Gabriela Mafra Fortuna , B.J. Zumbach , M. Johnsson , I. Pocrnic , G. Gorjanc
{"title":"Accounting for the nuclear and mito genome in dairy cattle breeding—A simulation study","authors":"Gabriela Mafra Fortuna , B.J. Zumbach , M. Johnsson , I. Pocrnic , G. Gorjanc","doi":"10.3168/jdsc.2023-0522","DOIUrl":null,"url":null,"abstract":"<div><div>Mitochondria play a significant role in numerous cellular processes through proteins encoded by both the nuclear genome (nDNA) and mito genome (mDNA), and increasing evidence shows that traits of interest might be affected by mito-nuclear interactions. Whereas the variation in nDNA is influenced by mutations and recombination of parental genomes, the variation in mDNA is solely driven by mutations. In addition, mDNA is inherited in a haploid form, from the dam. Cattle populations show substantial variation in mDNA between and within breeds. Past research suggests that variation in mDNA accounts for 1% to 5% of the phenotypic variation in dairy traits. Here we simulated a dairy cattle breeding program to assess the impact of accounting for mDNA variation in pedigree-based and genome-based genetic evaluations on the accuracy of EBVs for mDNA and nDNA components. We also examined the impact of alternative definitions of breeding values on genetic gain, including nDNA and mDNA components that both affect phenotype expression, but mDNA is inherited only maternally. We found that accounting for mDNA variation increased accuracy between +0.01 and +0.03 for different categories of animals, especially for young bulls (+0.03) and females without genotype data (between +0.01 and +0.03). Different scenarios of modeling and breeding value definition affected genetic gain. The standard approach of ignoring mDNA variation achieved competitive genetic gain. Modeling but not selecting on mDNA expectedly reduced genetic gain, whereas optimal use of mDNA variation recovered the genetic gain.</div></div>","PeriodicalId":94061,"journal":{"name":"JDS communications","volume":"5 6","pages":"Pages 572-576"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JDS communications","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666910224000796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mitochondria play a significant role in numerous cellular processes through proteins encoded by both the nuclear genome (nDNA) and mito genome (mDNA), and increasing evidence shows that traits of interest might be affected by mito-nuclear interactions. Whereas the variation in nDNA is influenced by mutations and recombination of parental genomes, the variation in mDNA is solely driven by mutations. In addition, mDNA is inherited in a haploid form, from the dam. Cattle populations show substantial variation in mDNA between and within breeds. Past research suggests that variation in mDNA accounts for 1% to 5% of the phenotypic variation in dairy traits. Here we simulated a dairy cattle breeding program to assess the impact of accounting for mDNA variation in pedigree-based and genome-based genetic evaluations on the accuracy of EBVs for mDNA and nDNA components. We also examined the impact of alternative definitions of breeding values on genetic gain, including nDNA and mDNA components that both affect phenotype expression, but mDNA is inherited only maternally. We found that accounting for mDNA variation increased accuracy between +0.01 and +0.03 for different categories of animals, especially for young bulls (+0.03) and females without genotype data (between +0.01 and +0.03). Different scenarios of modeling and breeding value definition affected genetic gain. The standard approach of ignoring mDNA variation achieved competitive genetic gain. Modeling but not selecting on mDNA expectedly reduced genetic gain, whereas optimal use of mDNA variation recovered the genetic gain.