Codon Adaptation of Plastid Genes

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چکیده

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Codon Adaptation of Plastid Genes

Codon adaptation is codon usage bias that results from selective pressure to increase the translation efficiency of a gene. Codon adaptation has been studied across a wide range of genomes and some early analyses of plastids have shown evidence for codon adaptation in a limited set of highly expressed plastid genes. Here we study codon usage bias across all fully sequenced plastid genomes which...

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Selection at the amino acid level can influence synonymous codon usage: implications for the study of codon adaptation in plastid genes.

A previously employed method that uses the composition of noncoding DNA as the basis of a test for selection between synonymous codons in plastid genes is reevaluated. The test requires the assumption that in the absence of selective differences between synonymous codons the composition of silent sites in coding sequences will match the composition of noncoding sites. It is demonstrated here th...

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Codon adaptation index as a measure of dominating codon bias

UNLABELLED We propose a simple algorithm to detect dominating synonymous codon usage bias in genomes. The algorithm is based on a precise mathematical formulation of the problem that lead us to use the Codon Adaptation Index (CAI) as a 'universal' measure of codon bias. This measure has been previously employed in the specific context of translational bias. With the set of coding sequences as a...

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1 Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada, 2 Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada, 3 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada and 4 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada * Correspon...

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Codon adaptation index is a widely used index for characterizing gene expression in general and translation efficiency in particular. Current computational implementations have a number of problems leading to various systematic biases. I illustrate these problems and provide a better computer implementation to solve these problems. The improved CAI can predict protein production better than CAI...

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ژورنال

عنوان ژورنال: PLOS ONE

سال: 2016

ISSN: 1932-6203

DOI: 10.1371/journal.pone.0154306