Literature DB >> 15537809

Codon bias signatures, organization of microorganisms in codon space, and lifestyle.

A Carbone1, F Képès, A Zinovyev.   

Abstract

New and simple numerical criteria based on a codon adaptation index are applied to the complete genomic sequences of 80 Eubacteria and 16 Archaea, to infer weak and strong genome tendencies toward content bias, translational bias, and strand bias. These criteria can be applied to all microbial genomes, even those for which little biological information is known, and a codon bias signature, that is the collection of strong biases displayed by a genome, can be automatically derived. A codon bias space, where genomes are identified by their preferred codons, is proposed as a novel formal framework to interpret genomic relationships. Principal component analysis confirms that although GC content has a dominant effect on codon bias space, thermophilic and mesophilic species can be identified and separated by codon preferences. Two more examples concerning lifestyle are studied with linear discriminant analysis: suitable separating functions characterized by sets of preferred codons are provided to discriminate: translationally biased (hyper)thermophiles from mesophiles, and organisms with different respiratory characteristics, aerobic, anaerobic, facultative aerobic and facultative anaerobic. These results suggest that codon bias space might reflect the geometry of a prokaryotic "physiology space." Evolutionary perspectives are noted, numerical criteria and distances among organisms are validated on known cases, and various results and predictions are discussed both on methodological and biological grounds.

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Year:  2004        PMID: 15537809     DOI: 10.1093/molbev/msi040

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


  36 in total

1.  Metabolic and translational efficiency in microbial organisms.

Authors:  Douglas W Raiford; Esley M Heizer; Robert V Miller; Travis E Doom; Michael L Raymer; Dan E Krane
Journal:  J Mol Evol       Date:  2012-04-27       Impact factor: 2.395

2.  Computational prediction of genomic functional cores specific to different microbes.

Authors:  Alessandra Carbone
Journal:  J Mol Evol       Date:  2006-11-10       Impact factor: 2.395

3.  Codon bias is a major factor explaining phage evolution in translationally biased hosts.

Authors:  Alessandra Carbone
Journal:  J Mol Evol       Date:  2008-02-20       Impact factor: 2.395

4.  Variation in the correlation of G + C composition with synonymous codon usage bias among bacteria.

Authors:  Haruo Suzuki; Rintaro Saito; Masaru Tomita
Journal:  EURASIP J Bioinform Syst Biol       Date:  2007

5.  Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria.

Authors:  Betsey Dexter Dyer; Michael J Kahn; Mark D Leblanc
Journal:  Archaea       Date:  2008-12       Impact factor: 3.273

6.  Word-based characterization of promoters involved in human DNA repair pathways.

Authors:  Jens Lichtenberg; Edwin Jacox; Joshua D Welch; Kyle Kurz; Xiaoyu Liang; Mary Qu Yang; Frank Drews; Klaus Ecker; Stephen S Lee; Laura Elnitski; Lonnie R Welch
Journal:  BMC Genomics       Date:  2009-07-07       Impact factor: 3.969

7.  Distinguishing microbial genome fragments based on their composition: evolutionary and comparative genomic perspectives.

Authors:  Scott C Perry; Robert G Beiko
Journal:  Genome Biol Evol       Date:  2010-01-25       Impact factor: 3.416

8.  Translational selection is ubiquitous in prokaryotes.

Authors:  Fran Supek; Nives Skunca; Jelena Repar; Kristian Vlahovicek; Tomislav Smuc
Journal:  PLoS Genet       Date:  2010-06-24       Impact factor: 5.917

9.  Relative codon adaptation: a generic codon bias index for prediction of gene expression.

Authors:  Jesse M Fox; Ivan Erill
Journal:  DNA Res       Date:  2010-05-07       Impact factor: 4.458

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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