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Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers
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Published on: June 24, 2019

Quantification of codon selection for comparative bacterial genomics.

Adam C Retchless1, Jeffrey G Lawrence

  • 1Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.

BMC Genomics
|July 27, 2011
PubMed
Summary
This summary is machine-generated.

A new statistic, Adaptive Codon Enrichment (ACE), quantifies codon selection bias. ACE accurately predicts gene properties and allows rigorous comparison of codon selection across genes and genomes.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Evolutionary Biology

Background:

  • Existing codon selection statistics lack a model for testing significance of differences between genes.
  • There is a need for improved methods to measure and compare codon selection across genes and genomes.

Purpose of the Study:

  • Introduce a novel statistic, Adaptive Codon Enrichment (ACE), for measuring codon selection.
  • Develop a statistical framework for rigorous comparison of codon selection levels.

Main Methods:

  • ACE models codon usage bias using a probabilistic distribution, comparing preferred codons to stochastic sampling.
  • Expected codon frequencies are derived from broad gene sets to account for nonselective influences like mutational biases.
  • Relative adaptiveness of synonymous codons is determined by comparing observed to expected frequencies.

Main Results:

  • ACE predicts transcript abundance and synonymous substitution rates with accuracy comparable to or exceeding existing metrics.
  • The study identifies optimal reference gene set compositions for ACE accuracy across different genomes, including bacteriophages.
  • ACE can quantify genome-wide codon selection, revealing variations correlated with tRNA gene number, even in bacteria with similar previously measured metrics.

Conclusions:

  • The Adaptive Codon Enrichment (ACE) provides a robust statistical framework for comparing codon selection.
  • ACE enables rigorous within- and between-genome comparisons of codon selection acting on genes.