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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: Aug 30, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

Exploration and analysis of R-loop mapping data with RLBase.

Henry E Miller^1,2,3, Daniel Montemayor^4,5, Janet Li^3,6,7

¹Department of Cell Systems and Anatomy, UT Health San Antonio, San Antonio, TX 78229, USA.

Nucleic Acids Research

|August 30, 2022

Summary

This summary is machine-generated.

RLBase is a new database offering the largest collection of RNA-DNA hybrid (R-loop) mapping data. It provides tools to explore, analyze, and download R-loop datasets for researchers.

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Last Updated: Aug 30, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA

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Published on: December 2, 2009

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

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

R-loops, three-stranded nucleic acid structures of RNA and DNA hybrids, are crucial in various cellular processes.
Existing R-loop databases offer limited data access and lack user-friendly analysis tools.
Hundreds of R-loop mapping studies have generated a wealth of public data since 2012.

Purpose of the Study:

To create the most extensive R-loop data resource to date.
To develop a comprehensive framework for R-loop data analysis.
To introduce RLBase, a user-friendly database for exploring and analyzing R-loop data.

Main Methods:

Reprocessing of 810 R-loop mapping samples.
Definition of R-loop consensus regions.
Development of a novel R-loop data analysis framework.

Main Results:

Establishment of the largest R-loop data resource with 810 reprocessed samples.
Identification of R-loop consensus regions.
Creation of RLBase, a database with capabilities for data exploration, analysis, and download.

Conclusions:

RLBase significantly enhances accessibility and usability of R-loop mapping data.
The database facilitates deeper insights into R-loop biology through standardized data and analysis tools.
RLBase serves as a central hub for the R-loop research community.