Unknown parent groups and truncated pedigree in single-step genomic evaluations of Murrah buffaloes

Abstract

ABSTRACT: Missing pedigrees may produce bias in genomic evaluations. Thus, strategies to deal with this problem have been proposed as using unknown parent groups (UPG) or truncated pedigrees. The aim of this study was to investigate the impact of modeling missing pedigrees under single-step genomic best linear unbiased prediction (ssGBLUP) evaluations for productive and reproductive traits in dairy buffalo using different approaches: (1) traditional BLUP without UPG (BLUP), (2) traditional BLUP including UPG (BLUP/UPG), (3) ssGBLUP without UPG (ssGBLUP), (4) ssGBLUP including UPG in the A and A22 matrices (ssGBLUP/A_UPG), (5) ssGBLUP including UPG in all elements of the H matrix (ssGBLUP/H_UPG), (6) BLUP with pedigree truncation for the last 3 generations (BLUP/truncated), and (7) ssGBLUP with pedigree truncation for the last 3 generations (ssGBLUP/truncated). Unknown parent groups were not used in the scenarios with truncated pedigree. A total of 3,717, 4,126, and 3,823 records of the first lactation for accumulated 305-d milk yield (MY), age at first calving (AFC), and lactation length (LL), respectively, were used. Accuracies ranged from 0.27 for LL (BLUP) to 0.46 for MY (BLUP), bias ranged from −0.62 for MY (ssGBLUP) to 0.0002 for AFC (BLUP/truncated), and dispersion ranged from 0.88 for MY (BLUP/A_UPG) to 1.13 for LL (BLUP). Genetic trend showed genetic gains for all traits across 20 years of selection, and the impact of including genomic information, UPG, or pedigree truncation under GEBV accuracies ranged among the evaluated traits. Overall, methods using UPG, truncation pedigree, and genomic information exhibited potential to improve GEBV accuracies, bias, and dispersion for all traits compared with other methods. Truncated scenarios promoted high genetic gains. In small populations with few genotyped animals, combining truncated pedigree or UPG with genomic information is a feasible approach to deal with missing pedigrees.

Keywords

• accuracy
• age at first calving
• bias
• lactation length
• milk yield