A review of Ribosome profiling and tools used in Ribo-seq data analysis

• Published in: Computational and structural biotechnology journal 2024-12, Vol.23, p.1912-1918
• Main Authors: Limbu, Mingso Sherma, Xiong, Tianze, Wang, Sufang
• Format: Article
• Language: English
• Subjects: Gene expression; Mini-Review; Multi-omics analysis; Ribo-seq; Ribosome profiling; RNA-seq
• ISSN: 2001-0370; 2001-0370
• DOI: 10.1016/j.csbj.2024.04.051

Translational regulation plays the most critical role in gene expression. Ribosome profiling sequencing (Ribo-Seq) is one of the methods to study translation and its regulation. It is a high throughput technology based on deep sequencing, which targets ribosome protected mRNA fragments to produce a ‘global snapshot’ of translatome. There has been an annual increase in the number of publications incorporating Ribo-seq technology. Because of its importance, we used PubMed database to conduct a comprehensive bibliometric analysis on Ribo-seq. We identified 2744 published articles that utilized the term ‘Ribo-seq’ between 2009 and Jan 2024, and 684 articles that contained both Ribo-seq and RNA-seq terms. Based on keywords correlation analysis, we discovered that the primary focus of Ribo-seq articles lies in the areas of translation, transcriptome, and ribosome in the past few years and other topics such as single-cell ribo-seq and crispr within two years, reflecting current areas of interests in Ribo-seq research. The Ribo-seq data analysis applications were also explored and summarized, providing a guide for researchers to choose corresponding tools for different types of analysis. Overall, we highlighted the advances made by Ribo-seq technologies, and the possibilities of utilizing machine learning models to unravel information from multi-omics data. The integration of Ribo-seq with other omics data, such as RNA-seq, is essential to understand the gene expression in complex biological systems.