ORFik: a comprehensive R toolkit for the analysis of translation

Abstract

ABSTRACT•BackgroundWith the rapid growth in the use of high-throughput methods for characterizing translation and the continued expansion of multi-omics, there is a need for back-end functions and streamlined tools for processing, analyzing, and characterizing data produced by these assays.•ResultsHere, we introduce ORFik, a user-friendly R/Bioconductor toolbox for studying translation and its regulation. It extends GenomicRanges from the genome to the transcriptome and implements a framework that integrates data from several sources. ORFik streamlines the steps to process, analyze, and visualize the different steps of translation with a particular focus on initiation and elongation. It accepts high-throughput sequencing data from ribosome profiling to quantify ribosome elongation or RCP-seq/TCP-seq to also quantify ribosome scanning. In addition, ORFik can use CAGE data to accurately determine 5’UTRs and RNA-seq for determining translation relative to RNA abundance. ORFik supports and calculates over 30 different translation-related features and metrics from the literature and can annotate translated regions such as proteins or upstream open reading frames. As a use-case, we demonstrate using ORFik to rapidly annotate the dynamics of 5’ UTRs across different tissues, detect their uORFs, and characterize their scanning and translation in the downstream protein-coding regions.•Availabilityhttp://bioconductor.org/packages/ORFik

Combined nanopore and single-molecule real-time sequencing survey of human betaherpesvirus 5 transcriptome

“…Genome annotations (including ORFs, according to Stern-Ginossar et al, 2012 35 ) were transferred to the Towne var-S genome with metablastr 59 and Liftoff 60 . Data evaluation, comparison of the transcripts, assessing their coding potentials, calculating their Kozak sequence score, carrying out ORF predictions and BLAST comparisons and generating visualizations were carried out with the following R packages: ORFik 61 , Gviz 62 and tidygenomics 57,63 using custom R scripts. Promoter elements and PASs were searched with https:// github.…”

Variation in upstream open reading frames contributes to allelic diversity in protein abundance

“…The alignments were sorted and indexed with samtools 60 version 1.11, and reads that mapped to more than one location in the genome were discarded. uORFs were computationally identified using the R 55 package ORFik 61 . uORFs were identified using the pattern (ATG|TTG|CTG-3n-TAA|TAG|TGA), since translated uORFs can initiate on non-canonical start codons [62][63][64] .…”

“…uORFs were computationally identified using the R(59) package ORFik (65). uORFs were identified using the pattern (ATG|TTG|CTG-3n-TAA|TAG|TGA), since translated uORFs can initiate on non-canonical start codons (66)(67)(68).…”

Small Open Reading Frames, How to Find Them and Determine Their Function

“…Although it is challenging to characterize sORFs and to determine their potential functional role, several studies have now demonstrated the importance of sORFs in different cellular mechanisms (Zacharias et al, 2012;Zhang et al, 2018;Qin et al, 2018;Zheng et al, 2019b) and in the regulation of CDS translation (Calvo et al, 2009;van Heesch et al, 2019). While many of these sORFs function through their interaction with the ribosome and the resulting regulatory effect this enacts, some sORFs can also encode functional peptides.…”

“…Further examples of SEPs and their function is discussed in the last section of this review. Briefly, one can divide sORFs into different categories depending on their characteristics and the available evidence: 1) non-translated sORFs or those with no evidence of translation, simply defined from the genomic sequence (Young et al, 2015) 2) sORFs that are translated, possibly resulting in SEPs (van Heesch et al, 2019;Loughran et al, 2020) 3) sORFs and/or SEPs with a known function (Zacharias et al, 2012;Zhang et al, 2018;Qin et al, 2018;Zheng et al, 2019b;Cloutier et al, 2020). Taken together, this reflects a diversity of sORFs in both healthy and disease conditions and argues for a need to characterize them.…”