Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Evolutionary distances in the twilight zone-a rational kernel approach

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
448kB

Item Type:Article
Title:Evolutionary distances in the twilight zone-a rational kernel approach
Creators Name:Schwarz, R.F. and Fletcher, W. and Foerster, F. and Merget, B. and Wolf, M. and Schultz, J. and Markowetz, F.
Abstract:Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets.
Keywords:Algorithms, Amino Acid Sequence, Chlorophyta, Computer Simulation, Intergenic DNA, Likelihood Functions, Markov Chains, Molecular Evolution, Molecular Sequence Data, Phylogeny, Probability, Secondary Protein Structure, Sequence Alignment, Statistical Models
Source:PLoS ONE
ISSN:1932-6203
Publisher:Public Library of Science (U.S.A.)
Volume:5
Number:12
Page Range:e15788
Date:31 December 2010
Official Publication:https://doi.org/10.1371/journal.pone.0015788
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library