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High-resolution mapping of cis-regulatory variation in budding yeast

  1. Hunter B. Frasera,1
  1. aDepartment of Biology, Stanford University, Stanford, CA 94305
  1. Edited by Jasper Rine, University of California, Berkeley, CA, and approved November 3, 2017 (received for review October 4, 2017)

Significance

Genetic variants affecting gene-expression levels are a major source of phenotypic variation. Using 85 diverse isolates of Saccharomyces cerevisiae, we mapped genetic variants that affect gene expression with 50-fold higher resolution than previously possible. By doing so, we were able to pinpoint likely causal variants and investigate their molecular mechanisms. We found that these genetic variants are generally under negative selection, but also that clinical yeast isolates have undergone positive selection for up-regulation of genes involved in biofilm suppression. Altogether, our results demonstrate the power of high-resolution mapping of genetic variants that affect gene expression, particularly in understanding the molecular mechanisms of regulatory variation and the natural selection acting on this variation.

Abstract

Genetic variants affecting gene-expression levels are a major source of phenotypic variation. The approximate locations of these variants can be mapped as expression quantitative trait loci (eQTLs); however, a major limitation of eQTLs is their low resolution, which precludes investigation of the causal variants and their molecular mechanisms. Here we report RNA-seq and full genome sequences for 85 diverse isolates of the yeast Saccharomyces cerevisiae—including wild, domesticated, and human clinical strains—which allowed us to perform eQTL mapping with 50-fold higher resolution than previously possible. In addition to variants in promoters, we uncovered an important role for variants in 3′UTRs, especially those affecting binding of the PUF family of RNA-binding proteins. The eQTLs are predominantly under negative selection, particularly those affecting essential genes and conserved genes. However, applying the sign test for lineage-specific selection revealed the polygenic up-regulation of dozens of biofilm suppressor genes in strains isolated from human patients, consistent with the key role of biofilms in fungal pathogenicity. In addition, a single variant in the promoter of a biofilm suppressor, NIT3, showed the strongest genome-wide association with clinical origin. Altogether, our results demonstrate the power of high-resolution eQTL mapping in understanding the molecular mechanisms of regulatory variation, as well as the natural selection acting on this variation that drives adaptation to environments, ranging from laboratories to vineyards to the human body.

Footnotes

  • ?1To whom correspondence should be addressed. Email: hbfraser{at}stanford.edu.
  • Author contributions: R.K. and H.B.F. designed research; R.K., S.V., and Y.Z. performed research; R.K. analyzed data; and R.K. and H.B.F. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • Data deposition: All RNA-Seq and DNA-Seq data are deposited in the NCBI Sequence Read Archive (Bioproject PRJNA342356).

  • This article contains supporting information online at www.danielhellerman.com/lookup/suppl/doi:10.1073/pnas.1717421114/-/DCSupplemental.

Published under the PNAS license.

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