tailieunhanh - Báo cáo sinh học: " Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học thế giới đề tài: Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data | Genet. Sel. Evol. 36 2004 261-279 INRA EDP Sciences 2004 DOI gse 2004001 261 Original article Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data Theo . MEUwissENa Mike E. GoDDARDb a Centre for Integrative Genetics Cigene Institute of Animal Science Agricultural University of Norway Box 5025 As Norway b Institute of Land and Food Resources University of Melbourne and Victorian Institute of Animal Science Attwood Australia Received 17 February 2003 accepted 10 November 2003 Abstract - A multi-locus QTL mapping method is presented which combines linkage and linkage disequilibrium LD information and uses multitrait data. The method assumed a putative QTL at the midpoint of each marker bracket. Whether the putative QTL had an effect or not was sampled using Markov chain Monte Carlo MCMC methods. The method was tested in dairy cattle data on chromosome 14 where the DGAT1 gene was known to be segregating. The DGAT1 gene was mapped to a region of cM and the effects of the gene were accurately estimated. The fitting of multiple QTL gave a much sharper indication of the QTL position than a single QTL model using multitrait data probably because the multi-locus QTL mapping reduced the carry over effect of the large DGAT1 gene to adjacent putative QTL positions. This suggests that the method could detect secondary QTL that would in single point analyses remain hidden under the broad peak of the dominant QTL. However no indications for a second QTL affecting dairy traits were found on chromosome 14. QTL mapping linkage analysis linkage disequilibrium mapping multitrait analysis multi-locus mapping 1. INTRODUCTION Quantitative trait loci QTL mapping methods that fit a single QTL to the data can be biased by the presence of other QTL especially if they are close to the putative QTL position. In extreme situations two linked QTL can cancel each others effects and none of the QTL is detected. In other situations a