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Nersisyan S, Loher P, Nazeraj I, Shao Z, Fullard JF, Voloudakis G, Girdhar K, Roussos P, Rigoutsos I. Comprehensive profiling of small RNAs and their changes and linkages to mRNAs in schizophrenia and bipolar disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.24.630254. [PMID: 39763727 PMCID: PMC11703252 DOI: 10.1101/2024.12.24.630254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
We investigated small non-coding RNAs (sncRNAs) from the prefrontal cortex of 93 individuals diagnosed with schizophrenia (SCZ) or bipolar disorder (BD) and 77 controls. We uncovered recurring complex sncRNA profiles, with 98% of all sncRNAs being accounted for by miRNA isoforms (60.6%), tRNA-derived fragments (17.8%), rRNA-derived fragments (11.4%), and Y RNA-derived fragments (8.3%). In SCZ, 15% of all sncRNAs exhibit statistically significant changes in their abundance. In BD, the fold changes (FCs) are highly correlated with those in SCZ but less acute. Non-templated nucleotide additions to the 3´-ends of many miRNA isoforms determine their FC independently of miRNA identity or genomic locus of origin. In both SCZ and BD, disease- and age-associated sncRNAs and mRNAs reveal accelerated aging. Co-expression modules between sncRNAs and mRNAs align with the polarities of SCZ changes and implicate sncRNAs in critical processes, including synaptic signaling, neurogenesis, memory, behavior, and cognition.
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Affiliation(s)
- Stepan Nersisyan
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Phillipe Loher
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Iliza Nazeraj
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Zhiping Shao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - John F. Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Center for Precision Medicine and Translational Therapeutics, JJ Peters VA Medical Center, Bronx, New York, USA
- Mental Illness Research Education and Clinical Center (MIRECC), JJ Peters VA Medical Center, Bronx, New York, USA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
- Center for Precision Medicine and Translational Therapeutics, JJ Peters VA Medical Center, Bronx, New York, USA
- Mental Illness Research Education and Clinical Center (MIRECC), JJ Peters VA Medical Center, Bronx, New York, USA
| | - Isidore Rigoutsos
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, USA
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Calin GA, Hubé F, Ladomery MR, Delihas N, Ferracin M, Poliseno L, Agnelli L, Alahari SK, Yu AM, Zhong XB. The 2024 Nobel Prize in Physiology or Medicine: microRNA Takes Center Stage. Noncoding RNA 2024; 10:62. [PMID: 39728607 PMCID: PMC11679529 DOI: 10.3390/ncrna10060062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2024] [Accepted: 12/03/2024] [Indexed: 12/28/2024] Open
Abstract
The Non-coding Journal Editorial Board Members would like to congratulate Victor Ambros and Gary Ruvkun, who were jointly awarded the 2024 Nobel Prize in Physiology or Medicine for their groundbreaking discovery of microRNAs and the role of microRNAs in post-transcriptional gene regulation, uncovering a previously unknown layer of gene control in eukaryotes [...].
