Literature DB >> 10075995

Proteome composition and codon usage in spirochaetes: species-specific and DNA strand-specific mutational biases.

B Lafay1, A T Lloyd, M J McLean, K M Devine, P M Sharp, K H Wolfe.   

Abstract

The genomes of the spirochaetes Borrelia burgdorferi and Treponema pallidum show strong strand-specific skews in nucleotide composition, with the leading strand in replication being richer in G and T than the lagging strand in both species. This mutation bias results in codon usage and amino acid composition patterns that are significantly different between genes encoded on the two strands, in both species. There are also substantial differences between the species, with T.pallidum having a much higher G+C content than B. burgdorferi. These changes in amino acid and codon compositions represent neutral sequence change that has been caused by strong strand- and species-specific mutation pressures. Genes that have been relocated between the leading and lagging strands since B. burgdorferi and T.pallidum diverged from a common ancestor now show codon and amino acid compositions typical of their current locations. There is no evidence that translational selection operates on codon usage in highly expressed genes in these species, and the primary influence on codon usage is whether a gene is transcribed in the same direction as replication, or opposite to it. The dnaA gene in both species has codon usage patterns distinctive of a lagging strand gene, indicating that the origin of replication lies downstream of this gene, possibly within dnaN. Our findings strongly suggest that gene-finding algorithms that ignore variability within the genome may be flawed.

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Year:  1999        PMID: 10075995      PMCID: PMC148367          DOI: 10.1093/nar/27.7.1642

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  39 in total

1.  A phylogenomic study of DNA repair genes, proteins, and processes.

Authors:  J A Eisen; P C Hanawalt
Journal:  Mutat Res       Date:  1999-12-07       Impact factor: 2.433

2.  Horizontal gene transfer in bacterial and archaeal complete genomes.

Authors:  S Garcia-Vallvé; A Romeu; J Palau
Journal:  Genome Res       Date:  2000-11       Impact factor: 9.043

3.  Use and misuse of correspondence analysis in codon usage studies.

Authors:  Guy Perrière; Jean Thioulouse
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

4.  Complete nucleotide sequence of Klebsiella phage P13 and prediction of an EPS depolymerase gene.

Authors:  Anqi Shang; Yang Liu; Jianlei Wang; Zhaolan Mo; Guiyang Li; Haijin Mou
Journal:  Virus Genes       Date:  2014-11-13       Impact factor: 2.332

Review 5.  Forces that influence the evolution of codon bias.

Authors:  Paul M Sharp; Laura R Emery; Kai Zeng
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

6.  Similar compositional biases are caused by very different mutational effects.

Authors:  Eduardo P C Rocha; Marie Touchon; Edward J Feil
Journal:  Genome Res       Date:  2006-10-26       Impact factor: 9.043

7.  Evolutionary constraints on codon and amino acid usage in two strains of human pathogenic actinobacteria Tropheryma whipplei.

Authors:  Sabyasachi Das; Sandip Paul; Chitra Dutta
Journal:  J Mol Evol       Date:  2006-03-22       Impact factor: 2.395

8.  Codon usages of genes on chromosome, and surprisingly, genes in plasmid are primarily affected by strand-specific mutational biases in Lawsonia intracellularis.

Authors:  Feng-Biao Guo; Jian-Bo Yuan
Journal:  DNA Res       Date:  2009-02-15       Impact factor: 4.458

9.  Measure of synonymous codon usage diversity among genes in bacteria.

Authors:  Haruo Suzuki; Rintaro Saito; Masaru Tomita
Journal:  BMC Bioinformatics       Date:  2009-06-01       Impact factor: 3.169

10.  Comparison of correspondence analysis methods for synonymous codon usage in bacteria.

Authors:  Haruo Suzuki; Celeste J Brown; Larry J Forney; Eva M Top
Journal:  DNA Res       Date:  2008-10-21       Impact factor: 4.458

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