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Analysis of transcriptome data reveals multifactor constraint on codon usage in Taenia multiceps.

Xing Huang1,2, Jing Xu1, Lin Chen3

  • 1Department of Parasitology, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, China.

BMC Genomics
|April 22, 2017
PubMed
Summary

This study reveals weak codon usage bias in T. multiceps, influenced by natural selection and mutational pressure. Understanding these patterns aids gene discovery and evolutionary studies in T. multiceps.

Keywords:
Codon usage patternEvolutionGenomeNatural selectionTaenia multiceps

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Molecular Biology

Background:

  • Codon usage bias (CUB) is a significant genomic feature observed across many organisms.
  • The synonymous codon usage patterns in T. multiceps have not been previously elucidated.
  • This study addresses the gap in understanding T. multiceps codon usage.

Purpose of the Study:

  • To analyze the codon usage patterns in T. multiceps using transcriptome data.
  • To identify the key factors influencing synonymous codon usage bias in T. multiceps.
  • To provide insights into the evolutionary mechanisms shaping CUB in this species.

Main Methods:

  • Analysis of 8,620 annotated mRNA sequences from T. multiceps.
  • Assessment of nucleotide composition (GC and GC3 content).
  • Evaluation of factors including mutational pressure, natural selection, and gene expression levels.

Main Results:

  • T. multiceps exhibits weak codon bias with mean GC (49.29%) and GC3 (51.43%) content.
  • Natural selection is the primary driver of codon usage variation, with mutational pressure affecting ribosome genes.
  • Twenty-one optimal codons, predominantly GC-rich and ending in G or C, were identified.

Conclusions:

  • This research systematically analyzes T. multiceps codon usage and its influencing factors.
  • The findings represent the first comprehensive study of codon biology in T. multiceps.
  • Understanding T. multiceps CUB is valuable for gene discovery, genetic engineering, and evolutionary research.