Ribo-uORF: a comprehensive data resource of upstream open reading frames (uORFs) based on ribosome profiling

Author:

Liu Qi1234,Peng Xin1234,Shen Mengyuan1234ORCID,Qian Qian1234,Xing Junlian1234,Li Chen1234ORCID,Gregory Richard I56789ORCID

Affiliation:

1. Rice Research Institute, Guangdong Academy of Agricultural Sciences , Guangzhou  510640, China

2. Guangdong Key Laboratory of New Technology in Rice Breeding , Guangzhou  510640, China

3. Guangdong Rice Engineering Laboratory , Guangzhou  510640, China

4. Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province) , Guangzhou  510640, China

5. Stem Cell Program, Division of Hematology/Oncology, Boston Children's Hospital , Boston , MA  02115, USA

6. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School , Boston , MA  02115, USA

7. Department of Pediatrics, Harvard Medical School , Boston , MA  02115, USA

8. Harvard Initiative for RNA Medicine , Boston , MA  02115, USA

9. Harvard Stem Cell Institute , Cambridge , MA  02138, USA

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.

Funder

National Natural Science Foundation of China

Special Foundation for Introduction of Scientific Talents of GDAAS

Project of Guangdong Key Laboratory of New Technology in Rice Breeding

NIH

Publisher

Oxford University Press (OUP)

Subject

Genetics

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