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Affiliation(s)
- George A. Calin
- Department of Translational Molecular Pathology, Center for RNA Interference and Non-Coding RNAs, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Florent Hubé
- Laboratoire Biologie du Développement, Institut de Biologie Paris-Seine, Transgenerational Epigenetics & Small RNA Biology, Sorbonne Université, CNRS, UMR7622, 75005 Paris, France
| | - Michael R. Ladomery
- School of Applied Sciences, University of the West of England, Bristol BS16 1QY, UK
| | - Nicholas Delihas
- Department of Microbiology and Immunology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Manuela Ferracin
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, via S. Giacomo, 14, 40126 Bologna, Italy
| | - Laura Poliseno
- National Research Council (CNR) and Oncogenomics Unit, Core Research Laboratory (CRL), Institute of Clinical Physiology (IFC), Istituto per lo Studio, la Prevenzione e la Rete Oncologica (ISPRO), via Moruzzi 1, 56124 Pisa, Italy
| | - Luca Agnelli
- Department of Diagnostic Innovation, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, 20133 Milan, Italy
- Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, 20133 Milan, Italy
| | - Suresh K. Alahari
- Department of Biochemistry and Molecular Biology, LSU School of Medicine, New Orleans, LA 70112, USA
| | - Ai-Ming Yu
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California at Davis, Sacramento, CA 95817, USA
| | - Xiao-Bo Zhong
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, CT 06269, USA
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Vivek AT, Arya A, Swain SP, Kumar S. athisomiRDB: A comprehensive database of Arabidopsis isomiRs. Database (Oxford) 2024; 2024:baae115. [PMID: 39514415 PMCID: PMC11544919 DOI: 10.1093/database/baae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 09/04/2024] [Accepted: 10/17/2024] [Indexed: 11/16/2024]
Abstract
Several pieces of evidence challenge the traditional view of miRNAs as static molecules, revealing dynamic isomiRs originating from each miRNA precursor arm. In plants, isomiRs, which result from imprecise cleavage during pre-miRNA processing and post-transcriptional alterations, serve as crucial regulators of target microRNAs (miRNAs). Despite numerous studies on Arabidopsis miRNAs, the systematic identification and annotation of isomiRs across various tissues and conditions remain limited. Due to the lack of systematically collected isomiR information, we introduce the athisomiRDB database, which houses 20 764 isomiRs from Arabidopsis small RNA-sequencing (sRNA-seq) libraries. It comprises >2700 diverse samples and allows exploration at the sample, miRNA, or isomiR levels, offering insights into the presence or absence of isomiRs. The athisomiRDB includes exclusive and ambiguous isomiRs, each with features such as transcriptional origin, variant-containing isomiRs, and identifiers for frequent single-nucleotide polymorphisms from the 1001 Genomes Project. It also provides 3' nontemplated post-transcriptional additions, isomiR-target interactions, and trait associations for each isomiR. We anticipate that athisomiRDB will play a pivotal role in unraveling the regulatory nature of the Arabidopsis miRNAome and enhancing sRNA research by leveraging isomiR profiles from extensive sRNA-seq datasets. Database URL: https://www.nipgr.ac.in/athisomiRDB.
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Grants
- BT/PR40160/BTIS/137/64/2023 BT/PR40169/BTIS/137/71/2023 BT/PR40261/ BTIS/137/55/2023 PR40146/BTIS/137/4/2020 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR40160/BTIS/137/64/2023 BT/PR40169/BTIS/137/71/2023 BT/PR40261/ BTIS/137/55/2023 PR40146/BTIS/137/4/2020 Department of Biotechnology, Ministry of Science and Technology, India
- BT/PR40146/BTIS/137/4/2020 DBT, Government of India, and NIPGR, laboratory of S.K.
- BT/PR40169/BTIS/137/71/2023 DBT, Government of India, and NIPGR, laboratory of S.K.
- BT/PR40160/BTIS/137/64/2023 DBT, Government of India, and NIPGR, laboratory of S.K.
- BT/PR40261/BTIS/137/55/2023 DBT, Government of India, and NIPGR, laboratory of S.K.
