bioRxivEvolutionary BiologyPreprint
Bioclimatic variables influence the strength of purifying selection on mitochondrial DNA in an avian clade (Aves: Piciformes)
Jérôme FuchsiD, Benoît NabholziD, Brieuc Kaesmann, Jean‐Marc PonsiD, Céline BonilloiD, Martin IrestedtiD, Sophea ChhiniD, Dawie de SwardtiD, Inocêncio Chongo, Almiro Rogério TivaneiD, Eduardo Samo GudoiD, Per G. P. EricsoniD
Abstract
Mitochondrial loci were for long considered as markers of choice to reconstruct phylogenies. The development of high-throughput sequencing over the past two decades fostered the sequencing of mitogenomes, allowing further macroevolutionary questions to be tested. Several biological traits of birds (e.g. body mass, migration distances) have been related to mitochondrial substitution rates. Environmental parameters in ectothermics vertebrates, and potentially in endotherms, have been further suggested to impact substitution rates for specific taxa or loci. Yet, the relative importance of biological traits versus bioclimatic variables is unknown because the former were not systematically controlled for in studies that underlined the effect of the bioclimatic variables. To assess the importance of bioclimatic variables on selection regimes, we analysed the thirteen mitochondrial protein-coding genes for 176 Piciformes (toucans, honeyguides, woodpeckers), a clade with homogeneous life-history traits that can be found in diverse bioclimatic environments. Our analyses highlighted a negative relationship between temperature annual range and the non synonymous to synonymous substitutions ratio. The higher purifying selection in temperate environments may be a result of the strong constraints on maintaining an optimal metabolism in broader climatic variations. Our results further highlight that care should be taken when applying general mitochondrial clocks to estimate divergence times among avian lineages distributed in different climatic conditions.
- organism: Xenopus
- assay: DNA methylation
- research focus: phylogenetics / evolution
- approach: statistical model
- Citations
- 0
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