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Background <p>Synonymous codon usage bias, a significant factor in gene expression and genome evolution, was extensively studied in genomics and molecular biology. Although the genetic code is universal, significant variations in synonymous codon usage have been observed among and within organisms. This bias was linked to various factors, including gene expression levels, tRNA abundance, protein structure, and environmental adaptation. Relative Synonymous Codon Usage (RSCU), a normalized measure, was used to quantify this bias. By analyzing RSCU values, researchers uncovered patterns and trends related to the underlying mechanisms driving codon usage bias.</p> Results <p>We present an R package named <i>RSCUcaller</i> designed for the analysis of coding nucleotide sequences at the level of relative synonymous codon usage (RSCU). The package enables both visualization of data and the performance of advanced statistical analyses. <i>RSCUcaller</i> accepts as input a multi-fasta file containing coding sequences (CDS) and an accompanying description table. Alternatively, the user may provide separate fasta files for each sequence along with the corresponding table. The program merges the provided sequences and calculates RSCU values for each. Implemented visualization features include creating heatmaps and dendrograms based on these heatmaps. Furthermore, the package allows for the presentation of data in the form of histograms. The calculated RSCU values can also be used to create matrices that can be subjected to further analysis by the user. <i>RSCUcaller</i> offers the functionality of correlation analysis between any two organisms. Additionally, to compare the frequency of amino acid occurrence between different groups of sequences, statistical&#xa0;tests have been implemented.</p> Conclusions <p><i>RSCUcaller</i> enabled comparative RSCU analysis between coding sequences of different organisms or individuals of the same species. It facilitated visualization and statistical analysis among codons and user-defined groups. The <i>RSCUcaller</i> package is available at <a href="https://github.com/Mordziarz/RSCUcaller">https://github.com/Mordziarz/RSCUcaller</a> under the GPL-3 license.</p>

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RSCUcaller: an R package for analyzing differences in relative synonymous codon usage (RSCU)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月29日

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  • Mateusz Maździarz,
  • Sebastian Zając,
  • Łukasz Paukszto,
  • Jakub Sawicki

摘要

Background

Synonymous codon usage bias, a significant factor in gene expression and genome evolution, was extensively studied in genomics and molecular biology. Although the genetic code is universal, significant variations in synonymous codon usage have been observed among and within organisms. This bias was linked to various factors, including gene expression levels, tRNA abundance, protein structure, and environmental adaptation. Relative Synonymous Codon Usage (RSCU), a normalized measure, was used to quantify this bias. By analyzing RSCU values, researchers uncovered patterns and trends related to the underlying mechanisms driving codon usage bias.

Results

We present an R package named RSCUcaller designed for the analysis of coding nucleotide sequences at the level of relative synonymous codon usage (RSCU). The package enables both visualization of data and the performance of advanced statistical analyses. RSCUcaller accepts as input a multi-fasta file containing coding sequences (CDS) and an accompanying description table. Alternatively, the user may provide separate fasta files for each sequence along with the corresponding table. The program merges the provided sequences and calculates RSCU values for each. Implemented visualization features include creating heatmaps and dendrograms based on these heatmaps. Furthermore, the package allows for the presentation of data in the form of histograms. The calculated RSCU values can also be used to create matrices that can be subjected to further analysis by the user. RSCUcaller offers the functionality of correlation analysis between any two organisms. Additionally, to compare the frequency of amino acid occurrence between different groups of sequences, statistical tests have been implemented.

Conclusions

RSCUcaller enabled comparative RSCU analysis between coding sequences of different organisms or individuals of the same species. It facilitated visualization and statistical analysis among codons and user-defined groups. The RSCUcaller package is available at https://github.com/Mordziarz/RSCUcaller under the GPL-3 license.