Abstract
RIBOSS is a pipeline solving gene annotation problems using reference-guided transcriptome assembly and ribosome profiling. It compares the translational potential of open reading frames within individual transcripts.
Ribosome profiling is routinely used for discovering actively translated ORFs. Standard ribosome profiling involves RNase digestion of ribosome-protected mRNA fragments, followed by sucrose gradient fractionation, and RNA sequencing (RNA-seq). As ribosomes progress along the mRNA codon-by-codon, they generate a characteristic triplet periodicity profile in the footprint data. Triplet periodicity can be used to determine the correct reading frame for the translated ORFs and distinguish true translation events from background noise.
RIBOSS is a Python package consisting of six modules that integrates long- and short-read RNA sequencing data for reference-guided transcriptome assembly with ribosome profiling data to identify and characterise novel translational events beyond annotated regions.
The source code is freely available on GitHub (https://github.com/lcscs12345/riboss). This package and its dependencies can be rapidly installed through the conda environment file using Miniforge3 v24.7.1-2 [86]. The Jupyter notebooks and the results are available on GitHub (https://github.com/lcscs12345/riboss_paper). Raw sequencing datasets for S. enterica are available on NCBI BioProject/SRA (PRJNA609733 and SRX20554650) and ENA (PRJEB51486). Raw ribosome profiling and matched RNA-seq data for A. thaliana and HeLa cells are available on PRJNA759858 and PRJNA316618, respectively.