Literature DB >> 21915654

Interspecific and intragenic differences in codon usage bias among vertebrate myosin heavy-chain genes.

Mikio C Aoi1, Bryan C Rourke.   

Abstract

Synonymous codon usage bias is a broadly observed phenomenon in bacteria, plants, and invertebrates and may result from selection. However, the role of selective pressures in shaping codon bias is still controversial in vertebrates, particularly for mammals. The myosin heavy-chain (MyHC) gene family comprises multiple isoforms of the major force-producing contractile protein in cardiac and skeletal muscles. Slow and fast genes are tandemly arrayed on separate chromosomes, and have distinct patterns of functionality and expression in muscle. We analyze both full-length MyHC genes (~5400 bp) and a larger collection of partial sequences at the 3' end (~500 bp). The MyHC isoforms are an interesting system in which to study codon usage bias because of their length, expression, and critical importance to organismal mobility. Codon bias and GC content differs among MyHC genes with regards to functional type, isoform, and position within the gene. Codon bias even varies by isoform within a species. We find evidence in favor of both chromosomal influences on nucleotide composition and selection against nonsense errors (SANE) acting on codon usage in MyHC genes. Intragenic variation in codon bias and elongation rate is significant, with a strong trend for increasing codon bias and elongation rate towards the 3' end of the gene, although the trend is dependent upon the degeneracy class of the codons. Therefore, patterns of codon usage in MyHC genes are consistent with models supporting SANE as a major force shaping codon usage.

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Year:  2011        PMID: 21915654     DOI: 10.1007/s00239-011-9457-0

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  84 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  1999-03-16       Impact factor: 11.205

2.  Estimating the "effective number of codons": the Wright way of determining codon homozygosity leads to superior estimates.

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Journal:  Genetics       Date:  2005-11-19       Impact factor: 4.562

3.  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

4.  Intragenic spatial patterns of codon usage bias in prokaryotic and eukaryotic genomes.

Authors:  Hong Qin; Wei Biao Wu; Josep M Comeron; Martin Kreitman; Wen-Hsiung Li
Journal:  Genetics       Date:  2004-12       Impact factor: 4.562

5.  Codon bias as a factor in regulating expression via translation rate in the human genome.

Authors:  Yizhar Lavner; Daniel Kotlar
Journal:  Gene       Date:  2004-12-24       Impact factor: 3.688

6.  Measuring and detecting molecular adaptation in codon usage against nonsense errors during protein translation.

Authors:  Michael A Gilchrist; Premal Shah; Russell Zaretzki
Journal:  Genetics       Date:  2009-10-12       Impact factor: 4.562

7.  Identification of a genomic locus containing three slow myosin heavy chain genes in the chicken.

Authors:  Q Chen; L A Moore; M Wick; E Bandman
Journal:  Biochim Biophys Acta       Date:  1997-08-07

8.  Selection on silent sites in the rodent H3 histone gene family.

Authors:  R W DeBry; W F Marzluff
Journal:  Genetics       Date:  1994-09       Impact factor: 4.562

Review 9.  Biased gene conversion and the evolution of mammalian genomic landscapes.

Authors:  Laurent Duret; Nicolas Galtier
Journal:  Annu Rev Genomics Hum Genet       Date:  2009       Impact factor: 8.929

10.  Measuring the prevalence of regional mutation rates: an analysis of silent substitutions in mammals, fungi, and insects.

Authors:  Aleah K Fox; Brian B Tuch; Jeffrey H Chuang
Journal:  BMC Evol Biol       Date:  2008-06-27       Impact factor: 3.260

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  1 in total

1.  Comparative analysis of codon usage bias and codon context patterns between dipteran and hymenopteran sequenced genomes.

Authors:  Susanta K Behura; David W Severson
Journal:  PLoS One       Date:  2012-08-17       Impact factor: 3.240

  1 in total

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