Alternative polyadenylation mediates genetic regulation of gene expression
Abstract
Little is known about co-transcriptional or post-transcriptional regulatory mechanisms linking noncoding variation to variation in organismal traits. To begin addressing this gap, we used 3' Seq to study the impact of genetic variation on alternative polyadenylation (APA) in the nuclear and total mRNA fractions of 52 HapMap Yoruba human lymphoblastoid cell lines. We mapped 602 APA quantitative trait loci (apaQTLs) at 10% FDR, of which 152 were nuclear specific. Effect sizes at intronic apaQTLs are negatively correlated with eQTL effect sizes. These observations suggest genetic variants can decrease mRNA expression levels by increasing usage of intronic PAS. We also identified 24 apaQTLs associated with protein levels, but not mRNA expression. Finally, we found that 19% of apaQTLs can be associated with disease. Thus, our work demonstrates that APA links genetic variation to variation in gene expression, protein expression, and disease risk, and reveals uncharted modes of genetic regulation.
Data availability
Fastq files and PAS annotations are available at GEO under accession GSE138197. All reproducible scripts and software versions can be found at through Zenodo with doi:10.5281/zenodo.3905372
-
Alternative polyadenylation mediates genetic regulation of gene expressionNCBI Gene Expression Omnibus, GSE138197.
-
Alternative polyadenylation mediates genetic regulation of gene expressionZenodo, doi:10.5281/zenodo.3905372.
Article and author information
Author details
Funding
National Institutes of Health (T32 GM09197)
- Briana E Mittleman
National Institutes of Health (F31HL149259)
- Briana E Mittleman
National Institutes of Health (R01GM130738)
- Yang Li
National Institutes of Health (K12 HL119995)
- Sebastian Pott
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Mittleman 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.
Metrics
-
- 5,185
- views
-
- 570
- downloads
-
- 58
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.