Conservation of pro-longevity genes among mammals

• Published in: Mechanisms of ageing and development Vol. 146-148; pp. 23 - 27
• Main Authors: Lindborg, Carter M., Propert, Kathleen J., Pignolo, Robert J.
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 01-03-2015
• Subjects: Aging; Animals; Databases, Genetic; Genes; Genetics; Homology; Humans; Longevity; Longevity - genetics; Models, Genetic; Aging; Genetics; Homology; Longevity; Genes
• ISSN: 0047-6374; 1872-6216
• DOI: 10.1016/j.mad.2015.03.004

•We identify longevity associated genes (LAGs) by multiple regression analyses.•We evaluated over 10,000 homologous genes across 30–39 mammalian species.•We provide a ranking of genes with the strongest associations with species maximum lifespan (MLS).•Known LAGs have strong associations with species maximum MLS.•LAGs were commonly related to immune function, cell cycle, and DNA damage response.
Genes which confer a relative longevity advantage may be regulated at the level of transcription or translation. Alternatively, pro-longevity genes may mediate their effects at the level of protein structure-functional relationships that are beneficially optimized in long-lived species. Longevity associated genes (LAGs) may be operationally defined as genes that confer beneficial effects and are relatively more conserved among long-lived species. Global and local protein sequence alignments of over 10,000 genes across at least 30 mammalian species were examined to identify LAGs. Known LAGs, including growth hormone receptor (GHR), and breast cancer 1, early onset (BRCA1), have strong associations with maximum lifespan by our analysis. Several common categories of protein function were observed among genes ranked with the strongest associations with MLS identified by all regression models. These genes included those that function in the immune system, cell cycle regulation, and DNA damage response. We provide a ranking of genes with the strongest associations with species maximum lifespan (MLS) by several phylogenetic generalized least squares regression models, including adjustment for confounding variables such as body weight and gestation length.