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Updated: Dec 1, 2025

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing
Published on: August 7, 2021
HRIBO: high-throughput analysis of bacterial ribosome profiling data
Rick Gelhausen1, Sarah L Svensson2, Kathrin Froschauer2
1Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany.
Motivation:
Ribosome profiling (Ribo-seq) is a powerful approach based on deep sequencing of cDNA libraries generated from ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (50-100 amino acids) that are recalcitrant to many standard biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the automatic processing and analysis of data from bacteria, nor are they focused on the discovery of unannotated open reading frames (ORFs).
Results:
We present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional feature information and expression values. This facilitates the rapid and high-confidence discovery of novel ORFs and their prioritization for functional characterization.
Availability And Implementation:
HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO.

