Estimation & Prediction

Genomic prediction using prioritized SNP markers in closed inbred beef cattle populations

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Abstract

With advances in high-throughput technology, whole-genome sequences and dense SNP panels are efficiently being generated for use in Livestock improvement. However, the benefits of this information generated have not consistently translated into improved accuracy of genomic estimated breeding values (GEBV). Pre-selection of the most informative SNPs may help realize the value of richer genomic information. In this study, we evaluated two SNP prioritization strategies for genomic prediction of growth traits in two closed inbred beef cattle populations: Line 1 Hereford (n = 1,192) with an inbreeding level of 0.32 and a composite breed (50% Red Angus, 25% Charolais, 25% Tarentaise; n = 2,776) with an inbreeding level of 0.11. Marker prioritization approaches included fixation index (Fst) by selecting the top 10% of highly differentiated markers between older and recent generations. The second prioritization approach is based on GWAS-derived SNP effects. For Line1, birth weight and yearling weight prediction accuracies increased when including only a subset of prioritized SNP markers through Fst and GWAS based prioritization. The accuracy for birth weight including all SNP markers was 0.43, and including only a subset of prioritized SNP markers the accuracy increased to 0.48. For yearling weight, the accuracy using all SNP markers was 0.32, and using prioritized markers the accuracy increased to 0.35. Generally, prediction accuracy increased using prioritized SNP markers in the more inbred population (Line 1 Hereford) than in the less inbred population (composite breed). Results indicate that SNP prioritization can enhance GEBV accuracy by selecting informative markers, but gains are dependent on population structure, highlighting the influence of inbreeding on genomic prediction performance. To our knowledge, this is the first study to evaluate prioritization of SNP makers in closed highly inbred populations.

Keywords: 2026

How to Cite:

Hay, E., (2026) “Genomic prediction using prioritized SNP markers in closed inbred beef cattle populations”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2293499. doi: https://doi.org/10.31274/wcgalp.24314

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