The Impact of Non-additive Effects on the Genetic Correlation Between Populations. Issue 2 (1st February 2020)

• Record Type: Journal Article
• Authors: Duenk, Pascal; Bijma, Piter; Calus, Mario P L; Wientjes, Yvonne C J; van der Werf, Julius H J
• Is Part Of: G3. Volume 10:Issue 2(2020)
• Page Start: 783
• Page End: 795
• Publication Date: 2020-02-01
• Subjects: dominance -- epistasis -- genomic prediction -- average effects -- population divergence; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.119.400663
• Languages: English
• ISSNs: 2160-1836

Abstract

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 (r g ). This r g 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 r g 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 r g . In addition, we found that with epistasis, r g 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, r g 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 r g values lower than 0.80 are due to dominance effects alone. With realistic levels of epistasis, r g 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.