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Affiliation(s)
- A T Vivek
- Bioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Ajay Arya
- Bioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Supriya P Swain
- Bioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Shailesh Kumar
- Bioinformatics Laboratory, National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
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Cherlin T, Jing Y, Shah S, Kennedy A, Telonis AG, Pliatsika V, Wilson H, Thompson L, Vlantis PI, Loher P, Leiby B, Rigoutsos I. The subcellular distribution of miRNA isoforms, tRNA-derived fragments, and rRNA-derived fragments depends on nucleotide sequence and cell type. BMC Biol 2024; 22:205. [PMID: 39267057 PMCID: PMC11397057 DOI: 10.1186/s12915-024-01970-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 08/01/2024] [Indexed: 09/14/2024] Open
Abstract
BACKGROUND MicroRNA isoforms (isomiRs), tRNA-derived fragments (tRFs), and rRNA-derived fragments (rRFs) represent most of the small non-coding RNAs (sncRNAs) found in cells. Members of these three classes modulate messenger RNA (mRNA) and protein abundance and are dysregulated in diseases. Experimental studies to date have assumed that the subcellular distribution of these molecules is well-understood, independent of cell type, and the same for all isoforms of a sncRNA. RESULTS We tested these assumptions by investigating the subcellular distribution of isomiRs, tRFs, and rRFs in biological replicates from three cell lines from the same tissue and same-sex donors that model the same cancer subtype. In each cell line, we profiled the isomiRs, tRFs, and rRFs in the nucleus, cytoplasm, whole mitochondrion (MT), mitoplast (MP), and whole cell. Using a rigorous mathematical model we developed, we accounted for cross-fraction contamination and technical errors and adjusted the measured abundances accordingly. Analyses of the adjusted abundances show that isomiRs, tRFs, and rRFs exhibit complex patterns of subcellular distributions. These patterns depend on each sncRNA's exact sequence and the cell type. Even in the same cell line, isoforms of the same sncRNA whose sequences differ by a few nucleotides (nts) can have different subcellular distributions. CONCLUSIONS SncRNAs with similar sequences have different subcellular distributions within and across cell lines, suggesting that each isoform could have a different function. Future computational and experimental studies of isomiRs, tRFs, and rRFs will need to distinguish among each molecule's various isoforms and account for differences in each isoform's subcellular distribution in the cell line at hand. While the findings add to a growing body of evidence that isomiRs, tRFs, rRFs, tRNAs, and rRNAs follow complex intracellular trafficking rules, further investigation is needed to exclude alternative explanations for the observed subcellular distribution of sncRNAs.
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Affiliation(s)
- Tess Cherlin
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- University of Pennsylvania, Philadelphia, PA, USA
| | - Yi Jing
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
| | - Siddhartha Shah
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
| | - Anne Kennedy
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- Department of Pharmacology, Physiology and Cancer Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Aristeidis G Telonis
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- University of Miami, Miami, FL, USA
| | - Venetia Pliatsika
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- New York University, New York, NY, USA
| | - Haley Wilson
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- Department of Pharmacology, Physiology and Cancer Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Lily Thompson
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- Department of Biochemistry and Molecular Biology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Panagiotis I Vlantis
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
- Independent Scholar, Athens, Greece
| | - Phillipe Loher
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA
| | - Benjamin Leiby
- Division of Biostatistics, Thomas Jefferson University, Philadelphia, PA, 19017, USA
| | - Isidore Rigoutsos
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA, 19017, USA.
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Maltseva D, Kirillov I, Zhiyanov A, Averinskaya D, Suvorov R, Gubani D, Kudriaeva A, Belogurov A, Tonevitsky A. Incautious design of shRNAs for stable overexpression of miRNAs could result in generation of undesired isomiRs. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2024; 1867:195046. [PMID: 38876159 DOI: 10.1016/j.bbagrm.2024.195046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 06/03/2024] [Accepted: 06/06/2024] [Indexed: 06/16/2024]
Abstract
shRNA-mediated strategy of miRNA overexpression based on RNA Polymerase III (Pol III) expression cassettes is widely used for miRNA functional studies. For some miRNAs, e.g., encoded in the genome as a part of a polycistronic miRNA cluster, it is most likely the only way for their individual stable overexpression. Here we have revealed that expression of miRNAs longer than 19 nt (e.g. 23 nt in length hsa-miR-93-5p) using such approach could be accompanied by undesired predominant generation of 5' end miRNA isoforms (5'-isomiRs). Extra U residues (up to five) added by Pol III at the 3' end of the transcribed shRNA during transcription termination could cause a shift in the Dicer cleavage position of the shRNA. This results in the formation of 5'-isomiRs, which have a significantly altered seed region compared to the initially encoded canonical hsa-miR-93-5p. We demonstrated that the commonly used qPCR method is insensitive to the formation of 5'-isomiRs and cannot be used to confirm miRNA overexpression. However, the predominant expression of 5'-isomiRs without three or four first nucleotides instead of the canonical isoform could be disclosed based on miRNA-Seq analysis. Moreover, mRNA sequencing data showed that the 5'-isomiRs of hsa-miR-93-5p presumably regulate their own mRNA targets. Thus, omitting miRNA-Seq analysis may lead to erroneous conclusions regarding revealed mRNA targets and possible molecular mechanisms in which studied miRNA is involved. Overall, the presented results show that structures of shRNAs for stable overexpression of miRNAs requires careful design to avoid generation of undesired 5'-isomiRs.
