Pleiotropy or linkage? Their relative contributions to the genetic correlation of quantitative traits and detection by multitrait GWA studies

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 multi-trait 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 non-pleiotropic causal loci maintains higher genetic correlations at the traits and leads to a greater proportion of false positives in association analyses.

Genome-wide association studies reveal putative QTLs for physiological traits under contrasting phosphorous conditions in wheat (Triticum aestivum L.)

“…Five QTLs in NLP, three QTLs in LP, and one in both treatments were detected for multiple traits. The loci affecting multiple traits should be a potential marker for marker-assisted selection for varietal improvement (Chebib and Guillaume, 2021).…”

Unraveling coevolutionary dynamics using ecological genomics

“…Furthermore, GEAS studies can identify genes and alleles of importance in GxGxE interactions, while taking as co-variables environmental data (e.g., climate) across habitats [59]. However, in all association studies, distinguishing the effects of mutations that are directly responsible for the phenotype from correlated mutations (i.e., from linkage disequilibrium) remains an issue [60]. We argue that systematic investigation of GxGxE will prove crucial for deciphering the genetic architecture of trade-offs across habitats, and for predicting the coevolutionary trajectories of interacting species across heterogeneous landscapes (Box 3, Figure 2).…”

A pleiotropic chemoreceptor facilitates the functional coupling of pheromone production and perception

“…Previously published theoretical models have postulated that the maintenance of robust coupling between the production and perception of mating signals is driven by strong genetic linkage between the cellular and physiological processes that regulate mating-signal production and its perception, or alternatively, via the action of pleiotropic genes that control both processes (Boake, 1991; Butlin and Ritchie, 1989; Butlin and Trickett, 1997; Shaw et al ., 2011; Shaw and Lesnick, 2009). Consequently, both mechanisms provide plausible explanations for how mating-signaling systems could remain stable and reliable at the population level while still retaining their capacity for future diversification, as necessitated for speciation (Chebib and Guillaume, 2021; Hoy et al ., 1977; Kirkpatrick and Hall, 2004; Lande, 1980; Shaw et al ., 2011; Shaw and Lesnick, 2009; Wiley et al, 2012).…”

“…Empirical data in support of the contribution of gene-linkage or pleiotropy to the maintenance of coupling between mating signal production and perception at the population level are rare (Chebib and Guillaume, 2021; Hoy et al ., 1977; Shaw et al ., 2011; Shaw and Lesnick, 2009; Wiley et al ., 2012). Additionally, the complex characteristics of mating behaviors, and the species-specific signals that drive them, present a major barrier for identifying the actual molecular mechanisms and candidate pleiotropic genes that support the coupling between the production and perception of specific mating signals (Chenoweth and Blows, 2006; Singh and Shaw, 2012).…”