Rare variants contribute disproportionately to quantitative trait variation in yeast

Abstract
Data availability
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Abstract

How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1,011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.

Data availability

Unless otherwise specified, all computational analyses were performed in R (v3.4.4). Analysis code and processing scripts are available at https://github.com/joshsbloom/yeast-16-parents. Additional links to generated data are also provided in the github repository. The version numbers of R packages used are listed in this repository. Sequencing data has been deposited in the SRA under the accession code PRJNA549760.

The following data sets were generated

1. Bloom JS
2. Boocock J
3. Treusch S
4. Sadhu MJ
5. Day L
6. Oates-Barker H
7. Kruglyak L
(2019) Rare variants contribute disproportionately to quantitative trait variation in yeast, Jun 19 '19
SRA Bioproject, PRJNA549760.

http://www.ncbi.nlm.nih.gov/bioproject/549760

Article and author information

Author details

Joshua S Bloom

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

For correspondence
jbloom@mednet.ucla.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-7241-1648
James Boocock

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Sebastian Treusch

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Meru J Sadhu

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Laura Day

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Holly Oates-Barker

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

Competing interests
The authors declare that no competing interests exist.
Leonid Kruglyak

Department of Human Genetics, University of California, Los Angeles, Los Angeles, United States

For correspondence
LKruglyak@mednet.ucla.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-8065-3057

Funding

National Institutes of Health (R01GM102308)

Joshua S Bloom
Meru J Sadhu
Laura Day
Holly Oates-Barker
Leonid Kruglyak

Howard Hughes Medical Institute

Joshua S Bloom
Laura Day
Holly Oates-Barker
Leonid Kruglyak

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

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.