Special Issue "microRNA Bioinformatics"

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cell Nuclei: Function, Transport and Receptors".

Deadline for manuscript submissions: closed (31 October 2020).

Special Issue Editor

Prof. Dr. Y-h. Taguchi
E-Mail Website
Guest Editor

Special Issue Information

Dear Colleagues,

Numerous computational methods have been proposed for studying the highly context-dependent interaction between miRNAs and mRNAs. Various databases for storing this information are continuously being established, and more and more applications are required for identifying new miRNAs in various species. In contrast to proteins and protein-coding RNAs, miRNAs have a greater potential to be targeted by computational methods. For this Special Issue, all kinds of studies related to the development of databases and applications, and investigations of miRNAs using existing applications are encouraged.

Prof. Y-h. Taguchi
Guest Editor

Manuscript Submission Information

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Keywords

  • miRNA target protein
  • miRNA–disease interaction
  • miRNA–protein interaction
  • prediction of miRNA
  • small RNA sequencing
  • seed match
  • miRNA–mRNA inreraction
  • miRNA–long-non coding RNA interaction
  • database
  • inference of target protein
  • interference of target mRNA
  • miRNA expression of tissue

Published Papers (12 papers)

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Research

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Article
A Transcription Regulatory Sequence in the 5′ Untranslated Region of SARS-CoV-2 Is Vital for Virus Replication with an Altered Evolutionary Pattern against Human Inhibitory MicroRNAs
Cells 2021, 10(2), 319; https://doi.org/10.3390/cells10020319 - 04 Feb 2021
Cited by 2 | Viewed by 994
Abstract
Our knowledge of the evolution and the role of untranslated region (UTR) in SARS-CoV-2 pathogenicity is very limited. Leader sequence, originated from UTR, is found at the 5′ ends of all encoded SARS-CoV-2 transcripts, highlighting its importance. Here, evolution of leader sequence was [...] Read more.
Our knowledge of the evolution and the role of untranslated region (UTR) in SARS-CoV-2 pathogenicity is very limited. Leader sequence, originated from UTR, is found at the 5′ ends of all encoded SARS-CoV-2 transcripts, highlighting its importance. Here, evolution of leader sequence was compared between human pathogenic and non-pathogenic coronaviruses. Then, profiling of microRNAs that can inactivate the key UTR regions of coronaviruses was carried out. A distinguished pattern of evolution in leader sequence of SARS-CoV-2 was found. Mining all available microRNA families against leader sequences of coronaviruses resulted in discovery of 39 microRNAs with a stable thermodynamic binding energy. Notably, SARS-CoV-2 had a lower binding stability against microRNAs. hsa-MIR-5004-3p was the only human microRNA able to target the leader sequence of SARS and to a lesser extent, also SARS-CoV-2. However, its binding stability decreased remarkably in SARS-COV-2. We found some plant microRNAs with low and stable binding energy against SARS-COV-2. Meta-analysis documented a significant (p < 0.01) decline in the expression of MIR-5004-3p after SARS-COV-2 infection in trachea, lung biopsy, and bronchial organoids as well as lung-derived Calu-3 and A549 cells. The paucity of the innate human inhibitory microRNAs to bind to leader sequence of SARS-CoV-2 can contribute to its high replication in infected human cells. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
MicroRNAs and Mammarenaviruses: Modulating Cellular Metabolism
Cells 2020, 9(11), 2525; https://doi.org/10.3390/cells9112525 - 23 Nov 2020
Viewed by 634
Abstract
Mammarenaviruses are a diverse genus of emerging viruses that include several causative agents of severe viral hemorrhagic fevers with high mortality in humans. Although these viruses share many similarities, important differences with regard to pathogenicity, type of immune response, and molecular mechanisms during [...] Read more.
Mammarenaviruses are a diverse genus of emerging viruses that include several causative agents of severe viral hemorrhagic fevers with high mortality in humans. Although these viruses share many similarities, important differences with regard to pathogenicity, type of immune response, and molecular mechanisms during virus infection are different between and within New World and Old World viral infections. Viruses rely exclusively on the host cellular machinery to translate their genome, and therefore to replicate and propagate. miRNAs are the crucial factor in diverse biological processes such as antiviral defense, oncogenesis, and cell development. The viral infection can exert a profound impact on the cellular miRNA expression