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Related Experiment Video

Updated: Jun 11, 2025

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on

Kunjie Fan¹, Yuanyuan Li², Zhiwei Chen²

¹Production and R&D Center I of LSS, GenScript (Shanghai) Biotech Co., Ltd., Shanghai, China.

BMC Bioinformatics

|September 28, 2024

Summary

GenRCA offers a comprehensive website for analyzing codon usage bias (CUB) across 65 organisms. It calculates 31 CUB indices to aid in gene expression and codon optimization.

Keywords:

Codon usage Gene design Protein expression Rare codon analysis

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Codon usage bias (CUB) is crucial for understanding gene expression, evolution, and design.
CUB indices offer insights into codon usage patterns across species.
A universal index for all species is lacking, necessitating comprehensive tools.

Purpose of the Study:

To develop a user-friendly platform for calculating and analyzing multiple CUB indices.
To provide a comprehensive tool for codon optimization.
To enhance the evaluation of codon usage preferences in coding sequences.

Main Methods:

Manually reviewed and implemented 31 codon preference indices.
Developed GenRCA, a website based on the Rare Codon Analysis Tool.
Supported batch processing for multiple gene sequences.

Main Results:

GenRCA provides an all-inclusive evaluation of codon usage preferences.
The platform covers 65 expression host organisms.
Offers a comprehensive and efficient analysis of CUB.

Conclusions:

The GenRCA website addresses the need for species-specific CUB calculation tools.
Enables thorough assessment of protein expression levels using 31 indices.
Guides researchers in codon optimization strategies.