The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study

Author:

Simona Panni1,Panneerselvam Kalpana2,Porras Pablo23,Duesbury Margaret2,Perfetto Livia4,Licata Luana5ORCID,Hermjakob Henning2ORCID,Orchard Sandra2ORCID

Affiliation:

1. Dipartimento di Biologia Ecologia e Scienze della Terra, Università della Calabria , Rende 87036, Italy

2. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton , Cambridge CB10 1SD, UK

3. Astra Zeneca, Data Office, Data Science and AI, UK Academy House , 136 Hills Road, Cambridge CB2 8PA, UK

4. Department of Biology and Biotechnologies “Charles Darwin”, La Sapienza University , Rome, Italy

5. Department of Biology , University of Tor Vergata, Rome, Italy

Abstract

Abstract In recent years, a huge amount of data on ncRNA interactions has been described in scientific papers and databases. Although considerable effort has been made to annotate the available knowledge in public repositories, there are still significant discrepancies in how different resources capture and interpret data on ncRNA functional and physical associations. In the present paper, we present a collection of microRNA–mRNA interactions annotated from the scientific literature following recognized standard criteria and focused on microRNAs, which regulate genes associated with rare diseases as a case study. The list of protein-coding genes with a known role in specific rare diseases was retrieved from the Genome England PanelApp, and associated microRNA–mRNA interactions were annotated in the IntAct database and compared with other datasets. RNAcentral identifiers were used for unambiguous, stable identification of ncRNAs. The information about the interaction was enhanced by a detailed description of the cell types and experimental conditions, providing a computer-interpretable summary of the published data, integrated with the huge amount of protein interactions already gathered in the database. Furthermore, for each interaction, the binding sites of the microRNA are precisely mapped on a well-defined mRNA transcript of the target gene. This information is crucial to conceive and design optimal microRNA mimics or inhibitors to interfere in vivo with a deregulated process. As these approaches become more feasible, high-quality, reliable networks of microRNA interactions are needed to help, for instance, in the selection of the best target to be inhibited and to predict potential secondary off-target effects. Database URL https://www.ebi.ac.uk/intact

Funder

European Joint Programme on Rare Diseases

National Heart, Lung, and Blood Institute

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

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