Skip Navigation



MBE Advance Access published online on February 7, 2003
Molecular Biology and Evolution, doi:10.1093/molbev/msg019
Molecular Biology and Evolution © Society for Molecular Biology and Evolution 2003; all rights reserved
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
20/2/182    most recent
msg019v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Meyer, S.
Right arrow Articles by von Haeseler, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Meyer, S.
Right arrow Articles by von Haeseler, A.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Accepted October 1, 2002
© 2003 Society for Molecular Biology and Evolution

Original Articles

Identifying site specific substitution rates

Sonja Meyer 1 Arndt von Haeseler 2*

1 Max-Planck-Institut für evolutionäre Anthropologie, Leipzig, Germany
2 Heinrich-Heine Universität Düsseldorf, Germany; Forschungszentrum Jülich, Germany

* To whom correspondence should be addressed. E-mail: haeseler{at}cs.uni-duesseldorf.de.


  Abstract

A maximum likelihood framework for estimating site specific substitution rates is presented that does not require any prior assumptions about the rate distribution. We show that the analysis of pairs of positions is sufficient to estimate site specific rates, when the branching pattern of the underlying tree is known. In the abscence of a known topology, we introduce an iterative procedure to estimate the branching pattern, the branch lengths, and site specific substitution rates simultaneously. Simulations show that the evolutionary rate of fast evolving sites can be reliably inferred and that the accuracy of rate estimates depends mainly on the number of sequences in the dataset. Thus, large sets of aligned sequences are necessary for reliable site specific rate estimates. The method is applied to the complete mitochondrial DNA sequence of 53 humans providing a complete picture of the site specific substitution rates in human mitochondrial DNA.

Key Words: sequence evolution, site-specific substitution rates, maximum likelihood, tree reconstruction, human mitochondrial DNA


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 GeneticsHome page
S. Rosset, R. S. Wells, D. F. Soria-Hernanz, C. Tyler-Smith, A. K. Royyuru, D. M. Behar, and and The Genographic Consortium
Maximum-Likelihood Estimation of Site-Specific Mutation Rates in Human Mitochondrial DNA From Partial Phylogenetic Classification
Genetics, November 1, 2008; 180(3): 1511 - 1524.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
A. D. Fernandes and W. R. Atchley
Site-specific evolutionary rates in proteins are better modeled as non-independent and strictly relative
Bioinformatics, October 1, 2008; 24(19): 2177 - 2183.
[Abstract] [Full Text] [PDF]

Home page
 Mol Biol EvolHome page
C. Santos, R. Montiel, B. Sierra, C. Bettencourt, E. Fernandez, L. Alvarez, M. Lima, A. Abade, and M. P. Aluja
Understanding Differences Between Phylogenetic and Pedigree-Derived mtDNA Mutation Rate: A Model Using Families from the Azores Islands (Portugal)
Mol. Biol. Evol., June 1, 2005; 22(6): 1490 - 1505.
[Abstract] [Full Text] [PDF]

Home page
 J. Mol. Diagn.Home page
J. P. Jakupciak, W. Wang, M. E. Markowitz, D. Ally, M. Coble, S. Srivastava, A. Maitra, P. E. Barker, D. Sidransky, and C. D. O'Connell
Mitochondrial DNA as a Cancer Biomarker
J. Mol. Diagn., May 1, 2005; 7(2): 258 - 267.
[Abstract] [Full Text] [PDF]

Home page
 Mol Biol EvolHome page
S. L. Kosakovsky Pond and S. D. W. Frost
A Simple Hierarchical Approach to Modeling Distributions of Substitution Rates
Mol. Biol. Evol., February 1, 2005; 22(2): 223 - 234.
[Abstract] [Full Text] [PDF]

Home page
 Mol Biol EvolHome page
I. Mayrose, D. Graur, N. Ben-Tal, and T. Pupko
Comparison of Site-Specific Rate-Inference Methods for Protein Sequences: Empirical Bayesian Methods Are Superior
Mol. Biol. Evol., September 1, 2004; 21(9): 1781 - 1791.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.