Back

Exploring genetic diversity in the species-rich genus Liolaemus: The interplay among isolation by distance, body size, and environmental variability

Ruiz Monachesi, M. R.; Cruz, F. B.; Martinez, J. J.

2025-01-24 evolutionary biology
10.1101/2025.01.21.634185 bioRxiv
Show abstract

Intraspecific genetic variation enhances the specie[s] capacity to endure diverse environments. Such variation may drive genetic divergence among populations, often manifesting as isolation by distance (IBD). Here, we investigated how ecological, environmental, life-history, morphological, and phylogenetic factors, shape IBD and genetic diversity ({pi}) in Liolaemus lizards. Further we explored differences related to reproductive modes and taxonomic groups. Using data from GenBank, we examined two mitochondrial genes: Cytb (86 species) and 12S rRNA (37 species). We integrated geographic information for each species to evaluate genetic differentiation concerning spatial distribution. We calculated the IBD slope ({beta}IBD), Mante[l]s r, and {pi} for each gene, then tested for an association between {beta}IBD and {pi}. Phylogenetic multiple linear regression revealed that IBD, in the case of Cytb, was present in 56.16% of species and was negatively associated with snout-vent length (SVL). At the same time {beta}IBD-Cytb was positively linked to geographic range size. Additionally, {pi} of Cytb gene declined with increasing temperature range variability and body size. In contrast, for 12S rRNA, IBD was present in 42.42% of species but showed no relation with SVL; instead, phylogenetic history played a more substantial role in determining {pi}-12S rRNA. Remarkably, only Cytb showed a positive association between {beta} and {pi}. These results underscore different evolutionary patterns across the two genes and suggest that both, isolation by distance, alongside thermal heterogeneity, shape genetic diversity within particular reproductive modes and phylogenetic contexts in Liolaemus.

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.