Ribo-uORF: a comprehensive data resource of upstream open reading frames (uORFs) based on ribosome profiling. Issue Volume 51:Issue D1(2023) (28th November 2022)

• Record Type: Journal Article
• Authors: Liu, Qi; Peng, Xin; Shen, Mengyuan; Qian, Qian; Xing, Junlian; Li, Chen; Gregory, Richard I
• Is Part Of: Nucleic acids research. Volume 51:Issue D1(2023)
• Page Start: D248
• Page End: D261
• Publication Date: 2022-11-28
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkac1094
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Upstream open reading frames (uORFs) are typically defined as translation sites located within the 5′ untranslated region upstream of the main protein coding sequence (CDS) of messenger RNAs (mRNAs). Although uORFs are prevalent in eukaryotic mRNAs and modulate the translation of downstream CDSs, a comprehensive resource for uORFs is currently lacking. We developed Ribo-uORF (http://rnainformatics.org.cn/RiboUORF ) to serve as a comprehensive functional resource for uORF analysis based on ribosome profiling (Ribo-seq) data. Ribo-uORF currently supports six species: human, mouse, rat, zebrafish, fruit fly, and worm. Ribo-uORF includes 501 554 actively translated uORFs and 107 914 upstream translation initiation sites (uTIS), which were identified from 1495 Ribo-seq and 77 quantitative translation initiation sequencing (QTI-seq) datasets, respectively. We also developed mRNAbrowse to visualize items such as uORFs, cis -regulatory elements, genetic variations, eQTLs, GWAS-based associations, RNA modifications, and RNA editing. Ribo-uORF provides a very intuitive web interface for conveniently browsing, searching, and visualizing uORF data. Finally, uORFscan and UTR5var were developed in Ribo-uORF to precisely identify uORFs and analyze the influence of genetic mutations on uORFs using user-uploaded datasets. Ribo-uORF should greatly facilitate studies of uORFs and their roles in mRNA translation and posttranscriptional control of gene expression. Graphical Abstract: