1. Genetics and Genomics
Download icon

Alternative polyadenylation mediates genetic regulation of gene expression

Research Article
  • Cited 0
  • Views 670
  • Annotations
Cite this article as: eLife 2020;9:e57492 doi: 10.7554/eLife.57492

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.

Article and author information

Author details

  1. Briana E Mittleman

    Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4979-4652
  2. Sebastian Pott

    Department of Human Genetics, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4118-6150
  3. Shane Warland

    Section of Genetic Medicine, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Tony Zeng

    Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Zepeng Mu

    Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7717-3247
  6. Mayher Kaur

    Section of Genetic Medicine, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Yoav Gilad

    Department of Medicine, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8284-8926
  8. Yang Li

    Department of Medicine, Department of Human Genetics, University of Chicago, Chicago, United States
    For correspondence
    yangili1@uchicago.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0736-251X

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.

Reviewing Editor

  1. Gene W Yeo, University of California, San Diego, United States

Publication history

  1. Received: April 2, 2020
  2. Accepted: June 17, 2020
  3. Accepted Manuscript published: June 25, 2020 (version 1)

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

  • 670
    Page views
  • 107
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Evolutionary Biology
    2. Genetics and Genomics
    CJ Battey et al.
    Tools and Resources Updated
    1. Genetics and Genomics
    Yasuhiro Kazuki et al.
    Research Article