TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data.

Wanting Liu,Tingkai Zheng,Jingjie Jin,Lunping Xiang,Gong Zhang

doi:10.1093/nar/gkx1034

Abstract

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power.

Highlights

According to the central dogma, all proteins are synthesized via translation process
The difficult and challenging experimental procedures of translatome sequencing and its corresponding high cost largely restricted the application of these methods, especially under the current status that the commercialized experimental service is hardly available
Mining valuable information from the published data would help biologists to briefly validate their intuitive ideas using the previous data before investing much time, effort and cost on such direction

Summary

Introduction

According to the central dogma, all proteins are synthesized via translation process. Two major methods of translatome investigations are RNC-seq (sequencing of ribosome-nascent-chain attached mRNA) [6] and Ribo-seq (sequencing of ribosome protected fragments, RPFs) [7] These two methods reflect different aspects of translatome and cannot be mutually replaced. The translatome data serve as an independent reference for proteome research and was proposed as the fourth key resource pillar of Chromosomecentric Human Proteome Project (C-HPP) [9] It has been intensively used in the C-HPP studies (reviewed in [10,11,12]) and can facilitate the discovery of new proteins (the proteins encoded by ‘non-coding RNAs’) [13,14]

Methods

Results

Conclusion