Abstract
Genome-wide association studies (GWAS) allow to dissect complex traits and map genetic variants, which often explain relatively little of the heritability. One potential reason is the preponderance of undetected low-frequency variants. To increase their allele frequency and assess their phenotypic impact in a population, we generated a diallel panel of 3025 yeast hybrids, derived from pairwise crosses between natural isolates and examined a large number of traits. Parental versus hybrid regression analysis showed that while most phenotypic variance is explained by additivity, a third is governed by non-additive effects, with complete dominance having a key role. By performing GWAS on the diallel panel, we found that associated variants with low frequency in the initial population are overrepresented and explain a fraction of the phenotypic variance as well as an effect size similar to common variants. Overall, we highlighted the relevance of low-frequency variants on the phenotypic variation.
Highlights
Natural populations are characterized by an astonishing phenotypic diversity
Based on the genomic and phenotypic data from the 1,011 S. cerevisiae isolate collection (Peter et al, 2018), we selected a subset of 55 isolates that were diploid, homozygous, genetically diverse (Figure 1a), and originated from a broad range of ecological sources (Figure 1b) as well as geographical origins (Europe, America, Africa and Asia) (Figure 1c and Supplementary file 1)
All 3025 hybrids were viable, indicating no dominant lethal interactions existed between the parental isolates
Summary
Variation observed among individuals of the same species represents a powerful raw material to develop better insight into the relationship existing between genetic variants and complex traits (Mackay et al, 2009). Dissection of the genetic mechanisms underlying natural phenotypic diversity is within easy reach when using classical mapping approaches such as linkage analysis and genome-wide association studies (GWAS) (Mackay et al, 2009; Visscher et al, 2017). Alongside these major advances, it must be noted that there are some limitations. All genotype-phenotype correlation studies in humans and other model eukaryotes have identified causal loci in GWAS explaining relatively little of the observed phenotypic variance of most complex traits (Eichler et al, 2010; Hindorff et al, 2009; Manolio et al, 2009; Shi et al, 2016; Stahl et al, 2012; Wood et al, 2014; Zuk et al, 2014)
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