Milk performance traits are likely influenced by both additive and non-additive (e.g. dominance) genetic effects. Genetic variation can be partitioned using genomic information. The objective of this study was to estimate genetic variance components of production and milk component traits (e.g. acetone, fatty acids), which are particularly important for milk processing or which can provide information on the health status of cows. A genomic relationship approach was applied to phenotypic and genetic information of 1295 Holstein cows for estimating additive genetic and dominance variance components. Most of the 17 investigated traits were mainly affected by additive genetic effects, but protein content and casein content also showed a significant contribution of dominance. The ratio of dominance to additive variance was estimated as 0.64 for protein content and 0.56 for casein content. This ratio was highest for SCS (1.36) although dominance was not significant. Dominance effects were negligible in other moderately heritable milk traits.
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http://dx.doi.org/10.1111/jbg.12103 | DOI Listing |
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Department of Clinical and School Psychology, Nova Southeastern University.
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January 2025
Laboratory of Mathematics and Complex Systems, Ministry of Education, School of Mathematical Sciences, Beijing Normal University, Beijing, People's Republic of China.
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