Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay
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nihms787218.pdf
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Author(s)
Park, Daniel S.
Liu, Brandon
Winnicki, Sarah
Reilly, Steven K.
Andersen, Kristian G.
Tewhey, Ryan
Kotliar, Dylan A.
Andersen, Kristian
Mikkelsen, Tarjei
Lander, Eric Steven
Date Issued
February 2018
Journal
Cell
Publisher
Elsevier
Citation
Tewhey, Ryan, Dylan Kotliar, Daniel S. Park, Brandon Liu, Sarah Winnicki, Steven K. Reilly, Kristian G. Andersen, et al. “Direct Identification of Hundreds of Expression-Modulating Variants Using a Multiplexed Reporter Assay.” Cell 165, no. 6 (June 2016): 1519–1529.
Version
Author's final manuscript
Abstract
Although studies have identified hundreds of loci associated with human traits and diseases, pinpointing causal alleles remains difficult, particularly for non-coding variants. To address this challenge, we adapted the massively parallel reporter assay (MPRA) to identify variants that directly modulate gene expression. We applied it to 32,373 variants from 3,642 cis-expression quantitative trait loci and control regions. Detection by MPRA was strongly correlated with measures of regulatory function. We demonstrate MPRA’s capabilities for pinpointing causal alleles, using it to identify 842 variants showing differential expression between alleles, including 53 well-annotated variants associated with diseases and traits. We investigated one in detail, a risk allele for ankylosing spondylitis, and provide direct evidence of a non-coding variant that alters expression of the prostaglandin EP4 receptor. These results create a resource of concrete leads and illustrate the promise of this approach for comprehensively interrogating how non-coding polymorphism shapes human biology.
MIT Department
Broad Institute of MIT and Harvard
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mathematics
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.CELL.2016.04.027