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Affiliation(s)
- Diana Maltseva
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Ivan Kirillov
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Anton Zhiyanov
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Daria Averinskaya
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Roman Suvorov
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Daria Gubani
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia
| | - Anna Kudriaeva
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997, Russia
| | - Alexey Belogurov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997, Russia
| | - Alexander Tonevitsky
- Faculty of Biology and Biotechnology, National Research University Higher School of Economics, Moscow 101000, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow 117997, Russia; Art Photonics GmbH, Berlin 12489, Germany.
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Wagner V, Meese E, Keller A. The intricacies of isomiRs: from classification to clinical relevance. Trends Genet 2024; 40:784-796. [PMID: 38862304 DOI: 10.1016/j.tig.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/13/2024]
Abstract
MicroRNAs (miRNAs) and isoforms of their archetype, called isomiRs, regulate gene expression via complementary base-pair binding to messenger RNAs (mRNAs). The partially evolutionarily conserved isomiR sequence variations are differentially expressed among tissues, populations, and genders, and between healthy and diseased states. Aiming towards the clinical use of isomiRs as diagnostic biomarkers and for therapeutic purposes, several challenges need to be addressed, including (i) clarification of isomiR definition, (ii) improved annotation in databases with new standardization (such as the mirGFF3 format), and (iii) improved methods of isomiR detection, functional verification, and in silico analysis. In this review we discuss the respective challenges, and highlight the opportunities for clinical use of isomiRs, especially in the light of increasing amounts of next-generation sequencing (NGS) data.
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Affiliation(s)
- Viktoria Wagner
- Chair for Clinical Bioinformatics, Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany; Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS), Saarland University Campus, 66123 Saarbrücken, Germany
| | - Eckart Meese
- Department of Human Genetics, Saarland University, 66421 Homburg/Saar, Germany
| | - Andreas Keller
- Chair for Clinical Bioinformatics, Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany; Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS), Saarland University Campus, 66123 Saarbrücken, Germany.
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Pliatsika V, Cherlin T, Loher P, Vlantis P, Nagarkar P, Nersisyan S, Rigoutsos I. MINRbase: a comprehensive database of nuclear- and mitochondrial-ribosomal-RNA-derived fragments (rRFs). Nucleic Acids Res 2024; 52:D229-D238. [PMID: 37843123 PMCID: PMC10767805 DOI: 10.1093/nar/gkad833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 09/17/2023] [Accepted: 09/20/2023] [Indexed: 10/17/2023] Open
Abstract
We describe the Mitochondrial and Nuclear rRNA fragment database (MINRbase), a knowledge repository aimed at facilitating the study of ribosomal RNA-derived fragments (rRFs). MINRbase provides interactive access to the profiles of 130 238 expressed rRFs arising from the four human nuclear rRNAs (18S, 5.8S, 28S, 5S), two mitochondrial rRNAs (12S, 16S) or four spacers of 45S pre-rRNA. We compiled these profiles by analyzing 11 632 datasets, including the GEUVADIS and The Cancer Genome Atlas (TCGA) repositories. MINRbase offers a user-friendly interface that lets researchers issue complex queries based on one or more criteria, such as parental rRNA identity, nucleotide sequence, rRF minimum abundance and metadata keywords (e.g. tissue type, disease). A 'summary' page for each rRF provides a granular breakdown of its expression by tissue type, disease, sex, ancestry and other variables; it also allows users to create publication-ready plots at the click of a button. MINRbase has already allowed us to generate support for three novel observations: the internal spacers of 45S are prolific producers of abundant rRFs; many abundant rRFs straddle the known boundaries of rRNAs; rRF production is regimented and depends on 'personal attributes' (sex, ancestry) and 'context' (tissue type, tissue state, disease). MINRbase is available at https://cm.jefferson.edu/MINRbase/.