profile, and numerous RNA viruses have been reported to interact directly with cellular miRNAs and/or to use these miRNAs to augment their replication potential. Our present study indicates that mammarenavirus infection induces metabolic reprogramming of host cells, probably manipulating cellular microRNAs. A number of metabolic pathways, including valine, leucine, and isoleucine biosynthesis, d-Glutamine and d-glutamate metabolism, thiamine metabolism, and pools of several amino acids were impacted by the predicted miRNAs that would no longer regulate these pathways. A deeper understanding of mechanisms by which mammarenaviruses handle these signaling pathways is critical for understanding the virus/host interactions and potential diagnostic and therapeutic targets, through the inhibition of specific pathologic metabolic pathways. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
miRTil: An Extensive Repository for Nile Tilapia microRNA Next Generation Sequencing Data
Cells 2020, 9(8), 1752; https://doi.org/10.3390/cells9081752 - 22 Jul 2020
Viewed by 889
Abstract
Nile tilapia is the third most cultivated fish worldwide and a novel model species for evolutionary studies. Aiming to improve productivity and contribute to the selection of traits of economic impact, biotechnological approaches have been intensively applied to species enhancement. In this sense, [...] Read more.
Nile tilapia is the third most cultivated fish worldwide and a novel model species for evolutionary studies. Aiming to improve productivity and contribute to the selection of traits of economic impact, biotechnological approaches have been intensively applied to species enhancement. In this sense, recent studies have focused on the multiple roles played by microRNAs (miRNAs) in the post-transcriptional regulation of protein-coding genes involved in the emergence of phenotypes with relevance for aquaculture. However, there is still a growing demand for a reference resource dedicated to integrating Nile Tilapia miRNA information, obtained from both experimental and in silico approaches, and facilitating the analysis and interpretation of RNA sequencing data. Here, we present an open repository dedicated to Nile Tilapia miRNAs: the “miRTil database”. The database stores data on 734 mature miRNAs identified in 11 distinct tissues and five key developmental stages. The database provides detailed information about miRNA structure, genomic context, predicted targets, expression profiles, and relative 5p/3p arm usage. Additionally, miRTil also includes a comprehensive pre-computed miRNA-target interaction network containing 4936 targets and 19,580 interactions. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Identification of miRNA Master Regulators in Breast Cancer
Cells 2020, 9(7), 1610; https://doi.org/10.3390/cells9071610 - 03 Jul 2020
Cited by 6 | Viewed by 1568
Abstract
Breast cancer is the neoplasm with the highest number of deaths in women. Although the molecular mechanisms associated with the development of this tumor have been widely described, metastatic disease has a high mortality rate. In recent years, several studies show that microRNAs [...] Read more.
Breast cancer is the neoplasm with the highest number of deaths in women. Although the molecular mechanisms associated with the development of this tumor have been widely described, metastatic disease has a high mortality rate. In recent years, several studies show that microRNAs or miRNAs regulate complex processes in different biological systems including cancer. In the present work, we describe a group of 61 miRNAs consistently over-expressed in breast cancer (BC) samples that regulate the breast cancer transcriptome. By means of data mining from TCGA, miRNA and mRNA sequencing data corresponding to 1091 BC patients and 110 normal adjacent tissues were downloaded and a miRNA–mRNA network was inferred. Calculations of their oncogenic activity demonstrated that they were involved in the regulation of classical cancer pathways such as cell cycle, PI3K–AKT, DNA repair, and k-Ras signaling. Using univariate and multivariate analysis, we found that five of these miRNAs could be used as biomarkers for the prognosis of overall survival. Furthermore, we confirmed the over-expression of two of them in 56 locally advanced BC samples obtained from the histopathological archive of the National Cancer Institute of Mexico, showing concordance with our previous bioinformatic analysis. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Substantially Altered Expression Profile of Diabetes/Cardiovascular/Cerebrovascular Disease Associated microRNAs in Children Descending from Pregnancy Complicated by Gestational Diabetes Mellitus—One of Several Possible Reasons for an Increased Cardiovascular Risk
Cells 2020, 9(6), 1557; https://doi.org/10.3390/cells9061557 - 26 Jun 2020
