RiboGalaxy: A browser based platform for the alignment, analysis and visualization of ribosome profiling data

Abstract

Ribosome profiling (ribo-seq) is a technique that uses high-throughput sequencing to reveal the exact locations and densities of translating ribosomes at the entire transcriptome level. The technique has become very popular since its inception in 2009. Yet experimentalists who generate ribo-seq data often have to rely on bioinformaticians to process and analyze their data. We present RiboGalaxy ( http://ribogalaxy.ucc.ie ), a freely available Galaxy-based web server for processing and analyzing ribosome profiling data with the visualization functionality provided by GWIPS-viz ( http://gwips.ucc.ie ). RiboGalaxy offers researchers a suite of tools specifically tailored for processing ribo-seq and corresponding mRNA-seq data. Researchers can take advantage of the published workflows which reduce the multi-step alignment process to a minimum of inputs from the user. Users can then explore their own aligned data as custom tracks in GWIPS-viz and compare their ribosome profiles to existing ribo-seq tracks from published studies. In addition, users can assess the quality of their ribo-seq data, determine the strength of the triplet periodicity signal, generate meta-gene ribosome profiles as well as analyze the relative impact of mRNA sequence features on local read density. RiboGalaxy is accompanied by extensive documentation and tips for helping users. In addition we provide a forum ( http://gwips.ucc.ie/Forum ) where we encourage users to post their questions and feedback to improve the overall RiboGalaxy service.

Keywords: Galaxy; RNA-seq; gene expression; mRNA; protein synthesis; ribo-seq; ribosome footprinting; ribosome profiling; translation; translatomics.

Figure 1.

(A) A sub-codon ribosome footprint along with the open reading frame (ORF) organization for the rat Ldha gene (NM_017025). The footprint reads are color coded (red, green, blue (see the color version of the figure online)) according to the frame alignment (1, 2, 3). The background gray alignments represent mRNA-seq data for the corresponding transcript. In this profile, the majority of the footprint reads are green indicating that they originate from an ORF in the second reading frame. (B) A triplet periodicity plot generated for protein coding regions of the zebrafish transcriptome showing the frequency of footprint 5′ ends mapping across the 3 frames depending on their nucleotide sequence length. (C) A metagene profile of ribosome density relative to the annotated start and stop codons in the zebrafish transcriptome. (D) A RUST metafootprint profile that reveals the influence of mRNA codons on the read density relative to the decoding center (the A-site codon coordinate is shown as 0). The relative entropy (Kullback-Leibler divergence) across these sites is also provided. (E) The relative enrichment of 61 codons in the A-site assessed as the RUST ratio. Codons are grouped by encoded amino acids that are colored according to their physicochemical properties. (F) A ribo-seq profile for the yeast WWM1 gene (YFL010C). The gray bar shows the location of the gene on chromosome VI. The top red panel shows the footprint alignments across the entire WWM1 gene region while the lower red panel is a zoom into the area around the annotated stop codon showing footprint alignments downstream of the annotated stop codon to the next in-frame stop codon. Panel A was generated using the RiboPlot suite on RiboGalaxy using data from the Andreev DE et al. study. Panels B and C were generated using the riboSeqR suite on RiboGalaxy using ribo-seq data from the Bazzini AA et al. study. Panels C and D were generated using the RUST suite on RiboGalaxy using data from the Andreev DE et al. study. Panel F was generated using the RiboTools suite on RiboGalaxy using ribo-seq data from the Baudin-Baillieu A et al. study.