Abstract
BackgroundRibosome profiling has been widely used for studies of translation under a large variety of cellular and physiological contexts. Many of these studies have greatly benefitted from a series of data-mining tools designed for dissection of the translatome from different aspects. However, as the studies of translation advance quickly, the current toolbox still falls in short, and more specialized tools are in urgent need for deeper and more efficient mining of the important and new features of the translation landscapes.ResultsHere, we present RiboMiner, a bioinformatics toolset for mining of multi-dimensional features of the translatome with ribosome profiling data. RiboMiner performs extensive quality assessment of the data and integrates a spectrum of tools for various metagene analyses of the ribosome footprints and for detailed analyses of multiple features related to translation regulation. Visualizations of all the results are available. Many of these analyses have not been provided by previous methods. RiboMiner is highly flexible, as the pipeline could be easily adapted and customized for different scopes and targets of the studies.ConclusionsApplications of RiboMiner on two published datasets did not only reproduced the main results reported before, but also generated novel insights into the translation regulation processes. Therefore, being complementary to the current tools, RiboMiner could be a valuable resource for dissections of the translation landscapes and the translation regulations by mining the ribosome profiling data more comprehensively and with higher resolution. RiboMiner is freely available at https://github.com/xryanglab/RiboMiner and https://pypi.org/project/RiboMiner.
Highlights
Ribosome profiling has been widely used for studies of translation under a large variety of cellular and physiological contexts
RiboPip is focused on the pre-processing of ribosome profiling and RNA-seq data; mQC [35] and Ribo-seQC [36] were mainly designed for quality control of the data; RiboPlot [28] and Shoelaces [34] can be used for quality control and visualization of the data; PausePred [33] was designed to identify pausing motifs; RiboTools [24] is a Galaxy toolbox with functions including detection of translational ambiguities and identification of readthrough events; PROTEOFORMER [23] is a python package for automatic processing of ribosome profiling data, which includes SNP calling, open reading frames (ORFs) assembly and Translation initiation site (TIS) identification; Fig. 1 Major functions of the data analysis tools for ribosome profiling
To showcase the application of RiboMiner for mining of insights into the translation regulation machineries, we used two published datasets, one from the study of eIF5A in translation regulation in yeast (GSE89704) [8] and the other from the study of cotranslation of the aminoacyl-tRNA-synthetase complex (GSE116570) [47], which is used for the Enrichment Analysis
Summary
To showcase the application of RiboMiner for mining of insights into the translation regulation machineries, we used two published datasets, one from the study of eIF5A in translation regulation in yeast (GSE89704) [8] and the other from the study of cotranslation of the aminoacyl-tRNA-synthetase complex (GSE116570) [47], which is used for the Enrichment Analysis. Results showed that the motifs of poly-proline (PPP) and poly-aspartic acid (DDD) were significantly enriched by ribosome upon eIF5A knock-down (Fig. 6a), whereas the ribosome density on poly-lysine was decreased, but with no statistical significance (Fig. 6b). These results are consistent to the original reports in [8] (Fig. 6c). Based on the results of RiboMiner, we reproduced the ribosome stalling event upon eIF5A knock-down as reported by the original study Such stalling was mainly contributed by a subset of genes, and further mining of multiple features of. Human GSE59821 SRR2873530/ SRR2873532 11,557,500/ 12,896,290 29.2 min 22.7 min 20.0 min 3.4 min 75.3 min
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