Evidence map›Paper›PMID 40236837›Full record

ArticleArXiv2025

Addressing missing context in regulatory variation across primate evolution.

Genevieve Housman, Audrey Arner, Amy Longtin, Christian Gagnon, Arun Durvasula, Amanda Lea

Abstract readPreprint
In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Genevieve HousmanDepartment of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
Audrey ArnerDepartment of Biological Sciences, Vanderbilt University, Nashville, TN, USA.
Amy LongtinDepartment of Biological Sciences, Vanderbilt University, Nashville, TN, USA.
Christian GagnonDepartment of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.
Arun DurvasulaDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Amanda LeaDepartment of Biological Sciences, Vanderbilt University, Nashville, TN, USA.

Funding

Early life environmental effects: molecular mechanisms and inter-individual variationR35GM147267 · NIGMS · VANDERBILT UNIVERSITY · PI Amanda Lea · 2022 to 2026
$2.0M
Early life effects on later life health and aging: molecular mechanisms and context-dependencyR21AG078554 · NIA · VANDERBILT UNIVERSITY · PI LEA, AMANDA · 2022 to 2023
$634k
NIA NIH HHS R21 AG078554NIGMS NIH HHS R35 GM147267
6 · The paper itself

Abstract

In primates, loci associated with adaptive trait variation often fall in non-coding regions. Understanding the mechanisms linking these regulatory variants to fitness-relevant phenotypes remains challenging, but can be addressed using functional genomic data. However, such data are rarely generated at scale in non-human primates. When they are, only select tissues, cell types, developmental stages, and cellular environments are typically considered, despite appreciation that adaptive variants often exhibit context-dependent effects. In this review, we 1) discuss why context-dependent regulatory loci might be especially evolutionarily relevant in primates, 2) explore challenges and emerging solutions for mapping such context-dependent variation, and 3) discuss the scientific questions these data could address. We argue that filling this gap will provide critical insights into evolutionary processes, human disease, and regulatory adaptation.

Indexed as

context-dependent gene regulationevolutionfunctional genomicsgenetics of adaptationprimates

Identifiers

PMID40236837
PMCPMC11998855

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.