High-resolution mapping of cis-regulatory variation in budding yeast
Sunday, 2017/12/24 | 07:17:04
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Ryosuke Kita, Sandeep Venkataram, Yiqi Zhou, and Hunter B. Fraser GENETICS PNAS December 12 2017; vol.114; no.50: E10736–E10744 SignificanceGenetic 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. AbstractGenetic 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.
See: http://www.pnas.org/content/114/50/E10736.full
Fig. 4. GWAS and differential expression of biofilm genes between clinical and nonclinical strains. (A) Manhattan plot of clinical and nonclinical variants. (B) Higher detail of the region neighboring the strongest GWAS variant. The locations of genes are shown behind the Manhattan plot and the linkage disequilibrium is shown below. (C) Expression of biofilm suppressor gene set. The x axis is the average rank of differential expression across the gene set. The gene with the most significant lower clinical expression has a rank of zero. Gray histogram presents the distribution from null permutations of the average rank from gene sets of the same size. The green arrow indicates the observed average rank. *P < 0.05. |
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