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A new and updated resource for codon usage tables.

John Athey1, Aikaterini Alexaki1, Ekaterina Osipova2

  • 1Division of Plasma Protein Therapeutics, Office of Tissue and Advanced Therapies, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, USA.

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|September 4, 2017
PubMed
Summary
This summary is machine-generated.

A new database, HIVE-CUTs, offers comprehensive and up-to-date codon usage tables for all organisms with available sequencing data. This resource aids in codon optimization for recombinant gene technologies and facilitates evolutionary and translation studies.

Keywords:
Codon optimizationCodon usage biasRecombinant protein therapeuticsTranslational kinetics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • The genetic code's degeneracy allows multiple codons for one amino acid, with varying frequencies across organisms.
  • Codon usage bias impacts protein expression, structure, and function, influencing recombinant gene technologies.
  • Accurate codon usage data is crucial for codon optimization, evolutionary studies, and understanding translation dynamics.

Purpose of the Study:

  • To develop a comprehensive and up-to-date database of codon usage tables for all organisms with available sequencing data.
  • To address limitations of existing resources, including scope and accuracy.
  • To provide new functionalities for analyzing and comparing codon usage patterns.

Main Methods:

  • Leveraged GenBank and NCBI's RefSeq database for extensive sequencing data.
  • Developed the High-performance Integrated Virtual Environment-Codon Usage Tables (HIVE-CUTs) database.
  • Implemented features for viewing and comparing codon usage across organisms and clades using graphical representations and indices.

Main Results:

  • Created HIVE-CUTs, a comprehensive database encompassing codon usage for all organisms with public sequencing data.
  • HIVE-CUTs surpasses existing databases in scope and accuracy.
  • The database offers advanced functionalities for comparative codon usage analysis and is routinely updated.

Conclusions:

  • HIVE-CUTs will significantly aid recombinant gene technologies, drug development, and diverse biological research areas.
  • The database facilitates effective codon optimization and review of recombinant products.
  • It serves as a valuable tool for evolutionary, translation, and co-evolution studies.