ArticleScientific reports2015
The proportion of genes in a functional category is linked to mass-specific metabolic rate and lifespan.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Revisiting the hypothesis of an energetic barrier to genome complexity between eukaryotes and prokaryotes.Royal Society open science · 2020Article
- Exosomes in mammals with greater habitat variability contain more proteins and RNAs.Royal Society open science · 2017Article
- Importance of metabolic rate to the relationship between the number of genes in a functional category and body size in Peto's paradox for cancer.Royal Society open science · 2016Article
- Evolutionary constraints over microsatellite abundance in larger mammals as a potential mechanism against carcinogenic burden.Scientific reports · 2016Article
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Authors and funding
2 authors.
Funding
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Abstract
Metabolic rate and lifespan are important biological parameters that are studied in a wide range of research fields. They are known to correlate with body mass, but their association with gene (protein) functions is poorly understood. In this study, we collected data on the metabolic rate and lifespan of various organisms and investigated the relationship of these parameters with their genomes. We showed that the proportion of genes in a functional category, but not genome size, was correlated with mass-specific metabolic rate and maximal lifespan. In particular, the proportion of genes in oxic reactions (which occur in the presence of oxygen) was significantly associated with these two biological parameters. Additionally, we found that temperature, taxonomy, and mode-of-life traits had little effect on the observed associations. Our findings emphasize the importance of considering the biological functions of genes when investigating the relationships between genome, metabolic rate, and lifespan. Moreover, this provides further insights into these relationships, and may be useful for estimating metabolic rate and lifespan in individuals and the ecosystem using a combination of body mass measurements and genomic data.
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