PHYRN: a robust method for phylogenetic analysis of highly divergent sequences

Both multiple sequence alignment and phylogenetic analysis are problematic in the "twilight zone" of sequence similarity (≤ 25% amino acid identity). Herein we explore the accuracy of phylogenetic inference at extreme sequence divergence using a variety of simulated data sets. We evaluate...

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Bibliographic Details
Published in:PloS one 2012-04, Vol.7 (4), p.e34261-e34261
Main Authors: Bhardwaj, Gaurav, Ko, Kyung Dae, Hong, Yoojin, Zhang, Zhenhai, Ho, Ngai Lam, Chintapalli, Sree V, Kline, Lindsay A, Gotlin, Matthew, Hartranft, David Nicholas, Patterson, Morgen E, Dave, Foram, Smith, Evan J, Holmes, Edward C, Patterson, Randen L, van Rossum, Damian B
Format: Article
Language:English
Subjects:
Algorithms
Amino acids
Apoptosis
Biochemistry
Biology
Caenorhabditis elegans
Cladistic analysis
Coffee
Computational Biology - methods
Computer science
Divergence
Evolution, Molecular
Genes
Kinases
Medicine
Methods
Nematodes
Nervous system
Phylogenetics
Phylogeny
Physiology
Proteins
Proteomics
Trees
Twilight
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Summary:Both multiple sequence alignment and phylogenetic analysis are problematic in the "twilight zone" of sequence similarity (≤ 25% amino acid identity). Herein we explore the accuracy of phylogenetic inference at extreme sequence divergence using a variety of simulated data sets. We evaluate four leading multiple sequence alignment (MSA) methods (MAFFT, T-COFFEE, CLUSTAL, and MUSCLE) and six commonly used programs of tree estimation (Distance-based: Neighbor-Joining; Character-based: PhyML, RAxML, GARLI, Maximum Parsimony, and Bayesian) against a novel MSA-independent method (PHYRN) described here. Strikingly, at "midnight zone" genetic distances (~7% pairwise identity and 4.0 gaps per position), PHYRN returns high-resolution phylogenies that outperform traditional approaches. We reason this is due to PHRYN's capability to amplify informative positions, even at the most extreme levels of sequence divergence. We also assess the applicability of the PHYRN algorithm for inferring deep evolutionary relationships in the divergent DANGER protein superfamily, for which PHYRN infers a more robust tree compared to MSA-based approaches. Taken together, these results demonstrate that PHYRN represents a powerful mechanism for mapping uncharted frontiers in highly divergent protein sequence data sets.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0034261