Abstract
The current study was undertaken to explore the efficacy of genomic prediction using single-step genomic BLUP (ssGBLUP) with information on breed-of-origin of alleles at each marker of genotyped animals in Holstein x B. indicus crossbred (CBHF) cattle of India. Breed-of-origin was used in construction of breed-of-origin specific genomic relationship matrix (G-matrix). Performance of conventional ssGBLUP (Model-I) was compared to breed-of-origin aware genomic prediction (Model-II). Comparisons were by two schemes of five-fold cross-validation, 1: wherein half-sibs families’ (daughters’) performance records were left-out from the data sets (Data set - I & Data set - II (the latter with pedigree corrections)) and 2: wherein half-sibs families’ (daughters’) performance records of sires born of proven bulls, were left-out (Data set - III). For daughters, the criteria for comparison was the gain/ loss in correlations between corrected daughter yield (Yc) and their predicted breeding values (EBV) and for sires, the criteria for comparison was the gain/ loss in correlations between average Yc of daughters of sires and sire EBV, in Model-II compared to Model-I. Correlations for all daughters did not improve in Data sets - I and II, but improvement was noted in Data set - III. Correlations for non-genotyped daughters reduced in Data sets-I and II, but improved for Data set - III. Correlations across genotyped daughters improved consistently (around +5%) with all three data sets. Correlations across all sires did not improve in Data sets-I and II. Data sets - I and II included all data for validation schemes, so sires with fewer daughters were also included, which may be a cause of no gain being observed due to large uncertainty. However, gains were noted in all three data sets for genotyped sires (there were no non-genotyped sires in Data set - III), the biggest increase was in Data set - III (+15%). Predicted breeding values were less biased with Data set - III for validation in Model-II than in Model-I, while the reverse was the case for the other two data sets. Data set - III was consistent with practical scenarios wherein breeding values for young bulls from proven sires would be evaluated at regular intervals. Thus, using breed-of-origin specific G-matrix in genomic predictions by ssGBLUP improves the accuracy and unbiasedness of genomic estimated breeding values for CBHF genotyped animals, as compared to conventional G-matrix. This will improve genetic gains per unit of time in the Holstein x B. indicus crossbred population in India. Keywords: chromosome painting, breed of origin, ssGBLUP, HF crossbred, small holder
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Theory to Application 3, , 754, 2018
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