Cited by 5 | Viewed by 1051
Abstract
Gestational diabetes mellitus (GDM), one of the major pregnancy-related complications, characterized as a transitory form of diabetes induced by insulin resistance accompanied by a low/absent pancreatic beta-cell compensatory adaptation to the increased insulin demand, causes the acute, long-term, and transgenerational health complications. The [...] Read more.
Gestational diabetes mellitus (GDM), one of the major pregnancy-related complications, characterized as a transitory form of diabetes induced by insulin resistance accompanied by a low/absent pancreatic beta-cell compensatory adaptation to the increased insulin demand, causes the acute, long-term, and transgenerational health complications. The aim of the study was to assess if alterations in gene expression of microRNAs associated with diabetes/cardiovascular/cerebrovascular diseases are present in whole peripheral blood of children aged 3–11 years descending from GDM complicated pregnancies. A substantially altered microRNA expression profile was found in children descending from GDM complicated pregnancies. Almost all microRNAs with the exception of miR-92a-3p, miR-155-5p, and miR-210-3p were upregulated. The microRNA expression profile also differed between children after normal and GDM complicated pregnancies in relation to the presence of overweight/obesity, prehypertension/hypertension, and/or valve problems and heart defects. Always, screening based on the combination of microRNAs was superior over using individual microRNAs, since at 10.0% false positive rate it was able to identify a large proportion of children with an aberrant microRNA expression profile (88.14% regardless of clinical findings, 75.41% with normal clinical findings, and 96.49% with abnormal clinical findings). In addition, the higher incidence of valve problems and heart defects was found in children with a prior exposure to GDM. The extensive file of predicted targets of all microRNAs aberrantly expressed in children descending from GDM complicated pregnancies indicates that a large group of these genes is involved in ontologies of diabetes/cardiovascular/cerebrovascular diseases. In general, children with a prior exposure to GDM are at higher risk of later development of diabetes mellitus and cardiovascular/cerebrovascular diseases, and would benefit from dispensarisation as well as implementation of primary prevention strategies. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Improved Prediction of miRNA-Disease Associations Based on Matrix Completion with Network Regularization
Cells 2020, 9(4), 881; https://doi.org/10.3390/cells9040881 - 03 Apr 2020
Cited by 3 | Viewed by 1102
Abstract
The identification of potential microRNA (miRNA)-disease associations enables the elucidation of the pathogenesis of complex human diseases owing to the crucial role of miRNAs in various biologic processes and it yields insights into novel prognostic markers. In the consideration of the time and [...] Read more.
The identification of potential microRNA (miRNA)-disease associations enables the elucidation of the pathogenesis of complex human diseases owing to the crucial role of miRNAs in various biologic processes and it yields insights into novel prognostic markers. In the consideration of the time and costs involved in wet experiments, computational models for finding novel miRNA-disease associations would be a great alternative. However, computational models, to date, are biased towards known miRNA-disease associations; this is not suitable for rare miRNAs (i.e., miRNAs with a few known disease associations) and uncommon diseases (i.e., diseases with a few known miRNA associations). This leads to poor prediction accuracies. The most straightforward way of improving the performance is by increasing the number of known miRNA-disease associations. However, due to lack of information, increasing attention has been paid to developing computational models that can handle insufficient data via a technical approach. In this paper, we present a general framework—improved prediction of miRNA-disease associations (IMDN)—based on matrix completion with network regularization to discover potential disease-related miRNAs. The success of adopting matrix factorization is demonstrated by its excellent performance in recommender systems. This approach considers a miRNA network as additional implicit feedback and makes predictions for disease associations relevant to a given miRNA based on its direct neighbors. Our experimental results demonstrate that IMDN achieved excellent performance with reliable area under the receiver operating characteristic (ROC) area under the curve (AUC) values of 0.9162 and 0.8965 in the frameworks of global and local leave-one-out cross-validations (LOOCV), respectively. Further, case studies demonstrated that our method can not only validate true miRNA-disease associations but also suggest novel disease-related miRNA candidates. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Intragenic MicroRNAs Autoregulate Their Host Genes in Both Direct and Indirect Ways—A Cross-Species Analysis
