Literature DB >> 17281312

The Correlation between Recombination Rate and Codon Bias in Yeast Mainly Results from Mutational Bias Associated with Recombination Rather than Hill-Robertson Interference.

T Zhou1, Z H Lu, X Sun.   

Abstract

Codon usage has been reported to be correlated with local recombination rate, which can be explained by two proposed models. In the present study, correspondence analysis was used to investigate the major trends in codon usage variation among S. cerevisiae genes. It was found that the first principle source of codon usage variation in yeast is due to the variance of expressional levels, which is consistent with the previous translational selection model. Moreover, recombination rate is also correlated with the codon pattern, which might be a byproduct of mutational bias associated with recombination rather than the consequence of Hill-Robertson interference. A recent study has analysed the genome sequence, but reached opposite conclusions: the positive correlation between recombination rate and codon bias in yeast mainly results from Hill-Robertson interference. In light of this conflicting result, we have discussed the possible reason and found that the previous analysis was undermined by mistaken assumptions that weak selection acting at expression level led to the correlation between recombination and codon bias.

Entities:  

Year:  2005        PMID: 17281312     DOI: 10.1109/IEMBS.2005.1615542

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

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Journal:  BMC Genomics       Date:  2022-05-30       Impact factor: 4.547

Review 2.  Synonymous Codon Usage Controls Various Molecular Aspects.

Authors:  Eu-Hyun Im; Sun Shim Choi
Journal:  Genomics Inform       Date:  2017-12-29

3.  Analysis of codon usage bias of WRKY transcription factors in Helianthus annuus.

Authors:  Yue Gao; Yan Lu; Yang Song; Lan Jing
Journal:  BMC Genom Data       Date:  2022-06-20

4.  Synonymous codon usage in chloroplast genome of Coffea arabica.

Authors:  Rahul R Nair; Manivasagam B Nandhini; Elango Monalisha; Kavitha Murugan; Thilaga Sethuraman; Sangeetha Nagarajan; Nayani Surya Prakash Rao; Doss Ganesh
Journal:  Bioinformation       Date:  2012-11-13

5.  SCUMBLE: a method for systematic and accurate detection of codon usage bias by maximum likelihood estimation.

Authors:  Morten Kloster; Chao Tang
Journal:  Nucleic Acids Res       Date:  2008-05-21       Impact factor: 16.971

6.  A comparison of synonymous codon usage bias patterns in DNA and RNA virus genomes: quantifying the relative importance of mutational pressure and natural selection.

Authors:  Youhua Chen
Journal:  Biomed Res Int       Date:  2013-10-02       Impact factor: 3.411

  6 in total

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