Methods and Tools in RNA Biology

A special issue of Non-Coding RNA (ISSN 2311-553X).

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 19490

Special Issue Editors


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Guest Editor
Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, DK-2450 Copenhagen, Denmark
Interests: non-coding RNAs; stem cell biology; neuroscience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Advancements in experimental methods and tools have fueled the discovery of non-coding RNAs (e.g., microRNAs, small RNAs, long non-coding RNAs) and epitranscriptomic marks that control the wide variety of RNA metabolisms, including splicing, stability, subcellular localization, and translation. When such generated data are of a transcriptional-wide manner, the power of computers is needed to identify non-coding RNAs and epitranscriptomic marks. Furthermore, this extracted information from the experimental data must be annotated to connect these data to the known information and to further discover novel non-coding RNAs and epitranscriptomic marks. Once these data are converted to the information, further processing of the analyzed data is necessary to disseminate the acquired knowledge to wider audiences so that further scientific discoveries can be made. In this Special Issue, we invite the submission of manuscripts on experimental methods and tools for non-coding RNAs and epitranscriptomic marks as well as computational methods to analyze, annotate, categorize, and/or disseminate to further elucidate the importance of non-coding RNAs and epitranscriptomic marks in cellular activities, tissue developments, and/or pathophysilogies of various organs and organisms.

Dr. Shizuka Uchida
Dr. Mirolyuba Ilieva
Guest Editors

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. Non-Coding RNA is an international peer-reviewed open access semimonthly 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 1800 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

  • non-coding RNA
  • microRNA
  • lncRNA
  • epitranscriptomics
  • RNA
  • metabolism
  • methods
  • computational methods
  • tool

Published Papers (7 papers)

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Editorial

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3 pages, 165 KiB  
Editorial
Methods and Tools in RNA Biology
by Mirolyuba Ilieva and Shizuka Uchida
Non-Coding RNA 2023, 9(4), 46; https://doi.org/10.3390/ncrna9040046 - 10 Aug 2023
Viewed by 1215
Abstract
Breakthroughs in innovative techniques and instruments have driven the exploration of non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) [...] Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)

