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

文献类型： 外文期刊

作者： Liu, Qi 1 ; Peng, Xin 1 ; Shen, Mengyuan 1 ; Qian, Qian 1 ; Xing, Junlian 1 ; Li, Chen 1 ; Gregory, Richard, I 5 ;

作者机构： 1.Guangdong Acad Agr Sci, Rice Res Inst, Guangzhou 510640, Peoples R China

2.GuangdongKey Lab New Technol Rice Breeding, Guangzhou 510640, Peoples R China

3.Guangdong Rice Engn Lab, Guangzhou 510640, Peoples R China

4.Key Lab Genet & Breeding High Qual Rice SouthernCh, Guangzhou 510640, Peoples R China

5.Boston Childrens Hosp, Stem Cell Program, Div Hematol Oncol, Boston, MA 02115 USA

6.Harvard Med Sch, Dept Biol Chem & Mol Pharmacol, Boston, MA 02115 USA

7.Harvard Med Sch, Dept Pediat, Boston, MA 02115 USA

8.Harvard Initiat RNA Med, Boston, MA 02115 USA

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

期刊名称：NUCLEIC ACIDS RESEARCH （ 影响因子：19.16； 五年影响因子：17.21 ）

ISSN： 0305-1048

年卷期：

页码：

收录情况： SCI

摘要： Upstream open reading frames (uORFs) are typically defined as translation sites located within the 5 & PRIME; 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 () 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.

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