Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multitrait GWA studies. Issue 4 (25th September 2021)

• Record Type: Journal Article
• Authors: Chebib, Jobran; Guillaume, Frédéric
• Editors: Barton, N
• Is Part Of: Genetics. Volume 219:Issue 4(2021)
• Publication Date: 2021-09-25
• Subjects: genetic architecture -- correlational selection -- multivariate -- forward-time simulation -- SNP -- spurious pleiotropy -- trait mapping; Genetics -- Periodicals; 576.5
• DOI: 10.1093/genetics/iyab159
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: Genetic correlations between traits may cause correlated responses to selection. Previous models described the conditions under which genetic correlations are expected to be maintained. Selection, mutation, and migration are all proposed to affect genetic correlations, regardless of whether the underlying genetic architecture consists of pleiotropic or tightly linked loci affecting the traits. Here, we investigate the conditions under which pleiotropy and linkage have different effects on the genetic correlations between traits by explicitly modeling multiple genetic architectures to look at the effects of selection strength, degree of correlational selection, mutation rate, mutational variance, recombination rate, and migration rate. We show that at mutation-selection(-migration) balance, mutation rates differentially affect the equilibrium levels of genetic correlation when architectures are composed of pairs of physically linked loci compared to architectures of pleiotropic loci. Even when there is perfect linkage (no recombination within pairs of linked loci), a lower genetic correlation is maintained than with pleiotropy, with a lower mutation rate leading to a larger decrease. These results imply that the detection of causal loci in multitrait association studies will be affected by the type of underlying architectures, whereby pleiotropic variants are more likely to be underlying multiple detected associations. We also confirm that tighter linkage between nonpleiotropic causal loci maintains higher genetic correlations at the traits and leads to a greater proportion of false positives in association analyses.