Back

O-Glycosylated RNA Identification and Site-specific Prediction by Solid-phase Chemoenzymatic TnORNA method and PONglyRNA tool

Li, J.; Wang, L.; Chen, Y.; Zhang, S.; Wen, Z.; Zhen, X.; Zhang, H.; Zhou, Y.; Yang, S.

2024-06-22 cancer biology
10.1101/2024.06.18.599663 bioRxiv
Show abstract

Recent studies have shown that the cell surface undergoes post-transcriptional modification by N-linked glycosylation. However, the question of whether RNA can be glycosylated by O-glycans remains to be explored. The presence of O-glycosylation in cells is indirectly revealed by the presence of O-glycans on RNAs following treatment with O-glycoproteases. To identify RNA O-glycosylation, we have developed a chemoenzymatic method for capturing and enriching O-glycosylated RNA (O-glycoRNA) using covalent immobilization on a solid support. GalNAcEXO selectively releases Tn-containing O-glycosylated RNAs (TnORNA). Using this method and SPCgRNA, we compared the expression of O-glycoRNAs and N-glycoRNAs in pancreatic cancer cell lines and tissues. We found that glycosylated miR-103a-3p, miR-122-5p, and miR-4492 regulate pancreatic cancer cell growth and proliferation through the PI3K-Akt pathway. In vitro assays and PDAC tissue analysis confirmed the potential regulatory roles of Tn-O-glycosylated miRNAs in pancreatic tumor growth and metastasis. Furthermore, a significant number (131) of miRNAs carrying both N- and Tn-O-glycosylation were identified, indicating the co-occurrence of N-linked and O-linked glycosylation on small RNAs. We have also developed PONglyRNA, an online bioinformatic tool for the site-specific prediction of RNA glycosylation. PONglyRNA identifies glycosylation motifs based on RNA sequence and has been validated using our glycoRNA data. In conclusion, this study establishes robust experimental and computational tools for identifying O-linked glycoRNAs. Additionally, it uncovers the novel role of glycosylation in PDAC development and progression through altered glycosylation of oncogenic miRNAs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/599663v1_ufig1.gif" ALT="Figure 1"> View larger version (72K): org.highwire.dtl.DTLVardef@199511corg.highwire.dtl.DTLVardef@9c3338org.highwire.dtl.DTLVardef@e6d315org.highwire.dtl.DTLVardef@2c1fc1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 13 journals account for 50% of the predicted probability mass.

1
Nucleic Acids Research
1281 papers in training set
Top 2%
7.8%
2
Scientific Reports
3612 papers in training set
Top 9%
7.2%
3
RNA Biology
78 papers in training set
Top 0.1%
6.7%
4
Molecular Cancer
16 papers in training set
Top 0.1%
5.4%
5
Nature Communications
5641 papers in training set
Top 29%
4.8%
6
NAR Cancer
37 papers in training set
Top 0.1%
2.8%
7
Cell Reports
1498 papers in training set
Top 14%
2.6%
8
Molecular Therapy - Nucleic Acids
25 papers in training set
Top 0.2%
2.6%
9
RSC Chemical Biology
39 papers in training set
Top 0.2%
2.6%
10
ACS Chemical Biology
167 papers in training set
Top 1%
2.4%
11
Cell Chemical Biology
94 papers in training set
Top 0.6%
2.4%
12
iScience
1154 papers in training set
Top 11%
2.4%
13
Journal of Biological Chemistry
690 papers in training set
Top 4%
2.1%
50% of probability mass above
14
ACS Omega
105 papers in training set
Top 1%
1.9%
15
PLOS ONE
5266 papers in training set
Top 48%
1.7%
16
Communications Biology
993 papers in training set
Top 14%
1.7%
17
Genomics, Proteomics & Bioinformatics
172 papers in training set
Top 1%
1.7%
18
Cancer Research Communications
51 papers in training set
Top 0.9%
1.7%
19
Genome Biology
637 papers in training set
Top 6%
1.7%
20
Journal of Proteome Research
234 papers in training set
Top 1%
1.5%
21
International Journal of Molecular Sciences
494 papers in training set
Top 10%
1.3%
22
Molecular Therapy Nucleic Acids
39 papers in training set
Top 0.7%
1.1%
23
Analytical Chemistry
218 papers in training set
Top 2%
1.1%
24
Cancers
213 papers in training set
Top 4%
1.0%
25
RNA
189 papers in training set
Top 1%
1.0%
26
Molecular & Cellular Proteomics
158 papers in training set
Top 1%
1.0%
27
Science Advances
1243 papers in training set
Top 28%
1.0%
28
Cell Reports Methods
165 papers in training set
Top 3%
1.0%
29
Computational and Structural Biotechnology Journal
242 papers in training set
Top 6%
0.9%
30
Epigenetics
50 papers in training set
Top 0.7%
0.8%