Literature DB >> 11420374

The inference of stepwise changes in substitution rates using serial sequence samples.

A Drummond1, R Forsberg, A G Rodrigo.   

Abstract

It is frequently true that molecular sequences do not evolve in a strictly clocklike manner. Instead, substitution rate may vary for a number of reasons, including changes in selection pressure and effective population size, as well as changes in mean generation time. Here we present two new methods for estimating stepwise changes in substitution rates when serially sampled molecular sequences are available. These methods are based on multiple rates with dated tips (MRDT) models and allow different rates to be estimated for different intervals of time. These intervals may correspond to the sampling intervals or to a priori--defined intervals that are not coincident with the times the serial samples are obtained. Two methods for obtaining estimates of multiple rates are described. The first is an extension of the phylogeny-based maximum-likelihood estimation procedure introduced by Rambaut. The second is a new parameterization of the pairwise distance least-squares procedure used by Drummond and Rodrigo. The utility of these methods is demonstrated on a genealogy of HIV sequences obtained at five different sampling times from a single patient over a period of 34 months.

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Year:  2001        PMID: 11420374     DOI: 10.1093/oxfordjournals.molbev.a003920

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


  19 in total

1.  Epidemiology, genetic diversity, and evolution of endemic feline immunodeficiency virus in a population of wild cougars.

Authors:  Roman Biek; Allen G Rodrigo; David Holley; Alexei Drummond; Charles R Anderson; Howard A Ross; Mary Poss
Journal:  J Virol       Date:  2003-09       Impact factor: 5.103

2.  Test of genetical isochronism for longitudinal samples of DNA sequences.

Authors:  Xiaoming Liu; Yun-Xin Fu
Journal:  Genetics       Date:  2007-02-04       Impact factor: 4.562

3.  The perils of plenty: what are we going to do with all these genes?

Authors:  Allen Rodrigo; Frederic Bertels; Joseph Heled; Raphael Noder; Helen Shearman; Peter Tsai
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-12-27       Impact factor: 6.237

4.  Summary statistics of neutral mutations in longitudinal DNA samples.

Authors:  Xiaoming Liu; Yun-Xin Fu
Journal:  Theor Popul Biol       Date:  2008-05-05       Impact factor: 1.570

5.  Pre- versus post-mass extinction divergence of Mesozoic marine reptiles dictated by time-scale dependence of evolutionary rates.

Authors:  Ryosuke Motani; Da-Yong Jiang; Andrea Tintori; Cheng Ji; Jian-Dong Huang
Journal:  Proc Biol Sci       Date:  2017-05-17       Impact factor: 5.349

6.  Molecular footprint of drug-selective pressure in a human immunodeficiency virus transmission chain.

Authors:  Philippe Lemey; Inge Derdelinckx; Andrew Rambaut; Kristel Van Laethem; Stephanie Dumont; Steve Vermeulen; Eric Van Wijngaerden; Anne-Mieke Vandamme
Journal:  J Virol       Date:  2005-09       Impact factor: 5.103

7.  The evolutionary rate dynamically tracks changes in HIV-1 epidemics: application of a simple method for optimizing the evolutionary rate in phylogenetic trees with longitudinal data.

Authors:  Irina Maljkovic Berry; Gayathri Athreya; Moulik Kothari; Marcus Daniels; William J Bruno; Bette Korber; Carla Kuiken; Ruy M Ribeiro; Thomas Leitner
Journal:  Epidemics       Date:  2009-11-12       Impact factor: 4.396

Review 8.  Cancer as an evolutionary and ecological process.

Authors:  Lauren M F Merlo; John W Pepper; Brian J Reid; Carlo C Maley
Journal:  Nat Rev Cancer       Date:  2006-11-16       Impact factor: 60.716

9.  Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

Authors:  Alexei J Drummond; Geoff K Nicholls; Allen G Rodrigo; Wiremu Solomon
Journal:  Genetics       Date:  2002-07       Impact factor: 4.562

10.  Unequal evolutionary rates in the human immunodeficiency virus type 1 (HIV-1) pandemic: the evolutionary rate of HIV-1 slows down when the epidemic rate increases.

Authors:  Irina Maljkovic Berry; Ruy Ribeiro; Moulik Kothari; Gayathri Athreya; Marcus Daniels; Ha Youn Lee; William Bruno; Thomas Leitner
Journal:  J Virol       Date:  2007-07-18       Impact factor: 5.103

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