Literature DB >> 19116280

Genome rhetoric and the emergence of compositional bias.

Kalin Vetsigian1, Nigel Goldenfeld.   

Abstract

Genomes exhibit diverse patterns of species-specific GC content, GC and AT skews, codon bias, and mutation bias. Despite intensive investigations and the rapid accumulation of sequence data, the causes of these a priori different genome biases have not been agreed on and seem multifactorial and idiosyncratic. We show that these biases can arise generically from an instability of the coevolutionary dynamics between genome composition and resource allocation for translation, transcription, and replication. Thus, we offer a unifying framework for understanding and analyzing different genome biases. We develop a test of multistability of nucleotide composition of completely sequenced genomes and reveal a bistability for Borrelia burgdorferi, a genome with pronounced replication-related biases. These results indicate that evolution generates rhetoric, it improves the efficiency of the genome's communication with the cell without modifying the message, and this leads to bias.

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Mesh:

Year:  2008        PMID: 19116280      PMCID: PMC2629207          DOI: 10.1073/pnas.0810122106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  25 in total

Review 1.  Asymmetric substitution patterns: a review of possible underlying mutational or selective mechanisms.

Authors:  A C Frank; J R Lobry
Journal:  Gene       Date:  1999-09-30       Impact factor: 3.688

Review 2.  Compositional bias in DNA.

Authors:  C Gautier
Journal:  Curr Opin Genet Dev       Date:  2000-12       Impact factor: 5.578

3.  The impact of message mutation on the fitness of a genetic code.

Authors:  Guy Sella; David H Ardell
Journal:  J Mol Evol       Date:  2002-05       Impact factor: 2.395

4.  Codon usage between genomes is constrained by genome-wide mutational processes.

Authors:  Swaine L Chen; William Lee; Alison K Hottes; Lucy Shapiro; Harley H McAdams
Journal:  Proc Natl Acad Sci U S A       Date:  2004-02-27       Impact factor: 11.205

5.  Coevolution of codon usage and transfer RNA abundance.

Authors:  M Bulmer
Journal:  Nature       Date:  1987 Feb 19-25       Impact factor: 49.962

6.  The guanine and cytosine content of genomic DNA and bacterial evolution.

Authors:  A Muto; S Osawa
Journal:  Proc Natl Acad Sci U S A       Date:  1987-01       Impact factor: 11.205

7.  Codon usage in bacteria: correlation with gene expressivity.

Authors:  M Gouy; C Gautier
Journal:  Nucleic Acids Res       Date:  1982-11-25       Impact factor: 16.971

Review 8.  Codon catalog usage and the genome hypothesis.

Authors:  R Grantham; C Gautier; M Gouy; R Mercier; A Pavé
Journal:  Nucleic Acids Res       Date:  1980-01-11       Impact factor: 16.971

9.  A simple model based on mutation and selection explains trends in codon and amino-acid usage and GC composition within and across genomes.

Authors:  R D Knight; S J Freeland; L F Landweber
Journal:  Genome Biol       Date:  2001-03-22       Impact factor: 13.583

10.  DNA asymmetric strand bias affects the amino acid composition of mitochondrial proteins.

Authors:  Xiang Jia Min; Donal A Hickey
Journal:  DNA Res       Date:  2007-11-01       Impact factor: 4.458

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  18 in total

1.  Nucleotide bias of DCL and AGO in plant anti-virus gene silencing.

Authors:  Thien Ho; Liang Wang; Linfeng Huang; Zhigang Li; Denise W Pallett; Tamas Dalmay; Kazusato Ohshima; John A Walsh; Hui Wang
Journal:  Protein Cell       Date:  2010-10-07       Impact factor: 14.870

2.  Codon Usage of Hepatitis E Viruses: A Comprehensive Analysis.

Authors:  Bingzhe Li; Han Wu; Ziping Miao; Linjie Hu; Lu Zhou; Yihan Lu
Journal:  Front Microbiol       Date:  2022-06-21       Impact factor: 6.064

3.  Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC).

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Journal:  PeerJ       Date:  2022-06-23       Impact factor: 3.061

4.  Analysis of intra-genomic GC content homogeneity within prokaryotes.

Authors:  Jon Bohlin; Lars Snipen; Simon P Hardy; Anja B Kristoffersen; Karin Lagesen; Torunn Dønsvik; Eystein Skjerve; David W Ussery
Journal:  BMC Genomics       Date:  2010-08-06       Impact factor: 3.969

5.  Effect of correlated tRNA abundances on translation errors and evolution of codon usage bias.

Authors:  Premal Shah; Michael A Gilchrist
Journal:  PLoS Genet       Date:  2010-09-16       Impact factor: 5.917

6.  Genomic taxonomy of Vibrios.

Authors:  Cristiane C Thompson; Ana Carolina P Vicente; Rangel C Souza; Ana Tereza R Vasconcelos; Tammi Vesth; Nelson Alves; David W Ussery; Tetsuya Iida; Fabiano L Thompson
Journal:  BMC Evol Biol       Date:  2009-10-27       Impact factor: 3.260

7.  Enhanced nucleotide analysis enables the quantification of deoxynucleotides in plants and algae revealing connections between nucleoside and deoxynucleoside metabolism.

Authors:  Henryk Straube; Markus Niehaus; Sarah Zwittian; Claus-Peter Witte; Marco Herde
Journal:  Plant Cell       Date:  2021-04-17       Impact factor: 11.277

8.  Pandemic influenza A virus codon usage revisited: biases, adaptation and implications for vaccine strain development.

Authors:  Natalia Goñi; Andrés Iriarte; Victoria Comas; Martín Soñora; Pilar Moreno; Gonzalo Moratorio; Héctor Musto; Juan Cristina
Journal:  Virol J       Date:  2012-11-08       Impact factor: 4.099

9.  The evolutionary dynamics of tRNA-gene copy number and codon-use in E. coli.

Authors:  Michael J McDonald; Chih-Hung Chou; Krishna B S Swamy; Hsien-Da Huang; Jun-Yi Leu
Journal:  BMC Evol Biol       Date:  2015-08-19       Impact factor: 3.260

10.  Revelation of Influencing Factors in Overall Codon Usage Bias of Equine Influenza Viruses.

Authors:  Naveen Kumar; Bidhan Chandra Bera; Benjamin D Greenbaum; Sandeep Bhatia; Richa Sood; Pavulraj Selvaraj; Taruna Anand; Bhupendra Nath Tripathi; Nitin Virmani
Journal:  PLoS One       Date:  2016-04-27       Impact factor: 3.240

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