Cells 2020, 9(1), 232; https://doi.org/10.3390/cells9010232 - 17 Jan 2020
Cited by 4 | Viewed by 1153
Abstract
MicroRNAs (miRNAs) function as master switches for post-transcriptional gene expression. Their genes are either located in the extragenic space or within host genes, but these intragenic miRNA::host gene interactions are largely enigmatic. The aim of this study was to investigate the location and [...] Read more.
MicroRNAs (miRNAs) function as master switches for post-transcriptional gene expression. Their genes are either located in the extragenic space or within host genes, but these intragenic miRNA::host gene interactions are largely enigmatic. The aim of this study was to investigate the location and co-regulation of all to date available miRNA sequences and their host genes in an unbiased computational approach. The majority of miRNAs were located within intronic regions of protein-coding and non-coding genes. These intragenic miRNAs exhibited both increased target probability as well as higher target prediction scores as compared to a model of randomly permutated genes. This was associated with a higher number of miRNA recognition elements for the hosted miRNAs within their host genes. In addition, strong indirect autoregulation of host genes through modulation of functionally connected gene clusters by intragenic miRNAs was demonstrated. In addition to direct miRNA-to-host gene targeting, intragenic miRNAs also appeared to interact with functionally related genes, thus affecting their host gene function through an indirect autoregulatory mechanism. This strongly argues for the biological relevance of autoregulation not only for the host genes themselves but, more importantly, for the entire gene cluster interacting with the host gene. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
The Relationship Between the miRNA Sequence and Disease May be Revealed by Focusing on Hydrogen Bonding Sites in RNA–RNA Interactions
Cells 2019, 8(12), 1615; https://doi.org/10.3390/cells8121615 - 11 Dec 2019
Viewed by 1082
Abstract
MicroRNAs are important genes in biological processes. Although the function of microRNAs has been elucidated, the relationship between the sequence and the disease is not sufficiently clear. It is important to clarify the relationship between the sequence and the disease because it is [...] Read more.
MicroRNAs are important genes in biological processes. Although the function of microRNAs has been elucidated, the relationship between the sequence and the disease is not sufficiently clear. It is important to clarify the relationship between the sequence and the disease because it is possible to clarify the meaning of the microRNA genetic code consisting of four nucleobases. Since seed theory is based on sequences, its development can be expected to reveal the meaning of microRNA sequences. However, this method has many false positives and false negatives. On the other hand, disease-related microRNA searches using network analysis are not based on sequences, so it is difficult to clarify the relationship between sequences and diseases. Therefore, RNA–RNA interactions which are caused by hydrogen bonding were focused on. As a result, it was clarified that sequences and diseases were highly correlated by calculating the electric field in microRNA which is considered as the torus. It was also suggested that four diseases with different major classifications can be distinguished. Conventionally, RNA was interpreted as a one-dimensional array of four nucleobases, but a new approach to RNA from this study can be expected to provide a new perspective on RNA-RNA interactions. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Identification of Transcriptional Markers and microRNA–mRNA Regulatory Networks in Colon Cancer by Integrative Analysis of mRNA and microRNA Expression Profiles in Colon Tumor Stroma
Cells 2019, 8(9), 1054; https://doi.org/10.3390/cells8091054 - 08 Sep 2019
Cited by 7 | Viewed by 1813
Abstract
The aberrant expression of microRNAs (miRNAs) and genes in tumor microenvironment (TME) has been associated with the pathogenesis of colon cancer. An integrative exploration of transcriptional markers (gene signatures) and miRNA–mRNA regulatory networks in colon tumor stroma (CTS) remains lacking. Using two datasets [...] Read more.
