Production and R&D Center I of LSS, GenScript (Shanghai) Biotech Co., Ltd., Shanghai, China.
Production and R&D Center I of LSS, GenScript Biotech Corporation, Nanjing, China.
BMC Bioinformatics. 2024 Sep 27;25(1):309. doi: 10.1186/s12859-024-05934-z.
The study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.
Here, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.
Our website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.
研究密码子使用偏好对于理解基因表达、进化和基因设计非常重要,为理解控制基因功能和调控的分子过程提供了关键的见解。密码子使用偏性(CUB)指数是一种有价值的指标,可在不进行大量实验的情况下了解不同生物体中的密码子使用模式。考虑到没有一个适用于所有物种的通用指数,因此非常需要一个支持计算和分析多种密码子优化 CUB 指数的综合平台。
在这里,我们发布了 GenRCA,这是我们之前的稀有密码子分析工具的更新版本,是一个免费且用户友好的网站,可全面评估编码序列的密码子使用偏好。在这项研究中,我们手动审查并实现了多达 31 种密码子偏好指数,涵盖了 65 种表达宿主生物,并支持对多个基因序列进行批处理,旨在改善用户体验并提供更全面、高效的分析。
我们的网站填补了缺乏针对特定物种的 CUB 计算综合工具的空白,使研究人员能够根据 31 个指数的综合列表彻底评估蛋白质表达水平,并进一步指导密码子优化。