Evidence map›Paper›PMID 25657249›Full record

ArticleScience (New York, N.Y.)2015

Genomic variation. Impact of regulatory variation from RNA to protein.

Alexis Battle, Zia Khan, Sidney H Wang, Amy Mitrano, Michael J Ford, Jonathan K Pritchard, Yoav Gilad

Open access · bronzeAbstract read
In one paragraph

Article in Science (New York, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 291 papers.

0numbers the graph read from it
0cells of the map it votes in
291citing papers in PubMed
18.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

291 citing papers in PubMed, 517 citations in OpenAlex.

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  17. Multi-Tissue Genetic Regulation of RNA Editing in Pigs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  18. Article
  19. Article
  20. Article

231 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Alexis BattleDepartment of Genetics, Stanford University, Stanford, CA 94305, USA. Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
Zia KhanDepartment of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
Sidney H WangDepartment of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
Amy MitranoDepartment of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
Michael J FordMS Bioworks, LLC, 3950 Varsity Drive, Ann Arbor, MI 48108, USA.
Jonathan K PritchardDepartment of Genetics, Stanford University, Stanford, CA 94305, USA. Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. Department of Biology, Stanford University, Stanford, CA 94305, USA. pritch@stanford.edu gilad@uchicago.edu.
Yoav GiladDepartment of Human Genetics, University of Chicago, Chicago, IL 60637, USA. pritch@stanford.edu gilad@uchicago.edu.
University of Chicago · USBioWorks (United States) · USHoward Hughes Medical Institute · USStanford University · US

Funding

Analysis and interpretation of noncoding regulatory variationR01MH084703 · NIMH · UNIVERSITY OF CHICAGO · PI GILAD, YOAV, PRITCHARD, JONATHAN K · 2008 to 2015
$3.4M
Natural Selection on Gene Regulation in HumansR01GM077959 · NIGMS · UNIVERSITY OF CHICAGO · PI GILAD, YOAV · 2006 to 2014
$2.9M
Genetic and epigenetic controls of gene regulationU01HG007036 · NHGRI · UNIVERSITY OF CHICAGO · PI PRITCHARD, JONATHAN K · 2012 to 2015
$1.4M
The Genetic Basis for Post-transcriptional Regulatory Variation in HumansF32HG006972 · NHGRI · UNIVERSITY OF CHICAGO · PI KHAN, ZIA · 2012 to 2013
$61k
Howard Hughes Medical InstituteNHGRI NIH HHS F32 HG006972NHGRI NIH HHS F32HG006972NHGRI NIH HHS HG007036NHGRI NIH HHS U01 HG007036NIGMS NIH HHS GM077959NIGMS NIH HHS R01 GM077959NIMH NIH HHS MH084703NIMH NIH HHS R01 MH084703
6 · The paper itself

Abstract

The phenotypic consequences of expression quantitative trait loci (eQTLs) are presumably due to their effects on protein expression levels. Yet the impact of genetic variation, including eQTLs, on protein levels remains poorly understood. To address this, we mapped genetic variants that are associated with eQTLs, ribosome occupancy (rQTLs), or protein abundance (pQTLs). We found that most QTLs are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, eQTLs tend to have significantly reduced effect sizes on protein levels, which suggests that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we identified a class of cis QTLs that affect protein abundance with little or no effect on messenger RNA or ribosome levels, which suggests that they may arise from differences in posttranslational regulation.

Indexed as

Gene Expression RegulationGenetic VariationQuantitative Trait LociTranscription, Genetic3' Flanking Region5' Flanking RegionCell LineExonsHumansPhenotypeProtein BiosynthesisRibosomesRNA, MessengerRNA, Messenger

Identifiers

PMID25657249
PMCPMC4507520
OpenAlexW2044286001

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.