Evolutionary History of the Asian Horned Frogs (Megophryinae): Integrative Approaches to Timetree Dating in the Absence of a Fossil Record

近亲 生物 系统发育树 系统发育学 进化生物学 变异 古生物学 动物 系统地理学 克莱德 基因 生物化学
作者
Stephen Mahony,Nicole M. Foley,S. D. Biju,Emma C. Teeling
出处
期刊:Molecular Biology and Evolution [Oxford University Press]
卷期号:34 (3): msw267-msw267 被引量:76
标识
DOI:10.1093/molbev/msw267
摘要

Molecular dating studies typically need fossils to calibrate the analyses. Unfortunately, the fossil record is extremely poor or presently nonexistent for many species groups, rendering such dating analysis difficult. One such group is the Asian horned frogs (Megophryinae). Sampling all generic nomina, we combined a novel ∼5 kb dataset composed of four nuclear and three mitochondrial gene fragments to produce a robust phylogeny, with an extensive external morphological study to produce a working taxonomy for the group. Expanding the molecular dataset to include out-groups of fossil-represented ancestral anuran families, we compared the priorless RelTime dating method with the widely used prior-based Bayesian timetree method, MCMCtree, utilizing a novel combination of fossil priors for anuran phylogenetic dating. The phylogeny was then subjected to ancestral phylogeographic analyses, and dating estimates were compared with likely biogeographic vicariant events. Phylogenetic analyses demonstrated that previously proposed systematic hypotheses were incorrect due to the paraphyly of genera. Molecular phylogenetic, morphological, and timetree results support the recognition of Megophryinae as a single genus, Megophrys, with a subgenus level classification. Timetree results using RelTime better corresponded with the known fossil record for the out-group anuran tree. For the priorless in-group, it also outperformed MCMCtree when node date estimates were compared with likely influential historical biogeographic events, providing novel insights into the evolutionary history of this pan-Asian anuran group. Given a relatively small molecular dataset, and limited prior knowledge, this study demonstrates that the computationally rapid RelTime dating tool may outperform more popular and complex prior reliant timetree methodologies.

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