The aberrant expression of microRNAs (miRNAs) and genes in tumor microenvironment (TME) has been associated with the pathogenesis of colon cancer. An integrative exploration of transcriptional markers (gene signatures) and miRNA–mRNA regulatory networks in colon tumor stroma (CTS) remains lacking. Using two datasets of mRNA and miRNA expression profiling in CTS, we identified differentially expressed miRNAs (DEmiRs) and differentially expressed genes (DEGs) between CTS and normal stroma. Furthermore, we identified the transcriptional markers which were both gene targets of DEmiRs and hub genes in the protein–protein interaction (PPI) network of DEGs. Moreover, we investigated the associations between the transcriptional markers and tumor immunity in colon cancer. We identified 17 upregulated and seven downregulated DEmiRs in CTS relative to normal stroma based on a miRNA expression profiling dataset. Pathway analysis revealed that the downregulated DEmiRs were significantly involved in 25 KEGG pathways (such as TGF-β, Wnt, cell adhesion molecules, and cytokine–cytokine receptor interaction), and the upregulated DEmiRs were involved in 10 pathways (such as extracellular matrix (ECM)-receptor interaction and proteoglycans in cancer). Moreover, we identified 460 DEGs in CTS versus normal stroma by a meta-analysis of two gene expression profiling datasets. Among them, eight upregulated DEGs were both hub genes in the PPI network of DEGs and target genes of the downregulated DEmiRs. We found that three of the eight DEGs were negative prognostic factors consistently in two colon cancer cohorts, including COL5A2, EDNRA, and OLR1. The identification of transcriptional markers and miRNA–mRNA regulatory networks in CTS may provide insights into the mechanism of tumor immune microenvironment regulation in colon cancer. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Article
Prediction of Potential miRNA–Disease Associations Through a Novel Unsupervised Deep Learning Framework with Variational Autoencoder
Cells 2019, 8(9), 1040; https://doi.org/10.3390/cells8091040 - 06 Sep 2019
Cited by 11 | Viewed by 1922
Abstract
The important role of microRNAs (miRNAs) in the formation, development, diagnosis, and treatment of diseases has attracted much attention among researchers recently. In this study, we present an unsupervised deep learning model of the variational autoencoder for MiRNA–disease association prediction (VAEMDA). Through combining [...] Read more.
The important role of microRNAs (miRNAs) in the formation, development, diagnosis, and treatment of diseases has attracted much attention among researchers recently. In this study, we present an unsupervised deep learning model of the variational autoencoder for MiRNA–disease association prediction (VAEMDA). Through combining the integrated miRNA similarity and the integrated disease similarity with known miRNA–disease associations, respectively, we constructed two spliced matrices. These matrices were applied to train the variational autoencoder (VAE), respectively. The final predicted association scores between miRNAs and diseases were obtained by integrating the scores from the two trained VAE models. Unlike previous models, VAEMDA can avoid noise introduced by the random selection of negative samples and reveal associations between miRNAs and diseases from the perspective of data distribution. Compared with previous methods, VAEMDA obtained higher area under the receiver operating characteristics curves (AUCs) of 0.9118, 0.8652, and 0.9091 ± 0.0065 in global leave-one-out cross validation (LOOCV), local LOOCV, and five-fold cross validation, respectively. Further, the AUCs of VAEMDA were 0.8250 and 0.8237 in global leave-one-disease-out cross validation (LODOCV), and local LODOCV, respectively. In three different types of case studies on three important diseases, the results showed that most of the top 50 potentially associated miRNAs were verified by databases and the literature. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Review

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Review
Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers
Cells 2020, 9(8), 1837; https://doi.org/10.3390/cells9081837 - 05 Aug 2020
Cited by 8 | Viewed by 1650
Abstract
Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures [...] Read more.
Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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Data Descriptor
GEDS: A Gene Expression Display Server for mRNAs, miRNAs and Proteins
Cells 2019, 8(7), 675; https://doi.org/10.3390/cells8070675 - 03 Jul 2019
Cited by 10 | Viewed by 2299
Abstract
High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could [...] Read more.
High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23,315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available online. Full article
(This article belongs to the Special Issue microRNA Bioinformatics)
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