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Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...

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Related Experiment Video

Updated: Jan 16, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

Published on: February 18, 2022

ribofootPrinter: A precision python toolbox for analysis of ribosome profiling data.

Kyra Kerkhofs¹, Nicholas R Guydosh¹

¹Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, 20892.

Biorxiv : the Preprint Server for Biology

|September 26, 2025

Summary

This summary is machine-generated.

Ribosome profiling analyzes cellular translation. A new Python tool, ribofootPrinter, simplifies analysis of ribosome profiling data and related sequencing experiments for researchers.

Keywords:

MANE Ribosome profiling dORF iORF metagene multimapping pausing python reading frame uORF

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Last Updated: Jan 16, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

Published on: February 18, 2022

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing

Published on: August 7, 2021

Eukaryotic Polyribosome Profile Analysis

Published on: June 15, 2010

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Ribosome profiling is crucial for understanding mRNA translation efficiency and ribosome dynamics.
Existing software for ribosome profiling analysis can be complex and difficult to customize.
Translation outside coding regions has significant regulatory implications.

Purpose of the Study:

To introduce ribofootPrinter, an accessible and adaptable Python toolkit for analyzing ribosome profiling and small RNA sequencing data.
To simplify complex data analysis pipelines for researchers with specialized needs.
To enhance the interpretation of translational changes, especially those occurring outside coding sequences.

Main Methods:

Development of a Python suite (ribofootPrinter) for ribosome profiling data analysis.
Utilizing a simplified transcriptome for intuitive read alignment.
Incorporating multiple normalization options for meta-analysis.
Generating multimapper identifier files to pinpoint ambiguous alignment regions.

Main Results:

ribofootPrinter provides a user-friendly interface for sophisticated analysis of ribosome profiling data.
The tool facilitates accurate mapping of short reads to a simplified transcriptome.
Normalization options aid in the interpretation of translational events, including those in non-coding regions.

Conclusions:

ribofootPrinter offers a powerful yet accessible solution for ribosome profiling data analysis.
The toolkit is designed for adaptability, meeting diverse research requirements.
This approach enhances the understanding of cellular translational control mechanisms.