.1186/1753-6561-3-S1-S3

Published: 23 February 2009



Dense marker maps require efficient statistical methods for QTL fine mapping that work fast and efficiently with a large number of markers. In this study, the simulated dataset for the XIIth QTLMAS workshop was analyzed using a QTL fine mapping set of tools.


The QTL fine-mapping strategy was based on the use of statistical methods combining linkage and linkage disequilibrium analysis. Variance component based linkage analysis provided confidence intervals for the QTL. Within these regions, two additional analyses combining both linkage analysis and linkage disequilibrium information were applied. The first method estimated identity-by-descent probabilities among base haplotypes that were used to group them in different clusters. The second method constructed haplotype groups based on identity-by-state probabilities.


Two QTL explaining 9.4 and 3.3% of the genetic variance were found with high significance on chromosome 1 at positions 19.5 and 76.6 cM. On chromosome 2, two QTL were also detected at positions 26.0 and 53.2 explaining respectively 9.0 and 7.8 of total genetic variance. The QTL detected on chromosome 3 at position 11.9 cM (5% of variance) was less important. The QTL with the highest effect (37% of variance) was detected on chromosome 4 at position 3.1 cM and another QTL (13.6% of variance) was detected on chromosome 5 at position 93.9 cM.


The proposed strategy for fine-mapping of QTL combining linkage and linkage disequilibrium analysis allowed detecting the most important QTL with an additive effect in a short period but it should be extended in the future in order to fine-map linked and epistatic QTL.