TAILIEUCHUNG - Báo cáo sinh học: "Joint QTL analysis of three connected F2-crosses in pigs"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học quốc tế đề tài: Joint QTL analysis of three connected F2-crosses in pigs | Ruckert and Bennewitz Genetics Selection Evolution 2010 42 40 http content 42 1 40 GSE Ge n et i cs Selection Evolution RESEARCH Open Access Joint QTL analysis of three connected F2-crosses in pigs Christine Ruckert Jorn Bennewitz Abstract Background Numerous QTL mapping resource populations are available in livestock species. Usually they are analysed separately although the same founder breeds are often used. The aim of the present study was to show the strength of analysing F2-crosses jointly in pig breeding when the founder breeds of several F2-crosses are the same. Methods Three porcine F2-crosses were generated from three founder breeds . Meishan Pietrain and wild boar . The crosses were analysed jointly using a flexible genetic model that estimated an additive QTL effect for each founder breed allele and a dominant QTL effect for each combination of alleles derived from different founder breeds. The following traits were analysed daily gain back fat and carcass weight. Substantial phenotypic variation was observed within and between crosses. Multiple QTL multiple QTL alleles and imprinting effects were considered. The results were compared to those obtained when each cross was analysed separately. Results For daily gain back fat and carcass weight 13 15 and 16 QTL were found respectively. For back fat daily gain and carcass weight respectively three four and five loci showed significant imprinting effects. The number of QTL mapped was much higher than when each design was analysed individually. Additionally the test statistic plot along the chromosomes was much sharper leading to smaller QTL confidence intervals. In many cases three QTL alleles were observed. Conclusions The present study showed the strength of analysing three connected F2-crosses jointly. In this experiment statistical power was high because of the reduced number of estimated parameters and the large number of individuals. The applied model was flexible and was .

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