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Biomolecules
Special Issues
Bioinformatics Resource and Protocols for Small RNA Research
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Bioinformatics Resource and Protocols for Small RNA Research

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 17017

Special Issue Editor

Dr. Michael Hackenberg

E-Mail Website
Guest Editor
Computational Epigenomics Lab, Department of Genetics, Faculty of Science, University of Granada, 18071 Granada, Spain
Interests: computational genomics; bioinformatics; small RNA detection and prediction; miRNA targets; small RNAs at the interface between parasites and hosts; NGS data analysis; epigenomics; epitranscriptomics

Special Issue Information

Dear colleagues,


Small RNA-based research has experienced a strong increase over the last 15 years. An important event that caused this boost was certainly the advent of high-throughput sequencing methods which facilitate the profiling of known small RNAs, its functional characterization, and the detection of novel sequences.

MicroRNAs were discovered over 25 years ago, and initially, the research focus was on its molecular functions in cell homeostasis through the negative regulation of target genes or by stabilizing gene expression programs during development. Since then, small RNAs have made their way into other research fields like biomedicine as putative therapeutic targets or diagnostic and predictive biomarkers, or in parasitology given their importance at the interface between parasites and hosts. Finally, small RNA research is no longer limited to microRNAs, as other small RNAs like tRNA, snoRNAs or yRNAs seem to produce fragments that might be functional as well.

Bioinformatics methods play an important role in small RNA research; however, frequently, the data analysis or the in silico functional analysis of RNAs are highly parametrized processes, and it is not always easy for the user to select the correct settings. Therefore, in this Special Issue, we seek both original research papers on bioinformatics resources for small RNA research and protocols for already published, well established tools, methods or databases. The protocol papers should be addressed to a non-bioinformatics readership with a clear focus on how to resolve clearly defined biological or biomedical problems. The protocol papers should contain (i) a very brief introduction including the mention of other, similar resources, (ii) discussion of the hardware requirements (if applicable) and instructions on the installation process, and (iii) a clear outline of the biological questions or problems that can be addressed including a discussion of the required input data, main parameters, and output files together with the biological interpretation of the results. The protocol papers should not contain a detailed description of the resource nor a comparison to others, as this should be contained in the original publications.

Assoc. Prof. Michael Hackenberg
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Small RNA data analysis
  • microRNA target prediction and analysis
  • microRNA networks
  • de novo annotation of small RNAs
  • in silico functional analysis of small RNAs

Published Papers (4 papers)

