Parallel Selection for Longevity in Mammals and Birds

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.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2025-12-17
DOI
https://doi.org/10.64898/2025.12.16.694703
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
article
Field-Weighted Citation Impact
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article

Parallel Selection for Longevity in Mammals and Birds

Marcus R. Kronforst, William B. Zhang
bioRxiv (Cold Spring Harbor Laboratory)
Genetics, Aging, and Longevity in Model Organisms
article

Parallel Selection for Longevity in Mammals and Birds

Marcus R. Kronforst, William B. Zhang
article en

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.

bioRxiv (Cold Spring Harbor Laboratory)
University of Chicago (US)
Openalex Percentile: Top 62%
Genetics, Aging, and Longevity in Model Organisms
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