Evolutionary history of mental glands in turtles reveals a single origin in an aquatic ancestor and recurrent losses independent of macrohabitat

Abstract

Despite the relevance of chemical communication in vertebrates, comparative examinations of macroevolutionary trends in chemical signaling systems are scarce. Many turtle and tortoise species are reliant on chemical signals to communicate in aquatic and terrestrial macrohabitats, and many of these species possess specialized integumentary organs, termed mental glands (MGs), involved in the production of chemosignals. We inferred the evolutionary history of MGs and tested the impact of macrohabitat on their evolution. Inference of ancestral states along a time-calibrated phylogeny revealed a single origin in the ancestor of the subclade Testudinoidea. Thus, MGs represent homologous structures in all descending lineages. We also inferred multiple independent losses of MGs in both terrestrial and aquatic clades. Although MGs first appeared in an aquatic turtle (the testudinoid ancestor), macrohabitat seems to have had little effect on MG presence or absence in descendants. Instead, we find clade-specific evolutionary trends, with some clades showing increased gland size and morphological complexity, whereas others exhibiting reduction or MG loss. In sister clades inhabiting similar ecological niches, contrasting patterns (loss vs. maintenance) may occur. We conclude that the multiple losses of MGs in turtle clades have not been influenced by macrohabitat and that other factors have affected MG evolution.

How aestivation evolve in turtles? a macroevolutionary and morphological approach

“…The second allowed for transition rates between states to differ (ARD model). These two models assume that the process generating the different states at the tips and ancestral nodes is homogenous across all branches of a phylogenetic tree, which may be a major simpli cation of biological reality (Ibáñez et al 2021). The generalized hidden Markov model (Beaulieu and Donoghue 2013; Boyko and Beaulieu 2021) implemented in corHMM v2.5 relaxes this assumption by allowing more than one process to affect trait evolution across a phylogeny.…”

“…This is achieved by constructing > 1 rate categories (i.e. transition matrices) and allowing them to vary across the tree by parameterizing the transitions among rate categories (Ibáñez et al 2021). We constructed three different models, each with two rate matrices (R1 and R2, rate.cat = 2).…”