Robust GMACE for young bulls - methodology

Abstract

Methods presented previously to combine GEBV of young bulls and MACE solutions of ancestors were reviewed.  Variances required for GMACE could be assumed equal to the variances in regular MACE, or estimated from GMACE input data.  Equations to estimate "genomic" variance were partitioned to explain extreme estimates that have been observed.  Variance estimation was subsequently improved and constraints were applied to avoid extreme variances in GMACE applications.  Subtracting the average difference between national GEBV and MACE parent average forced a null average for Mendelian Sampling estimates and removed inconsistencies among population scales.  This adjustment reduced or eliminated the majority of extreme genomic variance estimates.  The small number of remaining extremes were for traits with unusually low reliabilities of national GEBV.  Nearly all other estimates of genetic standard deviation (SD) were within the range 0.80-1.20 times the SD used for MACE.  Estimates outside this range were truncated to the edges of the range.  RMSE of local GEBV predictions, based on GMACE of data that included GEBV from only foreign countries, were reduced by these constraints on genomic variance estimates.  The use of robust variance estimates also reduced the bias of top young bull predictions, especially for traits with the largest biases.  Relative to the use of MACE variances, GMACE with robust genomic variances gave a slightly higher but similarly low maximum bias for SCS (20% versus 18%) and for all other traits the maximum bias was reduced, from 22% to 10% for protein yield, from 46% to 16% for stature, from 61% to 44% for longevity, and from 28% to 27% for fertility.