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Affiliation(s)
- Venetia Pliatsika
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Tess Cherlin
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Phillipe Loher
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Panagiotis Vlantis
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Parth Nagarkar
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Stepan Nersisyan
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Isidore Rigoutsos
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
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Akins RB, Ostberg K, Cherlin T, Tsiouplis NJ, Loher P, Rigoutsos I. The Typical tRNA Co-Expresses Multiple 5' tRNA Halves Whose Sequences and Abundances Depend on Isodecoder and Isoacceptor and Change with Tissue Type, Cell Type, and Disease. Noncoding RNA 2023; 9:69. [PMID: 37987365 PMCID: PMC10660753 DOI: 10.3390/ncrna9060069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 10/02/2023] [Accepted: 10/12/2023] [Indexed: 11/22/2023] Open
Abstract
Transfer RNA-derived fragments (tRFs) are noncoding RNAs that arise from either mature transfer RNAs (tRNAs) or their precursors. One important category of tRFs comprises the tRNA halves, which are generated through cleavage at the anticodon. A given tRNA typically gives rise to several co-expressed 5'-tRNA halves (5'-tRHs) that differ in the location of their 3' ends. These 5'-tRHs, even though distinct, have traditionally been treated as indistinguishable from one another due to their near-identical sequences and lengths. We focused on co-expressed 5'-tRHs that arise from the same tRNA and systematically examined their exact sequences and abundances across 10 different human tissues. To this end, we manually curated and analyzed several hundred human RNA-seq datasets from NCBI's Sequence Run Archive (SRA). We grouped datasets from the same tissue into their own collection and examined each group separately. We found that a given tRNA produces different groups of co-expressed 5'-tRHs in different tissues, different cell lines, and different diseases. Importantly, the co-expressed 5'-tRHs differ in their sequences, absolute abundances, and relative abundances, even among tRNAs with near-identical sequences from the same isodecoder or isoacceptor group. The findings suggest that co-expressed 5'-tRHs that are produced from the same tRNA or closely related tRNAs have distinct, context-dependent roles. Moreover, our analyses show that cell lines modeling the same tissue type and disease may not be interchangeable when it comes to experimenting with tRFs.
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Affiliation(s)
| | | | | | | | | | - Isidore Rigoutsos
- Computational Medical Center, Thomas Jefferson University, Philadelphia, PA 19107, USA
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Nersisyan S, Montenont E, Loher P, Middleton EA, Campbell R, Bray P, Rigoutsos I. Characterization of all small RNAs in and comparisons across cultured megakaryocytes and platelets of healthy individuals and COVID-19 patients. J Thromb Haemost 2023; 21:3252-3267. [PMID: 37558133 DOI: 10.1016/j.jtha.2023.07.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/03/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
BACKGROUND The small noncoding RNAs (sncRNAs) in megakaryocytes (MKs) and platelets are not well characterized. Neither is the impact of SARS-CoV-2 infection on the sncRNAs of platelets. OBJECTIVES To investigate the sorting of MK sncRNAs into platelets, and the differences in the platelet sncRNAomes of healthy donors (HDs) and COVID-19 patients. METHODS We comprehensively profiled sncRNAs from MKs cultured from cord blood-derived CD34+ cells, platelets from HDs, and platelets from patients with moderate and severe SARS-CoV-2 infection. We also comprehensively profiled Argonaute (AGO)-bound sncRNAs from the cultured MKs. RESULTS We characterized the sncRNAs in MKs and platelets and can account for ∼95% of all sequenced reads. We found that MKs primarily comprise microRNA isoforms (isomiRs), tRNA-derived fragments (tRFs), rRNA-derived fragments (rRFs), and Y RNA-derived fragments (yRFs) in comparable abundances. The platelets of HDs showed a skewed distribution by comparison: 56.7% of all sncRNAs are yRFs, 34.4% are isomiRs, and <2.0% are tRFs and rRFs. Most isomiRs in MKs and platelets are either noncanonical, nontemplated, or both. When comparing MKs and platelets from HDs, we found numerous isomiRs, tRFs, rRFs, and yRFs showing opposite enrichments or depletions, including molecules from the same parental miRNA arm, tRNA, rRNA, or Y RNA. The sncRNAome of platelets from patients with COVID-19 is skewed compared to that of HDs with only 19.8% of all sncRNAs now being yRFs, isomiRs increasing to 63.6%, and tRFs and rRFs more than tripling their presence to 6.1%. CONCLUSION The sncRNAomes of MKs and platelets are very rich and more complex than it has been believed. The evidence suggests complex mechanisms that sort MK sncRNAs into platelets. SARS-CoV-2 infection acutely alters the contents of platelets by changing the relative proportions of their sncRNAs.