Research

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24 pages, 4590 KiB  
Article
DoxoDB: A Database for the Expression Analysis of Doxorubicin-Induced lncRNA Genes
by Rebecca Distefano, Mirolyuba Ilieva, Jens Hedelund Madsen, Sarah Rennie and Shizuka Uchida
Non-Coding RNA 2023, 9(4), 39; https://doi.org/10.3390/ncrna9040039 - 13 Jul 2023
Cited by 3 | Viewed by 1873
Abstract
Cancer and cardiovascular disease are the leading causes of death worldwide. Recent evidence suggests that these two life-threatening diseases share several features in disease progression, such as angiogenesis, fibrosis, and immune responses. This has led to the emergence of a new field called [...] Read more.
Cancer and cardiovascular disease are the leading causes of death worldwide. Recent evidence suggests that these two life-threatening diseases share several features in disease progression, such as angiogenesis, fibrosis, and immune responses. This has led to the emergence of a new field called cardio-oncology. Doxorubicin is a chemotherapy drug widely used to treat cancer, such as bladder and breast cancer. However, this drug causes serious side effects, including acute ventricular dysfunction, cardiomyopathy, and heart failure. Based on this evidence, we hypothesize that comparing the expression profiles of cells and tissues treated with doxorubicin may yield new insights into the adverse effects of the drug on cellular activities. To test this hypothesis, we analyzed published RNA sequencing (RNA-seq) data from doxorubicin-treated cells to identify commonly differentially expressed genes, including long non-coding RNAs (lncRNAs) as they are known to be dysregulated in diseased tissues and cells. From our systematic analysis, we identified several doxorubicin-induced genes. To confirm these findings, we treated human cardiac fibroblasts with doxorubicin to record expression changes in the selected doxorubicin-induced genes and performed a loss-of-function experiment of the lncRNA MAP3K4-AS1. To further disseminate the analyzed data, we built the web database DoxoDB. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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11 pages, 1770 KiB  
Article
miRinGO: Prediction of Biological Processes Indirectly Targeted by Human microRNAs
by Mohammed Sayed and Juw Won Park
Non-Coding RNA 2023, 9(1), 11; https://doi.org/10.3390/ncrna9010011 - 22 Jan 2023
Cited by 1 | Viewed by 1999
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that are known for their role in the post-transcriptional regulation of target genes. Typically, their functions are predicted by first identifying their target genes and then finding biological processes enriched in these targets. Current tools for miRNA [...] Read more.
MicroRNAs (miRNAs) are small non-coding RNAs that are known for their role in the post-transcriptional regulation of target genes. Typically, their functions are predicted by first identifying their target genes and then finding biological processes enriched in these targets. Current tools for miRNA functional analysis use only genes with physical binding sites as their targets and exclude other genes that are indirectly targeted transcriptionally through transcription factors. Here, we introduce a method to predict gene ontology (GO) annotations indirectly targeted by microRNAs. The proposed method resulted in better performance in predicting known miRNA-GO term associations compared to the canonical approach. To facilitate miRNA GO enrichment analysis, we developed an R Shiny application, miRinGO, that is freely available online at GitHub. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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16 pages, 4905 KiB  
Article
Systematic Analysis of Long Non-Coding RNA Genes in Nonalcoholic Fatty Liver Disease
by Mirolyuba Ilieva, James Dao, Henry E. Miller, Jens Hedelund Madsen, Alexander J. R. Bishop, Sakari Kauppinen and Shizuka Uchida
Non-Coding RNA 2022, 8(4), 56; https://doi.org/10.3390/ncrna8040056 - 22 Jul 2022
Cited by 9 | Viewed by 3810
Abstract
The largest solid organ in humans, the liver, performs a variety of functions to sustain life. When damaged, cells in the liver can regenerate themselves to maintain normal liver physiology. However, some damage is beyond repair, which necessitates liver transplantation. Increasing rates of [...] Read more.
The largest solid organ in humans, the liver, performs a variety of functions to sustain life. When damaged, cells in the liver can regenerate themselves to maintain normal liver physiology. However, some damage is beyond repair, which necessitates liver transplantation. Increasing rates of obesity, Western diets (i.e., rich in processed carbohydrates and saturated fats), and cardiometabolic diseases are interlinked to liver diseases, including non-alcoholic fatty liver disease (NAFLD), which is a collective term to describe the excess accumulation of fat in the liver of people who drink little to no alcohol. Alarmingly, the prevalence of NAFLD extends to 25% of the world population, which calls for the urgent need to understand the disease mechanism of NAFLD. Here, we performed secondary analyses of published RNA sequencing (RNA-seq) data of NAFLD patients compared to healthy and obese individuals to identify long non-coding RNAs (lncRNAs) that may underly the disease mechanism of NAFLD. Similar to protein-coding genes, many lncRNAs are dysregulated in NAFLD patients compared to healthy and obese individuals, suggesting that understanding the functions of dysregulated lncRNAs may shed light on the pathology of NAFLD. To demonstrate the functional importance of lncRNAs in the liver, loss-of-function experiments were performed for one NAFLD-related lncRNA, LINC01639, which showed that it is involved in the regulation of genes related to apoptosis, TNF/TGF, cytokine signaling, and growth factors as well as genes upregulated in NAFLD. Since there is no lncRNA database focused on the liver, especially NAFLD, we built a web database, LiverDB, to further facilitate functional and mechanistic studies of hepatic lncRNAs. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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17 pages, 2714 KiB  
Article
DisiMiR: Predicting Pathogenic miRNAs Using Network Influence and miRNA Conservation
by Kevin R. Wang and Michael J. McGeachie
Non-Coding RNA 2022, 8(4), 45; https://doi.org/10.3390/ncrna8040045 - 23 Jun 2022
Cited by 2 | Viewed by 2064
Abstract
MiRNAs have been shown to play a powerful regulatory role in the progression of serious diseases, including cancer, Alzheimer’s, and others, raising the possibility of new miRNA-based therapies for these conditions. Current experimental methods, such as differential expression analysis, can discover disease-associated miRNAs, [...] Read more.
MiRNAs have been shown to play a powerful regulatory role in the progression of serious diseases, including cancer, Alzheimer’s, and others, raising the possibility of new miRNA-based therapies for these conditions. Current experimental methods, such as differential expression analysis, can discover disease-associated miRNAs, yet many of these miRNAs play no functional role in disease progression. Interventional experiments used to discover disease causal miRNAs can be time consuming and costly. We present DisiMiR: a novel computational method that predicts pathogenic miRNAs by inferring biological characteristics of pathogenicity, including network influence and evolutionary conservation. DisiMiR separates disease causal miRNAs from merely disease-associated miRNAs, and was accurate in four diseases: breast cancer (0.826 AUC), Alzheimer’s (0.794 AUC), gastric cancer (0.853 AUC), and hepatocellular cancer (0.957 AUC). Additionally, DisiMiR can generate hypotheses effectively: 78.4% of its false positives that are mentioned in the literature have been confirmed to be causal through recently published research. In this work, we show that DisiMiR is a powerful tool that can be used to efficiently and flexibly to predict pathogenic miRNAs in an expression dataset, for the further elucidation of disease mechanisms, and the potential identification of novel drug targets. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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Review

