Building the avian tree of life using a large-scale, sparse supermatrix

被引:121
作者
Burleigh, J. Gordon [1 ]
Kimball, Rebecca T. [1 ]
Braun, Edward L. [1 ]
机构
[1] Univ Florida, Dept Biol, Gainesville, FL 32611 USA
基金
美国国家科学基金会;
关键词
Supermatrix; Phylogeny; Birds; WALLACES ZOOGEOGRAPHIC REGIONS; MULTIPLE SEQUENCE ALIGNMENT; PHYLOGENETIC-RELATIONSHIPS; MAXIMUM-LIKELIHOOD; CRETACEOUS ORIGIN; NUCLEAR GENES; DIVERSIFICATION; EVOLUTION; SUPPORT; BIRDS;
D O I
10.1016/j.ympev.2014.12.003
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Birds are the most diverse tetrapod class, with about 10,000 extant species that represent a remarkable evolutionary radiation in which most taxa arose during a short period of time. There has been a tremendous increase in the amount of molecular data available from birds, and more than two-thirds of these species have some sequence data available. Here we assembled these available sequence data from birds to estimate a large-scale avian phylogeny. We performed an unconstrained maximum likelihood analysis of a sparse supermatrix comprising 22 nuclear loci and seven mitochondrial regions from 6714 species. We inferred a phylogeny with a backbone remarkably similar to that obtained by detailed analyses of multigene datasets, yet with the addition of thousands of more taxa. All orders were monophyletic with generally high support. While most families and genera were well supported, a number of them, especially within the oscine passerines, had little or no support. This likely reflects problems with the circumscription of these genera and families. Our results indicate that the amount of sequence data currently available is sufficient to produce a robust estimate of the avian tree of life using current methods of inference. The availability of a tree that is unconstrained by prior information, with branch lengths that have a direct connection to the underlying data, should be useful for comparative methods, taxonomic revisions, and prioritizing taxa that should be targeted for additional data collection. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:53 / 63
页数:11
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