Literature DB >> 15823544

Towards a resolution on the inherent methodological weakness of the "effective number of codons used by a gene".

T Banerjee1, S K Gupta, T C Ghosh.   

Abstract

Recently Anders Fuglsang provided a modified way for calculating N(c) when biased discrepancy is present in a gene [Biochem. Biophys. Res. Commun. 317 (2004) 957]. Instead of taking the average codon homozygosity for each synonymous family type (as proposed by Wright) [Gene 87 (1990) 23] Fuglsang considered codon homozygosity of each amino acid individually. Marsashi and Najafabadi [Biochem. Biophys. Res. Commun. 324 (2004) 1] in their recent article demonstrated that the readjustment for overestimation at the level of individual amino acids results in loss of considerable amount of information. Immediately after the publication of Marsashi and Najafabadi, Fuglsang proposed that codon homozygosities can be calculated based on the classical population genetics [Biochem. Biophys. Res. Commun. 327 (2005) 1]. Though Fuglsang's approach is a novel one, it fails when any of the amino acids are absent in a gene. However, the inherent cause of overestimation at the level of individual amino acids is still obscured in the literature. Here in this communication we have presented a general condition where effective number of codons is overestimated using Wright's formula and also we propose a new way to calculate N(c), which is independent of amino acid composition.

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Year:  2005        PMID: 15823544     DOI: 10.1016/j.bbrc.2005.02.150

Source DB:  PubMed          Journal:  Biochem Biophys Res Commun        ISSN: 0006-291X            Impact factor:   3.575


  5 in total

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

Authors:  Anders Fuglsang
Journal:  Genetics       Date:  2005-11-19       Impact factor: 4.562

2.  An entropy-based technique for classifying bacterial chromosomes according to synonymous codon usage.

Authors:  Andrew Hart; Servet Martínez
Journal:  J Math Biol       Date:  2016-10-12       Impact factor: 2.259

3.  A novel framework for evaluating the performance of codon usage bias metrics.

Authors:  Sophia S Liu; Adam J Hockenberry; Michael C Jewett; Luís A N Amaral
Journal:  J R Soc Interface       Date:  2018-01       Impact factor: 4.118

4.  Codon usage is associated with the evolutionary age of genes in metazoan genomes.

Authors:  Yosef Prat; Menachem Fromer; Nathan Linial; Michal Linial
Journal:  BMC Evol Biol       Date:  2009-12-08       Impact factor: 3.260

5.  Unusual codon usage bias in low expression genes of Vibrio cholerae.

Authors:  Surajit Basak; Indranuj Mukherjee; Mayukh Choudhury; Santasabuj Das
Journal:  Bioinformation       Date:  2008-12-31
  5 in total

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