Evidence map›Paper›PMID 39814022›Full record

ArticleAmerican journal of human genetics2025

No evidence for sex-differential transcriptomes driving genome-wide sex-differential natural selection.

Matthew J Ming, Changde Cheng, Mark Kirkpatrick, Arbel Harpak

Abstract read
In one paragraph

Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Reverse genetics of sexual antagonism.Nature ecology & evolution · 2026
    Article
  2. Article
  3. Drivers of systemic male-female allele frequency divergence in humans.bioRxiv : the preprint server for biology · 2026
    Article
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

4 authors.

Matthew J MingDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA.
Changde ChengSchool of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
Mark KirkpatrickDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA.
Arbel HarpakDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, USA; Department of Population Health, University of Texas at Austin, Austin, TX, USA. Electronic address: arbelharpak@utexas.edu.

Funding

Genomic causes and consequences of sexually antagonistic selectionR01GM116853 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI KIRKPATRICK, MARK · 2015 to 2022
$3.5M
Making Genomic Prediction of Complex Disease EquitableR35GM151108 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Arbel Harpak · 2023 to 2026
$1.6M
NIGMS NIH HHS R01 GM116853NIGMS NIH HHS R35 GM151108
6 · The paper itself

Abstract

Sex differences in human transcriptomes have been argued to drive sex-differential selection (SDS). Here, we show that previous evidence supporting this hypothesis has been largely unfounded. We develop a method to test for a genome-wide relationship between sex differences in expression and selection on expression-influencing alleles (expression quantitative trait loci [eQTLs]). We apply it across 34 human tissues and find no evidence for a general relationship. We offer possible explanations for the lack of evidence, including that it is due in part to eQTL ascertainment bias toward sites under weak selection. We conclude that the drivers of ongoing SDS in humans remain to be identified.

Indexed as

Genome, HumanSelection, GeneticSex CharacteristicsTranscriptomeAllelesFemaleGenome-Wide Association StudyHumansMalePolymorphism, Single NucleotideQuantitative Trait Locigene expressioninference of selectionpopulation geneticssex-differential selection

Identifiers

PMID39814022
PMCPMC11866945

What OpenQuestion holds

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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.