ArticleNucleic acids research2023
Gene expressions associated with longer lifespan and aging exhibit similarity in mammals.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Unlocking longevity through the comparative biology of aging.Nature aging · 2025Review
- Evaluating transcriptional alterations associated with ageing and developing age prediction models based on the human blood transcriptome.Biogerontology · 2025Article
- An atlas of the aging mouse proteome reveals the features of age-related post-transcriptional dysregulation.Nature communications · 2024Article
- CD44 correlates with longevity and enhances basal ATF6 activity and ER stress resistance.Cell reports · 2023Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Although molecular features underlying aging and species maximum lifespan (MLS) have been comprehensively studied by transcriptome analyses, the actual impact of transcriptome on aging and MLS remains elusive. Here, we found that transcriptional signatures that are associated with mammalian MLS exhibited significant similarity to those of aging. Moreover, transcriptional signatures of longer MLS and aging both exhibited significant similarity to that of longer-lived mouse strains, suggesting that gene expression patterns associated with species MLS contribute to extended lifespan even within a species and that aging-related gene expression changes overall represent adaptations that extend lifespan rather than deterioration. Finally, we found evidence of co-evolution of MLS and promoter sequences of MLS-associated genes, highlighting the evolutionary contribution of specific transcription factor binding motifs such as that of E2F1 in shaping MLS-associated gene expression signature. Our results highlight the importance of focusing on adaptive aspects of aging transcriptome and demonstrate that cross-species genomics can be a powerful approach for understanding adaptive aging transcriptome.
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