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      MiR&moRe2: A Bioinformatics Tool to Characterize microRNAs and microRNA-Offset RNAs from Small RNA-Seq Data

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          Abstract

          MicroRNA-offset RNAs (moRNAs) are microRNA-like small RNAs generated by microRNA precursors. To date, little is known about moRNAs and bioinformatics tools to inspect their expression are still missing. We developed miR&moRe2, the first bioinformatics method to consistently characterize microRNAs, moRNAs, and their isoforms from small RNA sequencing data. To illustrate miR&moRe2 discovery power, we applied it to several published datasets. MoRNAs identified by miR&moRe2 were in agreement with previous research findings. Moreover, we observed that moRNAs and new microRNAs predicted by miR&moRe2 were downregulated upon the silencing of the microRNA-biogenesis pathway. Further, in a sizeable dataset of human blood cell populations, tens of novel miRNAs and moRNAs were discovered, some of them with significantly varied expression levels among the cell types. Results demonstrate that miR&moRe2 is a valid tool for a comprehensive study of small RNAs generated from microRNA precursors and could help to investigate their biogenesis and function.

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          Most cited references29

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          A comprehensive survey of 3' animal miRNA modification events and a possible role for 3' adenylation in modulating miRNA targeting effectiveness.

          Animal microRNA sequences are subject to 3' nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3' adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1-EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3' addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3' adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake.
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            Evidence for the biogenesis of more than 1,000 novel human microRNAs

            Background MicroRNAs (miRNAs) are established regulators of development, cell identity and disease. Although nearly two thousand human miRNA genes are known and new ones are continuously discovered, no attempt has been made to gauge the total miRNA content of the human genome. Results Employing an innovative computational method on massively pooled small RNA sequencing data, we report 2,469 novel human miRNA candidates of which 1,098 are validated by in-house and published experiments. Almost 300 candidates are robustly expressed in a neuronal cell system and are regulated during differentiation or when biogenesis factors Dicer, Drosha, DGCR8 or Ago2 are silenced. To improve expression profiling, we devised a quantitative miRNA capture system. In a kidney cell system, 400 candidates interact with DGCR8 at transcript positions that suggest miRNA hairpin recognition, and 1,000 of the new miRNA candidates interact with Ago1 or Ago2, indicating that they are directly bound by miRNA effector proteins. From kidney cell CLASH experiments, in which miRNA-target pairs are ligated and sequenced, we observe hundreds of interactions between novel miRNAs and mRNA targets. The novel miRNA candidates are specifically but lowly expressed, raising the possibility that not all may be functional. Interestingly, the majority are evolutionarily young and overrepresented in the human brain. Conclusions In summary, we present evidence that the complement of human miRNA genes is substantially larger than anticipated, and that more are likely to be discovered in the future as more tissues and experimental conditions are sequenced to greater depth.
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              Deep annotation of Drosophila melanogaster microRNAs yields insights into their processing, modification, and emergence.

              Since the initial annotation of miRNAs from cloned short RNAs by the Ambros, Tuschl, and Bartel groups in 2001, more than a hundred studies have sought to identify additional miRNAs in various species. We report here a meta-analysis of short RNA data from Drosophila melanogaster, aggregating published libraries with 76 data sets that we generated for the modENCODE project. In total, we began with more than 1 billion raw reads from 187 libraries comprising diverse developmental stages, specific tissue- and cell-types, mutant conditions, and/or Argonaute immunoprecipitations. We elucidated several features of known miRNA loci, including multiple phased byproducts of cropping and dicing, abundant alternative 5' termini of certain miRNAs, frequent 3' untemplated additions, and potential editing events. We also identified 49 novel genomic locations of miRNA production, and 61 additional candidate loci with limited evidence for miRNA biogenesis. Although these loci broaden the Drosophila miRNA catalog, this work supports the notion that a restricted set of cellular transcripts is competent to be specifically processed by the Drosha/Dicer-1 pathway. Unexpectedly, we detected miRNA production from coding and untranslated regions of mRNAs and found the phenomenon of miRNA production from the antisense strand of known loci to be common. Altogether, this study lays a comprehensive foundation for the study of miRNA diversity and evolution in a complex animal model.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                04 March 2020
                March 2020
                : 21
                : 5
                : 1754
                Affiliations
                [1 ]Department of Molecular Medicine, University of Padova, 35121 Padova, Italy; michele.bortolomeazzi@ 123456gmail.com (M.B.); andrea.bisognin@ 123456gmail.com (A.B.)
                [2 ]Division of Pediatric Hematology, Department of Women’s and Children’s Health, University of Padova, 35128 Padova, Italy; piero.dibattista@ 123456phd.unipd.it (P.D.B.); federica.lovisa@ 123456unipd.it (F.L.); lara.mussolin@ 123456unipd.it (L.M.)
                [3 ]Istituto di Ricerca Pediatrica Città della Speranza, 35127 Padova, Italy
                [4 ]Interdepartmental Research Center for Innovative Biotechnologies (CRIBI), University of Padova, 35131 Padova, Italy
                Author notes
                [* ]Correspondence: enrico.gaffo@ 123456unipd.it (E.G.); stefania.bortoluzzi@ 123456unipd.it (S.B.); Tel.: +39-049-827-6502 (S.B.)
                Author information
                https://orcid.org/0000-0001-6338-7677
                https://orcid.org/0000-0001-8240-3070
                Article
                ijms-21-01754
                10.3390/ijms21051754
                7084216
                32143373
                d3d157a7-c09b-48d9-982a-ea1f9bdcd2a5
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 January 2020
                : 01 March 2020
                Categories
                Article

                Molecular biology
                mirnas,mornas,isomirs,isomors,small rna prediction,bioinformatics,non-coding rnas
                Molecular biology
                mirnas, mornas, isomirs, isomors, small rna prediction, bioinformatics, non-coding rnas

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