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Affiliation(s)
- Stepan Nersisyan
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Emilie Montenont
- University of Utah Molecular Medicine Program, University of Utah, Salt Lake City, Utah, USA
| | - Phillipe Loher
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Elizabeth A Middleton
- University of Utah Molecular Medicine Program, University of Utah, Salt Lake City, Utah, USA; Division of Pulmonary Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Robert Campbell
- University of Utah Molecular Medicine Program, University of Utah, Salt Lake City, Utah, USA; Division of General Medicine, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Paul Bray
- University of Utah Molecular Medicine Program, University of Utah, Salt Lake City, Utah, USA; Division of Hematology and Hematologic Malignancies, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Isidore Rigoutsos
- Computational Medicine Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
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10
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Nersisyan S, Zhiyanov A, Engibaryan N, Maltseva D, Tonevitsky A. A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer. Front Genet 2022; 13:1070528. [PMID: 36531236 PMCID: PMC9751988 DOI: 10.3389/fgene.2022.1070528] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 11/21/2022] [Indexed: 07/31/2023] Open
Abstract
A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.
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Affiliation(s)
- Stepan Nersisyan
- Faculty of Biology and Biotechnology, HSE University, Moscow, Russia
| | - Anton Zhiyanov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Narek Engibaryan
- Faculty of Biology and Biotechnology, HSE University, Moscow, Russia
| | - Diana Maltseva
- Faculty of Biology and Biotechnology, HSE University, Moscow, Russia
| | - Alexander Tonevitsky
- Faculty of Biology and Biotechnology, HSE University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Art Photonics GmbH, Berlin, Germany
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Distefano R, Tomasello L, Rampioni Vinciguerra GL, Gasparini P, Xiang Y, Bagnoli M, Marceca GP, Fadda P, Laganà A, Acunzo M, Ma Q, Nigita G, Croce CM. Pan-Cancer Analysis of Canonical and Modified miRNAs Enhances the Resolution of the Functional miRNAome in Cancer. Cancer Res 2022; 82:3687-3700. [PMID: 36040379 PMCID: PMC9574374 DOI: 10.1158/0008-5472.can-22-0240] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 06/24/2022] [Accepted: 08/18/2022] [Indexed: 12/14/2022]
Abstract
UNLABELLED Epitranscriptomic studies of miRNAs have added a new layer of complexity to the cancer field. Although there is fast-growing interest in adenosine-to-inosine (A-to-I) miRNA editing and alternative cleavage that shifts miRNA isoforms, simultaneous evaluation of both modifications in cancer is still missing. Here, we concurrently profiled multiple miRNA modification types, including A-to-I miRNA editing and shifted miRNA isoforms, in >13,000 adult and pediatric tumor samples across 38 distinct cancer cohorts from The Cancer Genome Atlas and The Therapeutically Applicable Research to Generate Effective Treatments data sets. The differences between canonical miRNAs and the wider miRNAome in terms of expression, clustering, dysregulation, and prognostic standpoint were investigated. The combination of canonical miRNAs and modified miRNAs boosted the quality of clustering results, outlining unique clinicopathologic features among cohorts. Certain modified miRNAs showed opposite expression from their canonical counterparts in cancer, potentially impacting their targets and function. Finally, a shifted and edited miRNA isoform was experimentally validated to directly bind and suppress a unique target. These findings outline the importance of going beyond the well-established paradigm of one mature miRNA per miRNA arm to elucidate novel mechanisms related to cancer progression. SIGNIFICANCE Modified miRNAs may act as cancer biomarkers and function as allies or antagonists of their canonical counterparts in gene regulation, suggesting the concurrent consideration of canonical and modified miRNAs can boost patient stratification.
