Evidence map›Paper›PMID 40565150›Full record

ArticleInternational journal of molecular sciences2025

Genomic Prediction and Heritability Estimation for Daughter Pregnancy Rate in U.S. Holstein Cows Using SNP, Epistasis and Haplotype Effects.

Ruifei Yang, Dzianis Prakapenka, Zuoxiang Liang, Yang Da

Abstract read
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Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ruifei YangDepartment of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.
Dzianis PrakapenkaDepartment of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.ORCID 0000-0002-4592-7120
Zuoxiang LiangDepartment of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.ORCID 0000-0002-9058-9327
Yang DaDepartment of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.

Funding

NIH HHS 1R01HG012425-22USDA/NIFA 2020-67015-31133
6 · The paper itself

Abstract

The contributions of additive, dominance, haplotype, and epistasis effects up to the third order to the accuracy of predicting daughter pregnancy rate (DPR) phenotypic values and to the phenotypic variance in U.S. Holstein cows were investigated using five samples with 25,827-133,934 cows and 74,855-75,209 SNPs. Heritability estimates showed that only additive × additive (A × A) epistasis effects had nonzero heritability and all other second- and third-order epistasis effects had zero heritability, and hence A × A was the only epistasis effects included in the prediction models. Based on the results of the largest sample with 133,934 cows, genomic heritability estimate was 0.044-0.054 for additive heritability, 0.005 for dominance heritability, 0.011-0.022 for haplotype heritability, and 0.052-0.062 for A × A heritability. The combination of additive (A) and A × A effects was the best prediction model based on the prediction accuracy. This best model improved the prediction accuracy over the A-only model by 4.88%, and had total heritability of 0.099 as the summation of the additive and A × A heritability estimates. Dominance and haplotype effects had minor contributions (0.97-2.44%) to prediction accuracy in models without A × A effects but had no contribution to prediction accuracy when A × A was in the prediction model. The partition of A × A effects into inter- and intra-chromosome A × A effects showed that inter-chromosome A × A were mainly responsible for the A × A contributions to prediction accuracy and phenotypic variance. Sample size had a major impact on prediction accuracy and the sample of 90,000 cows or 81,000 cows per training population had peak prediction accuracies that were 32.70-35.85% higher than in the sample with 25,827 cows. The largest sample with 133,934 cows had the smallest variations in prediction accuracy and slightly lower average prediction accuracy than in the sample with 90,000 cows.

Indexed as

Epistasis, GeneticHaplotypesPolymorphism, Single NucleotidePregnancy RateAnimalsCattleFemaleGenomicsModels, GeneticPhenotypePregnancyQuantitative Trait, HeritableUnited Statesdaughter pregnancy rateepistasisgenomic predictionhaplotypeHolstein cowsprediction accuracySNP

Identifiers

PMID40565150
PMCPMC12192797

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.