HRIBO: high-throughput analysis of bacterial ribosome profiling data

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 HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO.

[1]  B. Ahmer,et al.  Role of CsrA in stress responses and metabolism important for Salmonella virulence revealed by integrated transcriptomics , 2019, PloS one.

[2]  Lin Yang,et al.  A deep learning-based framework for lung cancer survival analysis with biomarker interpretation , 2020, BMC Bioinformatics.

[3]  Byung-Kwan Cho,et al.  STATR: A simple analysis pipeline of Ribo-Seq in bacteria , 2020, Journal of Microbiology.

[4]  Renan Valieris,et al.  Bioconda: sustainable and comprehensive software distribution for the life sciences , 2018, Nature Methods.

[5]  Peter F. Stadler,et al.  Lacking alignments? The next-generation sequencing mapper segemehl revisited , 2014, Bioinform..

[6]  Emma Dallon,et al.  Ribosome profiling in archaea reveals leaderless translation, novel translational initiation sites, and ribosome pausing at single codon resolution , 2020, Nucleic acids research.

[7]  W. Waegeman,et al.  DeepRibo: a neural network for precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patterns , 2019, Nucleic acids research.

[8]  Thomas J. Hardcastle,et al.  The use of duplex-specific nuclease in ribosome profiling and a user-friendly software package for Ribo-seq data analysis , 2015, RNA.

[9]  Nicholas T. Ingolia,et al.  Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling , 2009, Science.

[10]  Uwe Ohler,et al.  Detecting actively translated open reading frames in ribosome profiling data , 2015, Nature Methods.

[11]  Måns Magnusson,et al.  MultiQC: summarize analysis results for multiple tools and samples in a single report , 2016, Bioinform..

[12]  Xuerui Yang,et al.  RiboMiner: a toolset for mining multi-dimensional features of the translatome with ribosome profiling data , 2020, BMC Bioinformatics.

[13]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[14]  Virag Sharma,et al.  Retapamulin-Assisted Ribosome Profiling Reveals the Alternative Bacterial Proteome. , 2019, Molecular cell.

[15]  Ami S. Bhatt,et al.  MetaRibo-Seq measures translation in microbiomes , 2020, Nature Communications.

[16]  Marcel Martin Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[17]  Tao Liu,et al.  Genome-wide identification and differential analysis of translational initiation , 2017, Nature Communications.

[18]  Sven Rahmann,et al.  Snakemake--a scalable bioinformatics workflow engine. , 2012, Bioinformatics.

[19]  Zhi Xie,et al.  Computational resources for ribosome profiling: from database to Web server and software , 2019, Briefings Bioinform..

[20]  Wei Liu,et al.  Bottom-up precise synthesis of stable platinum dimers on graphene , 2017, Nature Communications.

[21]  Gerben Menschaert,et al.  REPARATION: ribosome profiling assisted (re-)annotation of bacterial genomes , 2017, bioRxiv.

[22]  Weili Wang,et al.  Riborex: fast and flexible identification of differential translation from Ribo‐seq data , 2017, Bioinform..

[23]  Audrey M. Michel,et al.  RiboGalaxy: A browser based platform for the alignment, analysis and visualization of ribosome profiling data , 2016, RNA biology.

[24]  Konrad U. Förstner,et al.  READemption - a tool for the computational analysis of deep-sequencing-based transcriptome data , 2014, Bioinform..

[25]  G. Storz,et al.  Identifying Small Proteins by Ribosome Profiling with Stalled Initiation Complexes , 2019, mBio.

[26]  Mathias Wilhelm,et al.  PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms* , 2019, Molecular & Cellular Proteomics.

[27]  Wei Shi,et al.  featureCounts: an efficient general purpose program for assigning sequence reads to genomic features , 2013, Bioinform..