Literature DB >> 8078401

Detecting substitution-rate heterogeneity among regions of a nucleotide sequence.

B S Gaut1, B S Weir.   

Abstract

Likelihood-ratio statistics are proposed to test for heterogeneity in nucleotide substitution rate among regions of a DNA sequence. The tests examine three-sequence phylogenies, and two specific tests are proposed: a test to detect rate heterogeneity among genic regions within a sequence, over all evolutionary lineages; and a test to detect rate heterogeneity among regions in a specific evolutionary lineage. Simulations examine the ability of tests to detect a single region that varies in nucleotide substitution rate relative to the remainder of the sequence. A 50-bp region with a fivefold substitution-rate increase can be detected > or = 90% of the time when it is found in all three lineages of the phylogeny, and a 50-bp region of fivefold rate increase can be detected with approximately 70% power when it is found in only one evolutionary lineage. Simulation also examines the effect of transition- and transversion-rate differences. The tests are applied to published DNA sequences. While the tests are powerful, significant results can be difficult to interpret biologically.

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Year:  1994        PMID: 8078401     DOI: 10.1093/oxfordjournals.molbev.a040141

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  7 in total

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3.  A dirichlet process prior for estimating lineage-specific substitution rates.

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Journal:  Mol Biol Evol       Date:  2011-11-02       Impact factor: 16.240

4.  Detecting heterogeneity of substitution along DNA and protein sequences.

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Journal:  Genetics       Date:  1996-05       Impact factor: 4.562

5.  Felsenstein Phylogenetic Likelihood.

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6.  Assessing the applicability of the GTR nucleotide substitution model through simulations.

Authors:  Laurent Gatto; Daniele Catanzaro; Michel C Milinkovitch
Journal:  Evol Bioinform Online       Date:  2007-02-04       Impact factor: 1.625

7.  Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences.

Authors:  Zhang Zhang; Jeffrey P Townsend
Journal:  PLoS Comput Biol       Date:  2009-06-26       Impact factor: 4.475

  7 in total

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