University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Veterinary and Agricultural Sciences
  • Agriculture and Food Systems
  • Agriculture and Food Systems - Research Publications
  • View Item
  • Minerva Access
  • Veterinary and Agricultural Sciences
  • Agriculture and Food Systems
  • Agriculture and Food Systems - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Non-additive genetic variation in growth, carcass and fertility traits of beef cattle

    Thumbnail
    Download
    Published version (1.564Mb)

    Citations
    Scopus
    Altmetric
    25
    Author
    Bolormaa, S; Pryce, JE; Zhang, Y; Reverter, A; Barendse, W; Hayes, BJ; Goddard, ME
    Date
    2015-04-02
    Source Title
    Genetics Selection Evolution
    Publisher
    BMC
    University of Melbourne Author/s
    Goddard, Michael
    Affiliation
    Agriculture and Food Systems
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Bolormaa, S., Pryce, J. E., Zhang, Y., Reverter, A., Barendse, W., Hayes, B. J. & Goddard, M. E. (2015). Non-additive genetic variation in growth, carcass and fertility traits of beef cattle. GENETICS SELECTION EVOLUTION, 47 (1), https://doi.org/10.1186/s12711-015-0114-8.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/260184
    DOI
    10.1186/s12711-015-0114-8
    Abstract
    BACKGROUND: A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. METHODS: Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. RESULTS: The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance. CONCLUSIONS: Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [52443]
    • Agriculture and Food Systems - Research Publications [655]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors