Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast
- Harvard University, United States
- Massachusetts Institute of Technology, United States
- Dana-Farber Cancer Institute, United States
Abstract
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.
Data availability
Code used for this study is available at https://github.com/arturrc/bbqtl_inference. FASTQ files from high-throughput sequencing have been deposited in the NCBI BioProject database with accession number PRJNA767876. Inferred genotype and phenotype data is deposited in Dryad (doi: 10.5061/dryad.1rn8pk0vd).
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Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeastDryad Digital Repository, doi:10.5061/dryad.1rn8pk0vd.
Article and author information
Author details
Funding
Natural Sciences and Engineering Research Council of Canada (RGPIN-2021-02716)
- Alex N Nguyen Ba
National Science Foundation (#1764269)
- Katherine R Lawrence
National Institutes of Health (U54CA193461)
- Michael M Desai
National Science Foundation (PHY-1914916)
- Franziska Michor
National Institutes of Health (GM104239)
- Michael M Desai
Natural Sciences and Engineering Research Council of Canada (DGECR-2021-00117)
- Alex N Nguyen Ba
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Nguyen Ba et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast
eLife 11:e73983.
https://doi.org/10.7554/eLife.73983
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