Translatome Database

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data
Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie; Zhang, Gong *
Nucleic Acids Research (2017) in press.

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 ( which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 3,288 Ribo-seq, 40 RNC-seq and their 2,415 corresponding mRNA-seq datasets in 23 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis and the corresponding GO enrichment analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices TR, EVI and TE can be calculated for single sample to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. RFP coverage analysis pilings up the reads along any specified mRNA to visualize. Principal component analysis visualize the similarity of multiple samples. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyses. TranslatomeDB also allows users to upload their own mRNA-seq, RNC-seq and Ribo-seq datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is comprehensive platform providing friendly user experience on translatome research across the studies, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power.