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Research

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12 pages, 1628 KiB  
Article
HumiR: Web Services, Tools and Databases for Exploring Human microRNA Data
by Jeffrey Solomon, Fabian Kern, Tobias Fehlmann, Eckart Meese and Andreas Keller
Biomolecules 2020, 10(11), 1576; https://0-doi-org.brum.beds.ac.uk/10.3390/biom10111576 - 20 Nov 2020
Cited by 5 | Viewed by 3328
Abstract
For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway [...] Read more.
For many research aspects on small non-coding RNAs, especially microRNAs, computational tools and databases are developed. This includes quantification of miRNAs, piRNAs, tRNAs and tRNA fragments, circRNAs and others. Furthermore, the prediction of new miRNAs, isomiRs, arm switch events, target and target pathway prediction and miRNA pathway enrichment are common tasks. Additionally, databases and resources containing expression profiles, e.g., from different tissues, organs or cell types, are generated. This information in turn leads to improved miRNA repositories. While most of the respective tools are implemented in a species-independent manner, we focused on tools for human small non-coding RNAs. This includes four aspects: (1) miRNA analysis tools (2) databases on miRNAs and variations thereof (3) databases on expression profiles (4) miRNA helper tools facilitating frequent tasks such as naming conversion or reporter assay design. Although dependencies between the tools exist and several tools are jointly used in studies, the interoperability is limited. We present HumiR, a joint web presence for our tools. HumiR facilitates an entry in the world of miRNA research, supports the selection of the right tool for a research task and represents the very first step towards a fully integrated knowledge-base for human small non-coding RNA research. We demonstrate the utility of HumiR by performing a very comprehensive analysis of Alzheimer’s miRNAs. Full article
(This article belongs to the Special Issue Bioinformatics Resource and Protocols for Small RNA Research)
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12 pages, 1576 KiB  
Article
High-Throughput Identification of Adapters in Single-Read Sequencing Data
by Asan M.S.H. Mohideen, Steinar D. Johansen and Igor Babiak
Biomolecules 2020, 10(6), 878; https://0-doi-org.brum.beds.ac.uk/10.3390/biom10060878 - 8 Jun 2020
Cited by 4 | Viewed by 3443
Abstract
Sequencing datasets available in public repositories are already high in number, and their growth is exponential. Raw sequencing data files constitute a substantial portion of these data, and they need to be pre-processed for any downstream analyses. The removal of adapter sequences is [...] Read more.
Sequencing datasets available in public repositories are already high in number, and their growth is exponential. Raw sequencing data files constitute a substantial portion of these data, and they need to be pre-processed for any downstream analyses. The removal of adapter sequences is the first essential step. Tools available for the automated detection of adapters in single-read sequencing protocol datasets have certain limitations. To explore these datasets, one needs to retrieve the information on adapter sequences from the methods sections of appropriate research articles. This can be time-consuming in metadata analyses. Moreover, not all research articles provide the information on adapter sequences. We have developed adapt_find, a tool that automates the process of adapter sequences identification in raw single-read sequencing datasets. We have verified adapt_find through testing a number of publicly available datasets. adapt_find secures a robust, reliable and high-throughput process across different sequencing technologies and various adapter designs. It does not need prior knowledge of the adapter sequences. We also produced associated tools: random_mer, for the detection of random N bases either on one or both termini of the reads, and fastqc_parser, for consolidating the results from FASTQC outputs. Together, this is a valuable tool set for metadata analyses on multiple sequencing datasets. Full article
(This article belongs to the Special Issue Bioinformatics Resource and Protocols for Small RNA Research)
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Review

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21 pages, 995 KiB  
Review
isomiRs–Hidden Soldiers in the miRNA Regulatory Army, and How to Find Them?
by Ilias Glogovitis, Galina Yahubyan, Thomas Würdinger, Danijela Koppers-Lalic and Vesselin Baev
Biomolecules 2021, 11(1), 41; https://0-doi-org.brum.beds.ac.uk/10.3390/biom11010041 - 30 Dec 2020
Cited by 11 | Viewed by 4264
Abstract
Numerous studies on microRNAs (miRNA) in cancer and other diseases have been accompanied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep [...] Read more.
Numerous studies on microRNAs (miRNA) in cancer and other diseases have been accompanied by diverse computational approaches and experimental methods to predict and validate miRNA biological and clinical significance as easily accessible disease biomarkers. In recent years, the application of the next-generation deep sequencing for the analysis and discovery of novel RNA biomarkers has clearly shown an expanding repertoire of diverse sequence variants of mature miRNAs, or isomiRs, resulting from alternative post-transcriptional processing events, and affected by (patho)physiological changes, population origin, individual’s gender, and age. Here, we provide an in-depth overview of currently available bioinformatics approaches for the detection and visualization of both mature miRNA and cognate isomiR sequences. An attempt has been made to present in a systematic way the advantages and downsides of in silico approaches in terms of their sensitivity and accuracy performance, as well as used methods, workflows, and processing steps, and end output dataset overlapping issues. The focus is given to the challenges and pitfalls of isomiR expression analysis. Specifically, we address the availability of tools enabling research without extensive bioinformatics background to explore this fascinating corner of the small RNAome universe that may facilitate the discovery of new and more reliable disease biomarkers. Full article
(This article belongs to the Special Issue Bioinformatics Resource and Protocols for Small RNA Research)
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16 pages, 708 KiB  
Review
Computational Methods and Software Tools for Functional Analysis of miRNA Data
by Adrian Garcia-Moreno and Pedro Carmona-Saez
Biomolecules 2020, 10(9), 1252; https://0-doi-org.brum.beds.ac.uk/10.3390/biom10091252 - 28 Aug 2020
Cited by 9 | Viewed by 5297
Abstract
miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in [...] Read more.
miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs. Full article
(This article belongs to the Special Issue Bioinformatics Resource and Protocols for Small RNA Research)
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