Impact and utility of shallow pedigree using single-step genomic BLUP for prediction of unbiased genomic breeding values

In unstructured dairy programs, pedigree is usually shallow, which leads to biased prediction of breeding values using best linear unbiased prediction (BLUP). The objective of this study was to come out with a genomic prediction strategy that can utilize shallow pedigree information and predict unbiased and more accurate GEBV for sex-limited traits in a small population using single-step GBLUP (ssGBLUP). The data and models for a population under selection were simulated. Out of current 10 generations, 10th generation with 1000 candidates served as validation population. For the complete pedigree scenario, pedigree (P)BLUP estimated breeding values (EBV) were unbiased with accuracy (r) of 0.35 ± 0.02 and 0.26 ± 0.01 for 0.3 and 0.1 h² scenario, respectively. For the shallow pedigree, biased prediction of breeding values and low accuracies were obtained with linear decline in the accuracy of EBV for removal of information on more distant pedigree. Accuracy and bias (ρ) for scenario with removing 4 distant generations from pedigree were 0.30 ± 0.02 and 0.55 ± 0.03, respectively, in moderate h² scenario. Use of Genomic (G)BLUP, especially with "extreme phenotypic contrast selective genotyping," (TB) resulted in higher accuracy for a small reference of females; however, GEBV were highly biased. We observed that ssGBLUPF, where the numerator relationship matrix is corrected for inbreeding, resulted in more accurate and unbiased estimates of GEBV across shallow pedigree scenario, with TB all female reference (missing 4 distant generations: r = 0.50 ± 0.02; ρ = 0.96 ± 0.02). We recommend use of ssGBLUPF with two tailed selectively genotyped all female reference in shallow pedigree scenarios, to obtain unbiased and accurate GEBV for sex-limited traits, when resources are limited.