Literature DB >> 15466418

On the evolution of codon volatility.

Jianzhi Zhang1.   

Abstract

Volatility of a codon is defined as the probability that a random point mutation in the codon generates a nonsynonymous change. It has been proposed that higher-than-expected mean codon volatility of a gene indicates that positive selection for nonsynonymous changes has acted on the gene in the recent past. I show that strong frequency-dependent selection (minority advantage) in large populations can increase codon volatility slightly, whereas directional positive selection has no effect on volatility. Factors unrelated to positive selection, such as expression-related or GC-content-related codon usage bias, also affect volatility. These and other considerations suggest that codon volatility has only limited utility for detecting positive selection at the DNA sequence level.

Mesh:

Substances:

Year:  2004        PMID: 15466418      PMCID: PMC1448886          DOI: 10.1534/genetics.104.034884

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  12 in total

1.  The origins of genome complexity.

Authors:  Michael Lynch; John S Conery
Journal:  Science       Date:  2003-11-21       Impact factor: 47.728

2.  The effect of expression levels on codon usage in Plasmodium falciparum.

Authors:  L Peixoto; V Fernández; H Musto
Journal:  Parasitology       Date:  2004-03       Impact factor: 3.234

3.  Nucleotide substitution at major histocompatibility complex class II loci: evidence for overdominant selection.

Authors:  A L Hughes; M Nei
Journal:  Proc Natl Acad Sci U S A       Date:  1989-02       Impact factor: 11.205

4.  Theoretical foundation of population genetics at the molecular level.

Authors:  M Kimura
Journal:  Theor Popul Biol       Date:  1971-06       Impact factor: 1.570

5.  Detecting selection using a single genome sequence of M. tuberculosis and P. falciparum.

Authors:  Joshua B Plotkin; Jonathan Dushoff; Hunter B Fraser
Journal:  Nature       Date:  2004-04-29       Impact factor: 49.962

6.  Slow molecular clocks in Old World monkeys, apes, and humans.

Authors:  Soojin Yi; Darrell L Ellsworth; Wen-Hsiung Li
Journal:  Mol Biol Evol       Date:  2002-12       Impact factor: 16.240

Review 7.  Codon usage patterns in Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Drosophila melanogaster and Homo sapiens; a review of the considerable within-species diversity.

Authors:  P M Sharp; E Cowe; D G Higgins; D C Shields; K H Wolfe; F Wright
Journal:  Nucleic Acids Res       Date:  1988-09-12       Impact factor: 16.971

8.  Pattern of nucleotide substitution at major histocompatibility complex class I loci reveals overdominant selection.

Authors:  A L Hughes; M Nei
Journal:  Nature       Date:  1988-09-08       Impact factor: 49.962

9.  Codon bias and frequency-dependent selection on the hemagglutinin epitopes of influenza A virus.

Authors:  Joshua B Plotkin; Jonathan Dushoff
Journal:  Proc Natl Acad Sci U S A       Date:  2003-05-14       Impact factor: 11.205

10.  Divergence time and population size in the lineage leading to modern humans.

Authors:  N Takahata; Y Satta; J Klein
Journal:  Theor Popul Biol       Date:  1995-10       Impact factor: 1.570

View more
  9 in total

1.  Positive selection on nucleotide substitutions and indels in accessory gland proteins of the Drosophila pseudoobscura subgroup.

Authors:  Sheri Dixon Schully; Michael E Hellberg
Journal:  J Mol Evol       Date:  2006-04-28       Impact factor: 2.395

2.  Codon usage and selection on proteins.

Authors:  Joshua B Plotkin; Jonathan Dushoff; Michael M Desai; Hunter B Fraser
Journal:  J Mol Evol       Date:  2006-10-14       Impact factor: 2.395

3.  Adaptive Evolution Hotspots at the GC-Extremes of the Human Genome: Evidence for Two Functionally Distinct Pathways of Positive Selection.

Authors:  Clara S M Tang; Richard J Epstein
Journal:  Adv Bioinformatics       Date:  2010-05-03

4.  Microbial evolution. Global epistasis makes adaptation predictable despite sequence-level stochasticity.

Authors:  Sergey Kryazhimskiy; Daniel P Rice; Elizabeth R Jerison; Michael M Desai
Journal:  Science       Date:  2014-06-27       Impact factor: 47.728

5.  In Arabidopsis thaliana codon volatility scores reflect GC3 composition rather than selective pressure.

Authors:  Mary J O'Connell; Aisling M Doyle; Thomas E Juenger; Mark T A Donoghue; Channa Keshavaiah; Reetu Tuteja; Charles Spillane
Journal:  BMC Res Notes       Date:  2012-07-17

6.  Evolution of genetic potential.

Authors:  Lauren Ancel Meyers; Fredric D Ancel; Michael Lachmann
Journal:  PLoS Comput Biol       Date:  2005-08-26       Impact factor: 4.475

7.  Chikungunya Virus Vaccine Candidates with Decreased Mutational Robustness Are Attenuated In Vivo and Have Compromised Transmissibility.

Authors:  Lucía Carrau; Veronica V Rezelj; María G Noval; Laura I Levi; Daniela Megrian; Herve Blanc; James Weger-Lucarelli; Gonzalo Moratorio; Kenneth A Stapleford; Marco Vignuzzi
Journal:  J Virol       Date:  2019-08-28       Impact factor: 5.103

8.  Analysis of the Contribution of Intrinsic Disorder in Shaping Potyvirus Genetic Diversity.

Authors:  Guillaume Lafforgue; Thierry Michon; Justine Charon
Journal:  Viruses       Date:  2022-09-03       Impact factor: 5.818

9.  [Chromosomal localization and molecular organization of human genomic fragment containing TNF/LT locus in transgenic mice].

Authors:  A R Galimov; A A Kruglov; N L Bol'sheva; O Iu Iurkevich; D Ia Lipin'sh; I A Mufazalov; D V Kuprash; S A Nedospasov
Journal:  Mol Biol (Mosk)       Date:  2008 Jul-Aug
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.