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      A Comprehensive Analysis of miRNA/isomiR Expression with Gender Difference

      research-article
      1 , * , 2 , 3 , 4 , 5 , *
      PLoS ONE
      Public Library of Science

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          Abstract

          Although microRNAs (miRNAs) have been widely studied as epigenetic regulation molecules, fewer studies focus on the gender difference at the miRNA and isomiR expression levels. In this study, we aim to understand the potential relationships between gender difference and miRNA/isomiR expression through a comprehensive analysis of small RNA-sequencing datasets based on different human diseases and tissues. Based on specific samples from males and females, we determined that some miRNAs may be diversely expressed between different tissues and genders. Thus, these miRNAs may exhibit inconsistent and even opposite expression between males and females. According to deregulated miRNA expression profiles, some dominantly expressed miRNA loci were selected to analyze isomiR expression patterns using rates of dominant isomiRs. In some miRNA loci, isomiRs showed statistical significance between tumor and normal samples and between males and females samples, suggesting that isomiR expression patterns are not always invariable but may vary between males and females, as well as among different tissues, tumors, and normal samples. The divergence implicates the fluctuation in the expression of miRNA and its detailed expression at the isomiR levels. The divergence also indicates that gender difference may be an important factor that affects the screening of disease-associated miRNAs and isomiRs. This study suggests that miRNA/isomiR expression and gender difference may be more complex than previously assumed and should be further studied according to specific samples from males or females.

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          Most cited references32

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          IsomiRs--the overlooked repertoire in the dynamic microRNAome.

          The development of deep sequencing has enabled the identification of novel microRNAs (miRNAs), leading to a growing appreciation for the fact that individual miRNAs can be heterogeneous in length and/or sequence. These variants, termed isomiRs, can be expressed in a cell-specific manner, and numerous recent studies suggest that at least some isomiRs may affect target selection, miRNA stability, or loading into the RNA-induced silencing complex (RISC). Reports indicating differential functionality for isomiRs are currently confined to several specific variants, and although isomiRs are common, their broader biological significance is yet to be fully resolved. Here we review the growing body of evidence suggesting that isomiRs have functional differences, of which at least some appear biologically relevant, and caution researchers to take miRNA isoforms into consideration in their experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            A comprehensive survey of 3' animal miRNA modification events and a possible role for 3' adenylation in modulating miRNA targeting effectiveness.

            Animal microRNA sequences are subject to 3' nucleotide addition. Through detailed analysis of deep-sequenced short RNA data sets, we show adenylation and uridylation of miRNA is globally present and conserved across Drosophila and vertebrates. To better understand 3' adenylation function, we deep-sequenced RNA after knockdown of nucleotidyltransferase enzymes. The PAPD4 nucleotidyltransferase adenylates a wide range of miRNA loci, but adenylation does not appear to affect miRNA stability on a genome-wide scale. Adenine addition appears to reduce effectiveness of miRNA targeting of mRNA transcripts while deep-sequencing of RNA bound to immunoprecipitated Argonaute (AGO) subfamily proteins EIF2C1-EIF2C3 revealed substantial reduction of adenine addition in miRNA associated with EIF2C2 and EIF2C3. Our findings show 3' addition events are widespread and conserved across animals, PAPD4 is a primary miRNA adenylating enzyme, and suggest a role for 3' adenine addition in modulating miRNA effectiveness, possibly through interfering with incorporation into the RNA-induced silencing complex (RISC), a regulatory role that would complement the role of miRNA uridylation in blocking DICER1 uptake.
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              Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks.

              MicroRNAs (miRNA) play critical roles in regulating gene expressions at the posttranscriptional levels. The prediction of disease-related miRNA is vital to the further investigation of miRNA's involvement in the pathogenesis of disease. In previous years, biological experimentation is the main method used to identify whether miRNA was associated with a given disease. With increasing biological information and the appearance of new miRNAs every year, experimental identification of disease-related miRNAs poses considerable difficulties (e.g. time-consumption and high cost). Because of the limitations of experimental methods in determining the relationship between miRNAs and diseases, computational methods have been proposed. A key to predict potential disease-related miRNA based on networks is the calculation of similarity among diseases and miRNA over the networks. Different strategies lead to different results. In this review, we summarize the existing computational approaches and present the confronted difficulties that help understand the research status. We also discuss the principles, efficiency and differences among these methods. The comprehensive comparison and discussion elucidated in this work provide constructive insights into the matter.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 May 2016
                2016
                : 11
                : 5
                : e0154955
                Affiliations
                [1 ]Department of Bioinformatics, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, China
                [2 ]Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Science, Nanjing Normal University, Nanjing, China
                [3 ]Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, Institute of Biophysics, Dezhou University, Dezhou, China
                [4 ]School of Computer Science and Technology, Tianjin University, Tianjin, China
                [5 ]State Key Laboratory of Medicinal Chemical Biology, NanKai University, Tianjin, China
                Huazhong University of Science and Technology, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LG QZ. Performed the experiments: LG JFY TML. Analyzed the data: LG JFY QZ. Contributed reagents/materials/analysis tools: TML QZ. Wrote the paper: LG.

                Article
                PONE-D-16-04347
                10.1371/journal.pone.0154955
                4864079
                27167065
                bc750f5e-e4c2-4490-af39-9b5cb67e92b9
                © 2016 Guo et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 March 2016
                : 21 April 2016
                Page count
                Figures: 4, Tables: 2, Pages: 12
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 61301251
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31401009
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 61370010
                Award Recipient :
                This work has been supported by the National Natural Science Foundation of China (Nos. 61301251, 31401009 and 61370010), the Research Fund for the Doctoral Program of Higher Education of China (No. 20133234120009), the National Natural Science Foundation of Jiangsu (No. BK20130885), the Natural Science Foundation of the Jiangsu Higher Education Institutions (No. 13KJB330003), the State Key Laboratory of Medicinal Chemical Biology, Shandong Provincial Key Laboratory of Functional Macromolecular Biophysics, the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and sponsored by NUPTSF (No. NY215068). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                MicroRNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                MicroRNAs
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Sequence Analysis
                Research and Analysis Methods
                Molecular Biology Techniques
                Sequencing Techniques
                Sequence Analysis
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                Sequence analysis
                RNA sequence analysis
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                Sequence analysis
                RNA sequence analysis
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                RNA sequencing
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                RNA sequencing
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Biochemistry
                Tissue Distribution
                Medicine and Health Sciences
                Pharmacology
                Pharmacokinetics
                Tissue Distribution
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Molecular biology assays and analysis techniques
                Nucleic acid analysis
                RNA analysis
                Research and analysis methods
                Molecular biology techniques
                Molecular biology assays and analysis techniques
                Nucleic acid analysis
                RNA analysis
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                All relevant data are within the paper and its Supporting Information files.

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