Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51480
Title: The Impact of Non-additive Effects on the Genetic Correlation Between Populations
Contributor(s): Duenk, Pascal  (author); Bijma, Piter (author); Calus, Mario P L (author); Wientjes, Yvonne C J (author); van der Werf, Julius H J  (author)orcid 
Publication Date: 2020-02-01
Open Access: Yes
DOI: 10.1534/g3.119.400663
Handle Link: https://hdl.handle.net/1959.11/51480
Abstract: Average effects of alleles can show considerable differences between populations. The magnitude of these differences can be measured by the additive genetic correlation between populations (rg). This rg can be lower than one due to the presence of non-additive genetic effects together with differences in allele frequencies between populations. However, the relationship between the nature of non-additive effects, differences in allele frequencies, and the value of rg remains unclear, and was therefore the focus of this study. We simulated genotype data of two populations that have diverged under drift only, or under drift and selection, and we simulated traits where the genetic model and magnitude of non-additive effects were varied. Results showed that larger differences in allele frequencies and larger non-additive effects resulted in lower values of rg. In addition, we found that with epistasis, rg decreases with an increase of the number of interactions per locus. For both dominance and epistasis, we found that, when non-additive effects became extremely large, rg had a lower bound that was determined by the type of inter-allelic interaction, and the difference in allele frequencies between populations. Given that dominance variance is usually small, our results show that it is unlikely that true rg values lower than 0.80 are due to dominance effects alone. With realistic levels of epistasis, rg dropped as low as 0.45. These results may contribute to the understanding of differences in genetic expression of complex traits between populations, and may help in explaining the inefficiency of genomic trait prediction across populations.
Publication Type: Journal Article
Source of Publication: G3: Genes, Genomes, Genetics, 10(2), p. 783-795
Publisher: Oxford University Press
Place of Publication: United States of America
ISSN: 2160-1836
Fields of Research (FoR) 2020: 310207 Statistical and quantitative genetics
Socio-Economic Objective (SEO) 2020: 100402 Dairy cattle
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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