Evidence map›Paper›PMID 41473298›Full record

ArticlebioRxiv : the preprint server for biology2025

Parallel Selection for Longevity in Mammals and Birds.

William B Zhang, Marcus R Kronforst

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

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.

William B ZhangDepartment of Pathology, University of Chicago.ORCID 0000-0002-4372-5496
Marcus R KronforstDepartment of Ecology & Evolution, University of Chicago.

Funding

J. NRSA Training CoreTL1TR002388 · NCATS · UNIVERSITY OF CHICAGO · PI ALI KESHAVARZIAN, Sonia Kupfer · 2017 to 2026
$6.7M
Characterizing the Molecular Basis of Supergene Mimicry in ButterfliesR35GM131828 · NIGMS · UNIVERSITY OF CHICAGO · PI Marcus Kronforst · 2019 to 2026
$3.3M
NCATS NIH HHS TL1 TR002388NIGMS NIH HHS R35 GM131828
6 · The paper itself

Abstract

Most studies of aging biology to date have involved the manipulation of short-lived model organisms, while the existing anti-aging mechanisms in naturally occurring long-lived vertebrates have generally remained undiscovered or understudied. The technological advances of the recent "omics revolution" have enabled comparative genomics studies, which have started to unravel genetic signatures of longevity in vertebrates. Building on prior studies and incorporating a novel approach to detecting convergent positive selection, we conducted the first genome-wide survey of positive and purifying selection among hundreds of long-lived mammals and birds, two major vertebrate taxa with notable parallels in their evolutionary history. We discovered an extensive network of shared pathways under purifying selection in both mammals that are exceptionally long-lived for their body size (ELL) and large-bodied long-lived (LLL) birds. In our positive selection survey, we identified 16 genes, involved in eight distinct hallmarks of aging, with concordant signals of positive selection in LLL mammals and LLL birds at neighboring amino acid residues. These included two genes directly involved in cholesterol metabolism, as well as genes whose products clear oxidized metabolites and regulate peroxisomal autophagy. These striking parallels between long-lived mammals and birds, both in broad pathways under purifying selection, as well as in instances of genes under parallel positive selection in LLL mammals and LLL birds, together imply an ancient shared genetic toolkit for longevity, deeply conserved and repeatedly modified to produce longevity in diverse lineages.

Identifiers

PMID41473298
PMCPMC12746067

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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.