Genetics of trans-regulatory variation in gene expression
Abstract
Heritable variation in gene expression forms a crucial bridge between genomic variation and the biology of many traits. However, most expression quantitative trait loci (eQTLs) remain unidentified. We mapped eQTLs by transcriptome sequencing in 1,012 yeast segregants. The resulting eQTLs accounted for over 70% of the heritability of mRNA levels, allowing comprehensive dissection of regulatory variation. Most genes had multiple eQTLs. Most expression variation arose from trans-acting eQTLs distant from their target genes. Nearly all trans-eQTLs clustered at 102 hotspot locations, some of which influenced the expression of thousands of genes. Fine-mapped hotspot regions were enriched for transcription factor genes. While most genes had a local eQTL, most of these had no detectable effects on the expression of other genes in trans. Hundreds of non-additive genetic interactions accounted for small fractions of expression variation. These results reveal the complexity of genetic influences on transcriptome variation in unprecedented depth and detail.
Data availability
Sequencing reads have been deposited at SRA under accession codes SRP148919 and SRP149494. Processed datasets are included with this manuscript, and are also available in a FigShare repository at https://figshare.com/s/83bddc1ddf3f97108ad4. All data are available freely and without restriction.
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A global genetic interaction network maps a wiring diagram of cellular functionRaw genetic interaction datasets: Pair-wise interaction format.
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Finding the sources of missing heritability in a yeast crossGenomic DNA sequencing reads.
Article and author information
Author details
Funding
Howard Hughes Medical Institute (Investigator)
- Leonid Kruglyak
National Institute of General Medical Sciences (R01GM102308)
- Leonid Kruglyak
National Institute of General Medical Sciences (1R35GM124676-01)
- Frank Wolfgang Albert
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Albert 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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