title: microTSS: accurate microRNA transcription start site identification reveals a significant number of divergent pri-miRNAs.
abstract: A large fraction of microRNAs (miRNAs) are derived from intergenic non-coding loci and the identification of their promoters remains 'elusive'. Here, we present microTSS, a machine-learning algorithm that provides highly accurate, single-nucleotide resolution predictions for intergenic miRNA transcription start sites (TSSs). MicroTSS integrates high-resolution RNA-sequencing data with active transcription marks derived from chromatin immunoprecipitation and DNase-sequencing to enable the characterization of tissue-specific promoters. MicroTSS is validated with a specifically designed Drosha-null/conditional-null mouse model, generated using the conditional by inversion (COIN) methodology. Analyses of global run-on sequencing data revealed numerous pri-miRNAs in human and mouse either originating from divergent transcription at promoters of active genes or partially overlapping with annotated long non-coding RNAs. MicroTSS is readily applicable to any cell or tissue samples and constitutes the missing part towards integrating the regulation of miRNA transcription into the modelling of tissue-specific regulatory networks.
authors.affiliation: Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece.
authors.forename: Georgios
authors.initials: G
authors.lastname: Georgakilas
authors.affiliation: 1] Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece [2] Laboratory for Experimental Surgery and Surgical Research 'N.S. Christeas', Medical School of Athens, University of Athens, 11527 Athens, Greece.
authors.forename: Ioannis S
authors.initials: IS
authors.lastname: Vlachos
authors.affiliation: Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece.
authors.forename: Maria D
authors.initials: MD
authors.lastname: Paraskevopoulou
authors.affiliation: Regeneron Pharmaceuticals Inc., Tarrytown, New York 10591, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Yang
authors.affiliation: Regeneron Pharmaceuticals Inc., Tarrytown, New York 10591, USA.
authors.forename: Yuhong
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Regeneron Pharmaceuticals Inc., Tarrytown, New York 10591, USA.
authors.forename: Aris N
authors.initials: AN
authors.lastname: Economides
authors.affiliation: Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece.
authors.forename: Artemis G
authors.initials: AG
authors.lastname: Hatzigeorgiou
mesh_terms: D000465:Algorithms; D000818:Animals; D047369:Chromatin Immunoprecipitation; D016000:Cluster Analysis; D019295:Computational Biology; D053595:Embryonic Stem Cells / Q000166:cytology; D006801:Humans; D051379:Mice; D008822:Mice, Transgenic; D035683:MicroRNAs / Q000235:genetics*; D008957:Models, Genetic; D016376:Oligonucleotides, Antisense / Q000235:genetics; D011401:Promoter Regions, Genetic; D012319:RNA Polymerase II / Q000378:metabolism; D012333:RNA, Messenger / Q000378:metabolism; D022661:RNA, Untranslated / Q000378:metabolism; D043244:Ribonuclease III / Q000235:genetics; D017423:Sequence Analysis, RNA; D060388:Support Vector Machine; D024363:Transcription Initiation Site
chemical_list: D035683:MicroRNAs; D016376:Oligonucleotides, Antisense; D012333:RNA, Messenger; D022661:RNA, Untranslated; D012319:RNA Polymerase II; C513400:Drosha protein, mouse; D043244:Ribonuclease III