Anota2seq Analysis for Transcriptome-Wide Studies of mRNA Translation.

mRNA translation plays a critical role in determining proteome composition. In health, regulation of mRNA translation facilitates rapid gene expression responses to intra- and extracellular signals. Moreover, dysregulated mRNA translation is a common feature in disease states, including neurological disorders and cancer. Yet, most studies of gene expression focus on analysis of mRNA levels, leaving variations in translational efficiencies largely uncharacterized. Here, we outline procedures to identify mRNA-selective alterations in translational efficiencies on a transcriptome-wide scale using the anota2seq package. Anota2seq compares expression data originating from translated mRNA to data from matched total mRNA to identify changes in translated mRNA not paralleled by corresponding changes in total mRNA (interpreted as changes in translational efficiencies impacting protein levels), congruent changes in total and translated mRNA (interpreted as changes in transcription and/or mRNA stability), and changes in total mRNA not paralleled by corresponding alterations in translated mRNA (interpreted as translational buffering). To illustrate the functionality of the anota2seq analysis package, we demonstrate a detailed analysis using a polysome-profiling data set quantified by RNA sequencing, revealing that estrogen receptor α modulates gene expression via a type of translational buffering termed offsetting. Notably, this anota2seq analysis procedure is also applicable to ribosome-profiling (RiboSeq) data sets and can be adapted to a variety of other data types and experimental contexts. Finally, we provide guidance for extending anota2seq analysis to examine associations between untranslated regions and altered translational efficiencies as well as targeted cellular functions to gain insights into mechanisms and phenotypic consequences of altered mRNA translation. Thus, this step-by-step manual allows users to interrogate selective changes in mRNA translation on a transcriptome-wide scale using the Bioconductor package anota2seq.
(© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)