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Inbreeding in genome‐wide selection
Author(s) -
Daetwyler H.D.,
Villanueva B.,
Bijma P.,
Woolliams J.A.
Publication year - 2007
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/j.1439-0388.2007.00693.x
Subject(s) - best linear unbiased prediction , selection (genetic algorithm) , inbreeding , genetic gain , biology , genome , statistics , genetics , genetic variation , mathematics , population , computer science , gene , machine learning , demography , sociology
Summary Traditional selection methods, such as sib and best linear unbiased prediction (BLUP) selection, which increased genetic gain by increasing accuracy of evaluation have also led to an increased rate of inbreeding per generation (Δ F G ). This is not necessarily the case with genome‐wide selection, which also increases genetic gain by increasing accuracy. This paper explains why genome‐wide selection reduces Δ F G when compared with sib and BLUP selection. Genome‐wide selection achieves high accuracies of estimated breeding values through better prediction of the Mendelian sampling term component of breeding values. This increases differentiation between sibs and reduces coselection of sibs and Δ F G . The high accuracy of genome‐wide selection is expected to reduce the between family variance and reweigh the emphasis of estimated breeding values of individuals towards the Mendelian sampling term. Moreover, estimation induced intraclass correlations of sibs are expected to be lower in genome‐wide selection leading to a further decrease of coselection of sibs when compared with BLUP. Genome‐wide prediction of breeding values, therefore, enables increased genetic gain while at the same time reducing Δ F G when compared with sib and BLUP selection.