RIBOSS leverages ribosome profiling and RNA-seq data (with optional transcriptome assembly) to identify non-canonical ORFs in prokaryotes and eukaryotes. RIBOSS employs a unique comparative approach, assessing the translational potential of non-canonical ORFs relative to annotated ORFs, as described in our paper.
This repository provides Jupyter Notebooks demonstrating RIBOSS's functionality in various scenarios:
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Salmonella enterica serovar Typhimurium: This notebook demonstrates the use of RIBOSS for analysing organisms with incomplete annotations, specifically missing transcription start/termination sites and intercistronic regions. It showcases how RIBOSS can be used to discover novel translational events in these contexts. Alignment files are available on Zenodo.
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Arabidopsis thaliana: This notebook illustrates how to use RIBOSS with a complete reference transcriptome. It provides a typical use case for eukaryotes.
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Homo sapiens: Similar to the Arabidopsis example, this notebook demonstrates RIBOSS usage with a complete human reference transcriptome, demonstrating its applicability to complex eukaryotic transcriptomes.
Further details on benchmarking results and performance evaluation can be found within the Arabidopsis and human notebooks. Additional notebooks detail the preparation of positive controls for benchmarking, specifically human Ribo-Seq ORFs and Araport uORFs.
To visualise the non-canonical ORFs detected, the bigGenePred tracks can be uploaded to the UCSC Genome Browser by pasting the URLs, for example:
track type=bigGenePred name="sORFs" description="RIBOSS top hits" baseColorDefault=genomicCodons bigDataUrl=https://github.com/lcscs12345/riboss_paper/raw/refs/heads/main/results/styphimurium/riboss/ERR9130942_3.riboss.sig.sORF.bb
- Lim, C. S., & Brown, C. M. (2024). RIBOSS detects novel translational events by combining long- and short-read transcriptome and translatome profiling. Brief Bioinform. DOI: 10.1093/bib/bbaf164
- Lim, C.S., Wardell, S.J.T., Kleffmann, T. & Brown, C.M. (2018) The exon-intron gene structure upstream of the initiation codon predicts translation efficiency. Nucleic Acids Res, 46:4575-4591. DOI: 10.1093/nar/gky282