Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.
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Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect
The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human‐altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments.
- PAR ID:
- 10488343
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Evolutionary Applications
- Volume:
- 17
- Issue:
- 1
- ISSN:
- 1752-4571
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Atlantic killifish (
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null (Ed.)Characterizing the genetic complexity of adaptation and trait evolution is a major emphasis of evolutionary biology and genetics. Incongruent findings from genetic studies have resulted in conceptual models ranging from a few large-effect loci to massively polygenic architectures. Here, we combine chromatin immunoprecipitation sequencing, Hi-C, RNA sequencing, and 40 whole-genome sequences from Heliconius butterflies to show that red color pattern diversification occurred via many genomic loci. We find that the red wing pattern master regulatory transcription factor Optix binds dozens of loci also under selection, which frequently form three-dimensional adaptive hubs with selection acting on multiple physically interacting genes. Many Optix-bound genes under selection are tied to pigmentation and wing development, and these loci collectively maintain separation between adaptive red color pattern phenotypes in natural populations. We propose a model of trait evolution where functional connections between loci may resolve much of the disparity between large-effect and polygenic evolutionary models.more » « less
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Abstract Recent studies have shown that the repeated evolution of similar phenotypes in response to similar ecological conditions (here “parallel evolution”) often occurs through mutations in the same genes. However, many previous studies have focused on known candidate genes in a limited number of systems. Thus, the question of how often parallel phenotypic evolution is due to parallel genetic changes remains open. Here, we used quantitative trait locus (QTL) mapping in F2 intercrosses between lake and stream threespine stickleback (Gasterosteus aculeatus) from four independent watersheds on Vancouver Island, Canada to determine whether the same QTL underlie divergence in the same phenotypes across, between, and within watersheds. We find few parallel QTL, even in independent crosses from the same watershed or for phenotypes that have diverged in parallel. These findings suggest that different mutations can lead to similar phenotypes. The low genetic repeatability observed in these lake-stream systems contrasts with the higher genetic repeatability observed in other stickleback systems. We speculate that differences in evolutionary history, gene flow, and/or the strength and direction of selection might explain these differences in genetic parallelism and emphasize that more work is needed to move beyond documenting genetic parallelism to identifying the underlying causes.
