Pangenome Evidence for Higher Codon Usage Bias and Stronger Translational Selection in Core Genes of Escherichia coli.

Shixiang Sun, Jingfa Xiao, Huiyong Zhang, Zhang Zhang
Author Information
  1. Shixiang Sun: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; University of Chinese Academy of SciencesBeijing, China.
  2. Jingfa Xiao: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
  3. Huiyong Zhang: College of Life Sciences, Henan Agricultural University Zhengzhou, China.
  4. Zhang Zhang: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.

Abstract

Codon usage bias, as a combined interplay from mutation and selection, has been intensively studied in Escherichia coli. However, codon usage analysis in an E. coli pangenome remains unexplored and the relative importance of mutation and selection acting on core genes and strain-specific genes is unknown. Here we perform comprehensive codon usage analyses based on a collection of multiple complete genome sequences of E. coli. Our results show that core genes that are present in all strains have higher codon usage bias than strain-specific genes that are unique to single strains. We further explore the forces in influencing codon usage and investigate the difference of the major force between core and strain-specific genes. Our results demonstrate that although mutation may exert genome-wide influences on codon usage acting similarly in different gene sets, selection dominates as an important force to shape biased codon usage as genes are present in an increased number of strains. Together, our results provide important insights for better understanding genome plasticity and complexity as well as evolutionary mechanisms behind codon usage bias.

Keywords

References

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