Evidence map›Paper›PMID 35047867›Full record

ArticleHGG advances2022

Adaptive eQTLs reveal the evolutionary impacts of pleiotropy and tissue-specificity while contributing to health and disease.

Melanie H Quiver, Joseph Lachance

Open access · goldAbstract read
In one paragraph

Article in HGG advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 26 citations in OpenAlex.

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  10. Mechanisms of transcriptional regulation inProceedings. Biological sciences · 2024
    Article
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  12. Mechanisms of transcriptional regulation inbioRxiv : the preprint server for biology · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Melanie H QuiverSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Joseph LachanceSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Georgia Institute of Technology · US

Funding

Evolution of genetic disease risks over time and spaceR35GM133727 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI LACHANCE, JOSEPH L. · 2019 to 2023
$1.9M
A Computational Biology and Predictive Health Genomics Training Program at GTT32GM105490 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI GIBSON, GREGORY C · 2014 to 2018
$901k
NIGMS NIH HHS R35 GM133727NIGMS NIH HHS T32 GM105490
6 · The paper itself

Abstract

Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested if tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics and that adaptive eQTLs affect two-thirds as many tissues as do non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selections also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.

Indexed as

adaptationeQTLsgene expressionnatural selectionpleiotropypopulation genetics

Identifiers

PMID35047867
PMCPMC8756519
OpenAlexW4200563017

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.