Back

A mitochondrial mutational signature of temperature and longevity in ectothermic and endothermic vertebrates.

Mikhailova, A. G.; Shamanskiy, V.; Mihailova, A. A.; Ushakova, K.; Tretiakov, E.; Oreshkov, S.; Knorre, D.; Polishchuk, L.; Lawless, D.; Mazunin, I.; Kunz, W.; Tanaka, M.; Fleischmann, Z.; Aidlen, D.; Makeev, V.; Kuptsov, A.; Fellay, J. S.; Khrapko, K.; Gunbin, K.; Popadin, K.

2020-07-26 evolutionary biology
10.1101/2020.07.25.221184 bioRxiv
Show abstract

The variation in the mutational spectrum of the mitochondrial genome (mtDNA) among species is not well understood. Recently, we demonstrated an increase in A>G substitutions on a heavy chain (hereafter AH>GH) of mtDNA in aged mammals, interpreting it as a hallmark of age-related oxidative damage. In this study, we hypothesized that the occurrence of AH>GH substitutions may depend on the level of aerobic metabolism, which can be inferred from an organisms body temperature. To test this hypothesis, we used body temperature in endotherms and environmental temperature in ectotherms as proxies for metabolic rate and reconstructed mtDNA mutational spectra for 1350 vertebrate species. Our results showed that temperature was associated with increased rates of AH>GH and asymmetry of AH>GH in different species of ray-finned fishes and within geographically distinct clades of European anchovy. Analysis of nucleotide composition in the most neutral synonymous sites of fishes revealed that warm-water species were expectedly more A-poor and G-rich compared to cold-water species. Finally, we extended our analyses to all vertebrates and observed higher AH>GH and increased asymmetry of AH>GH in warm-blooded (mammals and birds) compared to cold-blooded (Actinopterygii, amphibia, reptilia) vertebrate classes. Overall, our findings suggest that temperature, through its influence on metabolism and oxidative damage, shapes the mutational properties and nucleotide content of the mtDNA in all vertebrates.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.