Estimation & Prediction

Use of Haplotypes for Genomic Prediction in Holstein Cattle from Mexico

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Abstract

The objective of this study was to evaluate and compare the reliability of genomic breeding value (GBV) predictions for six traits in Holstein cattle: milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FP), protein percentage (PP), and somatic cell score (SCS, on a linear scale from 0 to 9), using two different genomic data sources: (a) SNP-Analysis, based on all available single nucleotide polymorphisms (SNPs), and (b) HAP-Analysis, based on haplotypes encoded as pseudo-SNPs derived from linkage disequilibrium (LD) structure. The SNP-analysis dataset included 88,911 SNPs from 8,290 animals, whereas the HAP-analysis dataset contained 35,552 pseudo-SNPs from 8,331 animals. In both datasets, genomic quality control excluded animals with a call rate < 0.95 or with parent-progeny conflicts. SNPs and haplotypes were filtered based on minor allele frequency (MAF) < 0.05, call rate < 0.95, Hardy-Weinberg equilibrium p-value < 0.15, or monomorphism. The analysis included 640,746 records of MY from first to third lactations, adjusted to 305-day mature-equivalent yields, from 358,857 Holstein cows across 353 herds in 18 Mexican states. The pedigree file comprised 470,695 animals, with an average depth of five generations. GBV were estimated using the single-step genomic BLUP method (ssGBLUP) implemented in BLUPF90 software for each trait and dataset. The model included fixed effects of the overall mean, herd-year-season, and age at calving (in months, classified from 1 to 9), and random effects of permanent environment, sire interaction, animal, and residual. The reliability was estimated as; 1 - (Prediction Error Variance of the GBVi / σ2 (1+Fi)), where σ2 is the additive genetic variance and Fi is the inbreeding coefficient of the i-th animal. A total of 11,788 haplotypes were identified, with an average of 3.48 ± 2.44 SNPs per haplotype (ranging from 2 to 59) and an average physical length of 41.06 kb (0.003-199 kb). The average reliability of GBV increased by up to 0.02 points in the HAP-Analysis compared with SNP-Analysis for FY, PY (from 0.69 ± 0.001 to 0.71 ± 0.001), and SCS (from 0.61 ± 0.001 to 0.63 ± 0.001). For MY, reliability increased from 0.62 ± 0.001 to 0.63 ± 0.001, for FP from 0.82 ± 0.001 to 0.83 ± 0.001 and for PP from 0.83 ± 0.001 to 0.84 ± 0.001 in SNP-Analysis and HAP-Analysis, respectively. Although reliability estimates differed significantly between the two approaches (p < 0.0001), these differences may have limited practical impact in genetic improvement programs. The modest improvement associated with HAP-Analysis is likely due to higher LD within haplotypes, which may better capture the underlying genetic architecture of the traits.

Keywords: 2026

How to Cite:

Cortes, J., Garcia-Ruiz, A., Montaldo Valdenegro, H., Peà±agaricano, F. & Ruiz-López, F., (2026) “Use of Haplotypes for Genomic Prediction in Holstein Cattle from Mexico”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2287316. doi: https://doi.org/10.31274/wcgalp.24262

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