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Does probabilistic modelling of linkage disequilibrium evolution improve the accuracy of QTL location in animal pedigree?

Christine Cierco-Ayrolles1*, Sébastien Dejean2, Andrés Legarra3, Hélène Gilbert4, Tom Druet5, Florence Ytournel6, Delphine Estivals1, Naïma Oumouhou1 and Brigitte Mangin1

Author Affiliations

1 INRA, UR 875 Unité de Biométrie et Intelligence Artificielle, F-31320 Castanet-Tolosan, France

2 Université Toulouse III, UMR 5219, F-31400 Toulouse, France

3 INRA, UR 631 Station d'Amélioration Génétique des Animaux, F-31320 Castanet-Tolosan, France

4 INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France

5 University of Liège (B43), Unit of Animal Genomics, Faculty of Veterinary Medicine and Centre for Biomedical Integrative Genoproteomics, Liège, Belgium

6 University of Göttingen, Faculty of Agricultural Sciences, Department of Animal Sciences, Georg-August University, Göttingen, Germany

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Genetics Selection Evolution 2010, 42:38  doi:10.1186/1297-9686-42-38

Published: 22 October 2010



Since 2001, the use of more and more dense maps has made researchers aware that combining linkage and linkage disequilibrium enhances the feasibility of fine-mapping genes of interest. So, various method types have been derived to include concepts of population genetics in the analyses. One major drawback of many of these methods is their computational cost, which is very significant when many markers are considered. Recent advances in technology, such as SNP genotyping, have made it possible to deal with huge amount of data. Thus the challenge that remains is to find accurate and efficient methods that are not too time consuming. The study reported here specifically focuses on the half-sib family animal design. Our objective was to determine whether modelling of linkage disequilibrium evolution improved the mapping accuracy of a quantitative trait locus of agricultural interest in these populations. We compared two methods of fine-mapping. The first one was an association analysis. In this method, we did not model linkage disequilibrium evolution. Therefore, the modelling of the evolution of linkage disequilibrium was a deterministic process; it was complete at time 0 and remained complete during the following generations. In the second method, the modelling of the evolution of population allele frequencies was derived from a Wright-Fisher model. We simulated a wide range of scenarios adapted to animal populations and compared these two methods for each scenario.


Our results indicated that the improvement produced by probabilistic modelling of linkage disequilibrium evolution was not significant. Both methods led to similar results concerning the location accuracy of quantitative trait loci which appeared to be mainly improved by using four flanking markers instead of two.


Therefore, in animal half-sib designs, modelling linkage disequilibrium evolution using a Wright-Fisher model does not significantly improve the accuracy of the QTL location when compared to a simpler method assuming complete and constant linkage between the QTL and the marker alleles. Finally, given the high marker density available nowadays, the simpler method should be preferred as it gives accurate results in a reasonable computing time.