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Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979589/ https://www.ncbi.nlm.nih.gov/pubmed/35147078 http://dx.doi.org/10.7554/eLife.73983 |
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author | Nguyen Ba, Alex N Lawrence, Katherine R Rego-Costa, Artur Gopalakrishnan, Shreyas Temko, Daniel Michor, Franziska Desai, Michael M |
author_facet | Nguyen Ba, Alex N Lawrence, Katherine R Rego-Costa, Artur Gopalakrishnan, Shreyas Temko, Daniel Michor, Franziska Desai, Michael M |
author_sort | Nguyen Ba, Alex N |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8979589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-89795892022-04-05 Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast Nguyen Ba, Alex N Lawrence, Katherine R Rego-Costa, Artur Gopalakrishnan, Shreyas Temko, Daniel Michor, Franziska Desai, Michael M eLife Evolutionary Biology 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. eLife Sciences Publications, Ltd 2022-02-11 /pmc/articles/PMC8979589/ /pubmed/35147078 http://dx.doi.org/10.7554/eLife.73983 Text en © 2022, Nguyen Ba et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Evolutionary Biology Nguyen Ba, Alex N Lawrence, Katherine R Rego-Costa, Artur Gopalakrishnan, Shreyas Temko, Daniel Michor, Franziska Desai, Michael M Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title | Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title_full | Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title_fullStr | Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title_full_unstemmed | Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title_short | Barcoded bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
title_sort | barcoded bulk qtl mapping reveals highly polygenic and epistatic architecture of complex traits in yeast |
topic | Evolutionary Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979589/ https://www.ncbi.nlm.nih.gov/pubmed/35147078 http://dx.doi.org/10.7554/eLife.73983 |
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