Genome-wide interrogation advances resolution of recalcitrant groups in the tree of life

Much progress has been achieved in disentangling evolutionary relationships among species in the tree of life, but some taxonomic groups remain difficult to resolve despite increasing availability of genome-scale data sets. Here we present a practical approach to studying ancient divergences in the...

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Autores:
Tipo de recurso:
Fecha de publicación:
2017
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/27774
Acceso en línea:
https://doi.org/10.1038/s41559-016-0020
https://repository.urosario.edu.co/handle/10336/27774
Palabra clave:
Ichthyology
Phylogenetics
Rights
License
Restringido (Acceso a grupos específicos)
Description
Summary:Much progress has been achieved in disentangling evolutionary relationships among species in the tree of life, but some taxonomic groups remain difficult to resolve despite increasing availability of genome-scale data sets. Here we present a practical approach to studying ancient divergences in the face of high levels of conflict, based on explicit gene genealogy interrogation (GGI). We show its efficacy in resolving the controversial relationships within the largest freshwater fish radiation (Otophysi) based on newly generated DNA sequences for 1,051 loci from 225 species. Initial results using a suite of standard methodologies revealed conflicting phylogenetic signal, which supports ten alternative evolutionary histories among early otophysan lineages. By contrast, GGI revealed that the vast majority of gene genealogies supports a single tree topology grounded on morphology that was not obtained by previous molecular studies. We also reanalysed published data sets for exemplary groups with recalcitrant resolution to assess the power of this approach. GGI supports the notion that ctenophores are the earliest-branching animal lineage, and adds insight into relationships within clades of yeasts, birds and mammals. GGI opens up a promising avenue to account for incompatible signals in large data sets and to discern between estimation error and actual biological conflict explaining gene tree discordance.