GxE

Genome-wide association analysis accounting for genotype by diet interaction for feed efficiency in Holstein cows

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Abstract

Feed efficiency (14.3 to 20.8 % DM), starch (20 to 33.6 % DM), and neutral detergent fiber (23.7 to 39.8 % DM). A total of 5,146 performance records on 3,243 cows were used for modeling GxD for CP and NDF, whereas 3,455 records on 2,449 cows had dietary information available for fat and starch. These records were based on 28 d intervals between 50 and 150 days in milk and derived from five research institutions across the US. All cows were genotyped with all analyses based on 66,589 SNP markers. Estimated overall heritabilities for DMI and RFI based on standard genomic models were 0.28 and 0.22, respectively. Random regression models up to cubic order were fitted to evaluate how additive genetic (G) and permanent environment (PE) variances changed across a continuum of dietary components. Model choice was based on likelihood-ratio tests and Akaike's information criteria. The best models were then used for random regression GWA analyses to uncover diet-sensitive genetic architecture of feed efficiency traits. The random regressions for DMI generally required higher order polynomials for optimal fits compared to RFI. Heritabilities for DMI ranged from 0.13 to 0.46, 0.16 to 0.30, 0.18 to 0.31, and 0.23 to 0.38 across fat, CP, starch, and NDF, respectively, while the respective ranges for RFI were 0.17 to 0.29, 0.10 to 0.34, 0.14 to 0.25, and 0.20 to 0.22. A SNP marker on chromosome 1 (BTA-53370-no-rs) was identified (Bonferroni adjusted P< 0.05) as influencing GxD across starch levels and three SNP markers on chromosome 20 (ARS-BFGL-NGS-109022, BovineHD2000001144, BovineHD2000001145) across NDF levels for DMI. There was generally no formal evidence of associations with any SNP marker based on a conventional GWA model. These results suggest that modeling GxD could facilitate potentially sharper GWA inferences in FE traits. Nevertheless, GxD appears to be primarily driven by a highly polygenic genomic architecture with individually small gene effects.

Keywords: 2026

How to Cite:

Ambike, V., Baldwin, R., Koltes, J., Parker Gaddis, K., Peà±agaricano, F., Santos, J., Tempelman, R., VandeHaar, M., Weigel, K. & White, H., (2026) “Genome-wide association analysis accounting for genotype by diet interaction for feed efficiency in Holstein cows”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2287181. doi: https://doi.org/10.31274/wcgalp.24228

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