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15 pages, 889 KiB  
Review
Insights into Online microRNA Bioinformatics Tools
by Diana Luna Buitrago, Ruth C. Lovering and Andrea Caporali
Non-Coding RNA 2023, 9(2), 18; https://doi.org/10.3390/ncrna9020018 - 06 Mar 2023
Cited by 4 | Viewed by 4153
Abstract
MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the [...] Read more.
MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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15 pages, 1944 KiB  
Review
Computational Methods to Study DNA:DNA:RNA Triplex Formation by lncRNAs
by Timothy Warwick, Ralf P. Brandes and Matthias S. Leisegang
Non-Coding RNA 2023, 9(1), 10; https://doi.org/10.3390/ncrna9010010 - 21 Jan 2023
Cited by 6 | Viewed by 2934
Abstract
Long non-coding RNAs (lncRNAs) impact cell function via numerous mechanisms. In the nucleus, interactions between lncRNAs and DNA and the consequent formation of non-canonical nucleic acid structures seems to be particularly relevant. Along with interactions between single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA), [...] Read more.
Long non-coding RNAs (lncRNAs) impact cell function via numerous mechanisms. In the nucleus, interactions between lncRNAs and DNA and the consequent formation of non-canonical nucleic acid structures seems to be particularly relevant. Along with interactions between single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA), such as R-loops, ssRNA can also interact with double-stranded DNA (dsDNA) to form DNA:DNA:RNA triplexes. A major challenge in the study of DNA:DNA:RNA triplexes is the identification of the precise RNA component interacting with specific regions of the dsDNA. As this is a crucial step towards understanding lncRNA function, there exist several computational methods designed to predict these sequences. This review summarises the recent progress in the prediction of triplex formation and highlights important DNA:DNA:RNA triplexes. In particular, different prediction tools (Triplexator, LongTarget, TRIPLEXES, Triplex Domain Finder, TriplexFFP, TriplexAligner and Fasim-LongTarget) will be discussed and their use exemplified by selected lncRNAs, whose DNA:DNA:RNA triplex forming potential was validated experimentally. Collectively, these tools revealed that DNA:DNA:RNA triplexes are likely to be numerous and make important contributions to gene expression regulation. Full article
(This article belongs to the Special Issue Methods and Tools in RNA Biology)
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