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Affiliation(s)
- Rosario Distefano
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Luisa Tomasello
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Gian Luca Rampioni Vinciguerra
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
- Faculty of Medicine and Psychology, Department of Clinical and Molecular Medicine, University of Rome “Sapienza,” Santo Andrea Hospital, Rome, Italy
| | - Pierluigi Gasparini
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Yujia Xiang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio
| | - Marina Bagnoli
- Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Gioacchino P. Marceca
- Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Paolo Fadda
- Genomics Shared Resource, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Alessandro Laganà
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Mario Acunzo
- Division of Pulmonary Diseases and Critical Care Medicine, Virginia Commonwealth University, Richmond, Virginia
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio
| | - Giovanni Nigita
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Carlo M. Croce
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
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Giannella A, Riccetti S, Sinigaglia A, Piubelli C, Razzaboni E, Di Battista P, Agostini M, Dal Molin E, Manganelli R, Gobbi F, Ceolotto G, Barzon L. Circulating microRNA signatures associated with disease severity and outcome in COVID-19 patients. Front Immunol 2022; 13:968991. [PMID: 36032130 PMCID: PMC9403711 DOI: 10.3389/fimmu.2022.968991] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/20/2022] [Indexed: 12/14/2022] Open
Abstract
Background SARS-CoV-2 induces a spectrum of clinical conditions ranging from asymptomatic infection to life threatening severe disease. Host microRNAs have been involved in the cytokine storm driven by SARS-CoV-2 infection and proposed as candidate biomarkers for COVID-19. Methods To discover signatures of circulating miRNAs associated with COVID-19, disease severity and mortality, small RNA-sequencing was performed on serum samples collected from 89 COVID-19 patients (34 severe, 29 moderate, 26 mild) at hospital admission and from 45 healthy controls (HC). To search for possible sources of miRNAs, investigation of differentially expressed (DE) miRNAs in relevant human cell types in vitro. Results COVID-19 patients showed upregulation of miRNAs associated with lung disease, vascular damage and inflammation and downregulation of miRNAs that inhibit pro-inflammatory cytokines and chemokines, angiogenesis, and stress response. Compared with mild/moderate disease, patients with severe COVID-19 had a miRNA signature indicating a profound impairment of innate and adaptive immune responses, inflammation, lung fibrosis and heart failure. A subset of the DE miRNAs predicted mortality. In particular, a combination of high serum miR-22-3p and miR-21-5p, which target antiviral response genes, and low miR-224-5p and miR-155-5p, targeting pro-inflammatory factors, discriminated severe from mild/moderate COVID-19 (AUROC 0.88, 95% CI 0.80-0.95, p<0.0001), while high leukocyte count and low levels of miR-1-3p, miR-23b-3p, miR-141-3p, miR-155-5p and miR-4433b-5p predicted mortality with high sensitivity and specificity (AUROC 0.95, 95% CI 0.89-1.00, p<0.0001). In vitro experiments showed that some of the DE miRNAs were modulated directly by SARS-CoV-2 infection in permissive lung epithelial cells. Conclusions We discovered circulating miRNAs associated with COVID-19 severity and mortality. The identified DE miRNAs provided clues on COVID-19 pathogenesis, highlighting signatures of impaired interferon and antiviral responses, inflammation, organ damage and cardiovascular failure as associated with severe disease and death.
