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Impact of epistasis effects on the accuracy of predicting phenotypic values of residual feed intake in U. S Holstein cows

Authors :
Zuoxiang Liang
Dzianis Prakapenka
Kristen L. Parker Gaddis
Michael J. VandeHaar
Kent A. Weigel
Robert J. Tempelman
James E. Koltes
José Eduardo P. Santos
Heather M. White
Francisco Peñagaricano
Ransom L. Baldwin VI
Yang Da
Source :
Frontiers in Genetics, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

The impact of genomic epistasis effects on the accuracy of predicting the phenotypic values of residual feed intake (RFI) in U.S. Holstein cows was evaluated using 6215 Holstein cows and 78,964 SNPs. Two SNP models and seven epistasis models were initially evaluated. Heritability estimates and the accuracy of predicting the RFI phenotypic values from 10-fold cross-validation studies identified the model with SNP additive effects and additive × additive (A×A) epistasis effects (A + A×A model) to be the best prediction model. Under the A + A×A model, additive heritability was 0.141, and A×A heritability was 0.263 that consisted of 0.260 inter-chromosome A×A heritability and 0.003 intra-chromosome A×A heritability, showing that inter-chromosome A×A effects were responsible for the accuracy increases due to A×A. Under the SNP additive model (A-only model), the additive heritability was 0.171. In the 10 validation populations, the average accuracy for predicting the RFI phenotypic values was 0.246 (with range 0.197–0.333) under A + A×A model and was 0.231 (with range of 0.188–0.319) under the A-only model. The average increase in the accuracy of predicting the RFI phenotypic values by the A + A×A model over the A-only model was 6.49% (with range of 3.02–14.29%). Results in this study showed A×A epistasis effects had a positive impact on the accuracy of predicting the RFI phenotypic values when combined with additive effects in the prediction model.

Details

Language :
English
ISSN :
16648021
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.8c1acb4721d9415995ab89b3ea3e2ef7
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2022.1017490