Abstract
BackgroundTranslatomics data, particularly genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. The increasing popularity of these techniques has resulted in multiple algorithms to detect translational regulation, typically distributed in the form of command line tools that require a basic level of programming ability. Additionally, due to the static nature of current software, dynamic transcriptional and translational comparative analysis cannot be adequately achieved. In order to streamline hypothesis generation, investigators must have the ability to manipulate and interact with their data in real-time.ResultsTo address the lack of integration in current software, we introduce RIVET, Ribosomal Investigation and Visualization to Evaluate Translation, an R shiny based graphical user interface for translatomics data exploration and differential analysis. RIVET can analyze either microarray or RNA sequencing data from polysome profiling and ribosome profiling experiments. RIVET provides multiple choices for statistical analysis as well as integration of transcription, translation, and translational efficiency data analytics and the ability to visualize all results dynamically.ConclusionsRIVET is a user-friendly tool designed for bench scientists with little to no programming background. RIVET facilitates the data analysis of translatomics data allowing for dynamic generation of results based on user-defined inputs and publication ready visualization. We expect RIVET will allow for scientists to efficiently make more comprehensive data observations that will lead to more robust hypothesis regarding translational regulation.
Highlights
Translatomics data, genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency
Upon disruption of regulatory mechanisms, gene expression can become disrupted at the level of transcription, cytoplasmic export, RNA stability, RNA localization, and at the level of mRNA translation leading to aberrant protein expression
As polysome profiling allows for an exact enrichment of mRNA corresponding to the number of bound ribosomes, changes that shift the level of translation of a particular mRNA can be examined through density-based segmentation of the polysome fractions [5] (Fig. 1b)
Summary
Translatomics data, genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. Two commonly used approaches to study genome-wide translational control are polysome profiling and ribosome profiling (reviewed in [4]) Polysome profiling captures both transcriptional and translational regulation by isolating cytoplasmic RNA and enriching for actively translating mRNA bound to ribosomes. Enrichment of actively translated mRNA is performed by separation of ribosomebound mRNA using sucrose-gradient ultracentrifugation followed by fractionation of mRNA pertaining to the Ernlund et al BMC Genomics (2018) 19:809 quantity of bound ribosomes followed by RNA-seq or microarray analysis for transcriptional quantitation (Fig. 1b). Ribosome profiling, utilizes a multi-omics approach to capture both transcriptional and translational effects, exclusively quantifies mRNA using an RNA sequencing platform (Fig. 1c). Only a transcription and translational fraction of mRNA can be captured utilizing ribosome profiling [6]
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