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Ann N Y Acad Sci. 2015 Dec;1360:36-53. doi: 10.1111/nyas.12747. Epub 2015 Apr 14.

Estimating phylogenetic trees from genome-scale data.

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Department of Statistics, University of Georgia, Athens, Georgia.
Institute of Bioinformatics, University of Georgia, Athens, Georgia.
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts.
Department of Biochemistry and Molecular Biology & Tianjin Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.


The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data.


anomaly zone; bias-variance dilemma; isochore; recombination; transcriptome

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