tailieunhanh - Báo cáo sinh học: " Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học quốc tế đề tài: Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction | Liu et al. Genetics Selection Evolution 2011 43 19 http content 43 1 19 GSE Ge n et i cs Selection Evolution RESEARCH Open Access Impacts of both reference population size and inclusion of a residual polygenic effect on the accuracy of genomic prediction 1 1 1 2 1 Zengting Liu Franz R Seefried Friedrich Reinhardt Stephan Rensing Georg Thaller and Reinhard Reents Abstract Background The purpose of this work was to study the impact of both the size of genomic reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic evaluations enhanced with genomic information. Methods Direct genomic values were estimated for German Holstein cattle with a genomic BLUP model including a residual polygenic effect. A total of 17 429 genotyped Holstein bulls were evaluated using the phenotypes of 44 traits. The Interbull genomic validation test was implemented to investigate how the inclusion of a residual polygenic effect impacted genomic estimated breeding values. Results As the number of reference bulls increased both the variance of the estimates of single nucleotide polymorphism effects and the reliability of the direct genomic values of selection candidates increased. Fitting a residual polygenic effect in the model resulted in less biased genome-enhanced breeding values and decreased the correlation between direct genomic values and estimated breeding values of sires in the reference population. Conclusions Genetic evaluation of dairy cattle enhanced with genomic information is highly effective in increasing reliability as well as using large genomic reference populations. We found that fitting a residual polygenic effect reduced the bias in genome-enhanced breeding values decreased the correlation between direct genomic values and sire s estimated breeding values and made genome-enhanced breeding values more consistent in mean and variance as is the case for pedigree-based estimated breeding values. Background With .