Estimating the phylogeny and divergence times of primates using a supermatrix approach
Date
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Chatterjee, Helen J
Ho, Simon
Barnes, Ian
Groves, Colin
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BioMed Central Ltd
Abstract
BACKGROUND: The primates are among the most broadly studied mammalian orders, with the
published literature containing extensive analyses of their behavior, physiology, genetics and
ecology. The importance of this group in medical and biological research is well appreciated, and
explains the numerous molecular phylogenies that have been proposed for most primate families
and genera. Composite estimates for the entire order have been infrequently attempted, with the
last phylogenetic reconstruction spanning the full range of primate evolutionary relationships having
been conducted over a decade ago.
RESULTS: To estimate the structure and tempo of primate evolutionary history, we employed
Bayesian phylogenetic methods to analyze data supermatrices comprising 7 mitochondrial genes
(6,138 nucleotides) from 219 species across 67 genera and 3 nuclear genes (2,157 nucleotides)
from 26 genera. Many taxa were only partially represented, with an average of 3.95 and 5.43
mitochondrial genes per species and per genus, respectively, and 2.23 nuclear genes per genus. Our
analyses of mitochondrial DNA place Tarsiiformes as the sister group of Strepsirrhini. Within
Haplorrhini, we find support for the primary divergence of Pitheciidae in Platyrrhini, and our results
suggest a sister grouping of African and non-African colobines within Colobinae and of
Cercopithecini and Papionini within Cercopthecinae. Date estimates for nodes within each family
and genus are presented, with estimates for key splits including: Strepsirrhini-Haplorrhini 64 million
years ago (MYA), Lemuriformes-Lorisiformes 52 MYA, Platyrrhini-Catarrhini 43 MYA and
Cercopithecoidea-Hominoidea 29 MYA.
CONCLUSION: We present an up-to-date, comprehensive estimate of the structure and tempo of
primate evolutionary history. Although considerable gaps remain in our knowledge of the primate
phylogeny, increased data sampling, particularly from nuclear loci, will be able to provide further
resolution.
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BMC Evolutionary Biology 9.259 (2009)
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BMC Evolutionary Biology
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