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Affiliation(s)
| | - Silvia Riccetti
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Chiara Piubelli
- Department of Infectious-Tropical Diseases and Microbiology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Sacro Cuore Don Calabria Hospital, Verona, Italy
| | - Elisa Razzaboni
- Department of Infectious-Tropical Diseases and Microbiology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Sacro Cuore Don Calabria Hospital, Verona, Italy
| | - Piero Di Battista
- Maternal and Child Health Department, University of Padova, Padova, Italy
| | - Matteo Agostini
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | | | - Riccardo Manganelli
- Department of Molecular Medicine, University of Padova, Padova, Italy
- Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
| | - Federico Gobbi
- Department of Infectious-Tropical Diseases and Microbiology, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Sacro Cuore Don Calabria Hospital, Verona, Italy
| | | | - Luisa Barzon
- Department of Molecular Medicine, University of Padova, Padova, Italy
- Microbiology and Virology Unit, Padova University Hospital, Padova, Italy
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Epigenomic Modifications in Modern and Ancient Genomes. Genes (Basel) 2022; 13:genes13020178. [PMID: 35205223 PMCID: PMC8872240 DOI: 10.3390/genes13020178] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 01/12/2022] [Accepted: 01/13/2022] [Indexed: 12/26/2022] Open
Abstract
Epigenetic changes have been identified as a major driver of fundamental metabolic pathways. More specifically, the importance of epigenetic regulatory mechanisms for biological processes like speciation and embryogenesis has been well documented and revealed the direct link between epigenetic modifications and various diseases. In this review, we focus on epigenetic changes in animals with special attention on human DNA methylation utilizing ancient and modern genomes. Acknowledging the latest developments in ancient DNA research, we further discuss paleoepigenomic approaches as the only means to infer epigenetic changes in the past. Investigating genome-wide methylation patterns of ancient humans may ultimately yield in a more comprehensive understanding of how our ancestors have adapted to the changing environment, and modified their lifestyles accordingly. We discuss the difficulties of working with ancient DNA in particular utilizing paleoepigenomic approaches, and assess new paleoepigenomic data, which might be helpful in future studies.
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MicroRNA Isoforms Contribution to Melanoma Pathogenesis. Noncoding RNA 2021; 7:ncrna7040063. [PMID: 34698264 PMCID: PMC8544706 DOI: 10.3390/ncrna7040063] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/15/2021] [Accepted: 09/21/2021] [Indexed: 12/28/2022] Open
Abstract
Cutaneous melanoma (CM) is the most lethal tumor among skin cancers, and its incidence is constantly increasing. A deeper understanding of the molecular processes guiding melanoma pathogenesis could improve diagnosis, treatment and prognosis. MicroRNAs play a key role in melanoma biology. Recently, next generation sequencing (NGS) experiments, designed to assess small-RNA expression, revealed the existence of microRNA variants with different length and sequence. These microRNA isoforms are known as isomiRs and provide an additional layer to the complex non-coding RNA world. Here, we collected data from NGS experiments to provide a comprehensive characterization of miRNA and isomiR dysregulation in benign nevi (BN) and early-stage melanomas. We observed that melanoma and BN express different and specific isomiRs and have a different isomiR abundance distribution. Moreover, isomiRs from the same microRNA can have opposite expression trends between groups. Using The Cancer Genome Atlas (TCGA) dataset of skin cancers, we analyzed isomiR expression in primary melanoma and melanoma metastasis and tested their association with NF1, BRAF and NRAS mutations. IsomiRs differentially expressed were identified and catalogued with reference to the canonical form. The reported non-random dysregulation of specific isomiRs contributes to the understanding of the complex melanoma pathogenesis and serves as the basis for further functional studies.
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