Abstract
Originalsprog | Engelsk |
---|---|
Tidsskrift | Current Biology |
Vol/bind | 14 |
Udgave nummer | 18 |
Sider (fra-til) | 1644-9 |
Antal sider | 5 |
ISSN | 0960-9822 |
DOI | |
Status | Udgivet - 2004 |
Bibliografisk note
901FCTimes Cited:1
Cited References Count:3
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Bayesian inference of the metazoan phylogeny : a combined molecular and morphological approach. / Glenner, Henrik; Hansen, Anders J; Sørensen, Martin V; Ronquist, Frederik; Huelsenbeck, John P; Willerslev, Eske.
I: Current Biology, Bind 14, Nr. 18, 2004, s. 1644-9.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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TY - JOUR
T1 - Bayesian inference of the metazoan phylogeny
T2 - a combined molecular and morphological approach
AU - Glenner, Henrik
AU - Hansen, Anders J
AU - Sørensen, Martin V
AU - Ronquist, Frederik
AU - Huelsenbeck, John P
AU - Willerslev, Eske
N1 - Keywords: Animals; Bayes Theorem; Chordata; Classification; DNA, Ribosomal; Databases, Genetic; Invertebrates; Models, Biological; Models, Genetic; Phylogeny
PY - 2004
Y1 - 2004
N2 - Metazoan phylogeny remains one of evolutionary biology's major unsolved problems. Molecular and morphological data, as well as different analytical approaches, have produced highly conflicting results due to homoplasy resulting from more than 570 million years of evolution. To date, parsimony has been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses demonstrate a high degree of congruence between morphological and molecular data, and both data sets contribute to the result of the combined analysis. Additionally, they resolve several irregularities obtained in previous studies and show high credibility values for controversial groups such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis.
AB - Metazoan phylogeny remains one of evolutionary biology's major unsolved problems. Molecular and morphological data, as well as different analytical approaches, have produced highly conflicting results due to homoplasy resulting from more than 570 million years of evolution. To date, parsimony has been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses demonstrate a high degree of congruence between morphological and molecular data, and both data sets contribute to the result of the combined analysis. Additionally, they resolve several irregularities obtained in previous studies and show high credibility values for controversial groups such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis.
U2 - 10.1016/j.cub.2004.09.027
DO - 10.1016/j.cub.2004.09.027
M3 - Journal article
C2 - 15380066
VL - 14
SP - 1644
EP - 1649
JO - Current Biology
JF - Current Biology
SN - 0960-9822
IS - 18
ER -