dc.creator | Paraskevopoulou M.D., Karagkouni D., Vlachos I.S., Tastsoglou S., Hatzigeorgiou A.G. | en |
dc.date.accessioned | 2023-01-31T09:45:43Z | |
dc.date.available | 2023-01-31T09:45:43Z | |
dc.date.issued | 2018 | |
dc.identifier | 10.1038/s41467-018-06046-y | |
dc.identifier.issn | 20411723 | |
dc.identifier.uri | http://hdl.handle.net/11615/77930 | |
dc.description.abstract | Argonaute crosslinking and immunoprecipitation (CLIP) experiments are the most widely used high-throughput methodologies for miRNA targetome characterization. The analysis of Photoactivatable Ribonucleoside-Enhanced (PAR) CLIP methodology focuses on sequence clusters containing T-to-C conversions. Here, we demonstrate for the first time that the non-T-to-C clusters, frequently observed in PAR-CLIP experiments, exhibit functional miRNA-binding events and strong RNA accessibility. This discovery is based on the analysis of an extensive compendium of bona fide miRNA-binding events, and is further supported by numerous miRNA perturbation experiments and structural sequencing data. The incorporation of these previously neglected clusters yields an average of 14% increase in miRNA-target interactions per PAR-CLIP library. Our findings are integrated in microCLIP (www.microrna.gr/microCLIP), a cutting-edge framework that combines deep learning classifiers under a super learning scheme. The increased performance of microCLIP in CLIP-Seq-guided detection of miRNA interactions, uncovers previously elusive regulatory events and miRNA-controlled pathways. © 2018, The Author(s). | en |
dc.language.iso | en | en |
dc.source | Nature Communications | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052975932&doi=10.1038%2fs41467-018-06046-y&partnerID=40&md5=970a58245da4ce391874a71d6617b2d2 | |
dc.subject | messenger RNA | en |
dc.subject | microRNA | en |
dc.subject | microRNA 155 5p | en |
dc.subject | microRNA 16 5p | en |
dc.subject | microRNA 20a 5p | en |
dc.subject | microRNA 24 3p | en |
dc.subject | microRNA 30a 5p | en |
dc.subject | microRNA 7 5p | en |
dc.subject | microRNA 92a 3p | en |
dc.subject | transcriptome | en |
dc.subject | unclassified drug | en |
dc.subject | argonaute protein | en |
dc.subject | cross linking reagent | en |
dc.subject | microRNA | en |
dc.subject | database | en |
dc.subject | experimental study | en |
dc.subject | methodology | en |
dc.subject | RNA | en |
dc.subject | 3' untranslated region | en |
dc.subject | Article | en |
dc.subject | comparative study | en |
dc.subject | controlled study | en |
dc.subject | cross linking | en |
dc.subject | female | en |
dc.subject | gene library | en |
dc.subject | gene mutation | en |
dc.subject | HEK293 cell line | en |
dc.subject | HeLa cell line | en |
dc.subject | human | en |
dc.subject | human cell | en |
dc.subject | immunoprecipitation | en |
dc.subject | mRNA expression level | en |
dc.subject | nucleotide sequence | en |
dc.subject | photoactivatable ribonucleoside enhanced crosslinking and immunoprecipitation | en |
dc.subject | RNA binding | en |
dc.subject | RNA sequence | en |
dc.subject | RNA structure | en |
dc.subject | binding site | en |
dc.subject | breast tumor | en |
dc.subject | chemistry | en |
dc.subject | computer simulation | en |
dc.subject | gene expression profiling | en |
dc.subject | genetics | en |
dc.subject | high throughput sequencing | en |
dc.subject | immunoprecipitation | en |
dc.subject | MCF-7 cell line | en |
dc.subject | metabolism | en |
dc.subject | Paget nipple disease | en |
dc.subject | procedures | en |
dc.subject | reproducibility | en |
dc.subject | sequence analysis | en |
dc.subject | Argonaute Proteins | en |
dc.subject | Binding Sites | en |
dc.subject | Breast Neoplasms | en |
dc.subject | Carcinoma, Ductal, Breast | en |
dc.subject | Computer Simulation | en |
dc.subject | Cross-Linking Reagents | en |
dc.subject | Female | en |
dc.subject | Gene Expression Profiling | en |
dc.subject | Gene Library | en |
dc.subject | High-Throughput Nucleotide Sequencing | en |
dc.subject | Humans | en |
dc.subject | Immunoprecipitation | en |
dc.subject | MCF-7 Cells | en |
dc.subject | MicroRNAs | en |
dc.subject | Reproducibility of Results | en |
dc.subject | Sequence Analysis, RNA | en |
dc.subject | Nature Publishing Group | en |
dc.title | microCLIP super learning framework uncovers functional transcriptome-wide miRNA interactions | en |
dc.type | journalArticle | en |