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      Profiling of Circulating MicroRNAs after a Bout of Acute Resistance Exercise in Humans

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          Abstract

          Recent studies have revealed a new aspect of physiological regulation in which microRNAs (miRNAs) play fundamental roles in diverse biological and pathological processes. Furthermore, it was recently discovered that miRNAs are stably secreted into blood and that circulating miRNAs may play important roles in cell–cell communication. Here, we examined whether the circulating miRNA profile is affected by acute resistance exercise. Twelve males performed a resistance exercise session (bench press and leg press), consisting of five sets of 10 repetitions at 70% of maximum strength, with a 1 min rest between sets. Blood samples were taken before exercise, and at 0 and 60 min, 1 day, and 3 days after exercise. The circulating miRNA profile was determined by microarray analysis. Quantitative real-time PCR confirmed that the miR-149* level increased three days after resistance exercise. In contrast, the miR-146a and miR-221 levels decreased three days after resistance exercise. Our findings suggest that circulating miRNA levels change in response to acute resistance exercise, and miRNAs may play important roles in resistance-exercise-induced adaptation.

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          Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression.

          RNA abundance and DNA copy number are routinely measured in high-throughput using microarray and next-generation sequencing (NGS) technologies, and the attributes of different platforms have been extensively analyzed. Recently, the application of both microarrays and NGS has expanded to include microRNAs (miRNAs), but the relative performance of these methods has not been rigorously characterized. We analyzed three biological samples across six miRNA microarray platforms and compared their hybridization performance. We examined the utility of these platforms, as well as NGS, for the detection of differentially expressed miRNAs. We then validated the results for 89 miRNAs by real-time RT-PCR and challenged the use of this assay as a "gold standard." Finally, we implemented a novel method to evaluate false-positive and false-negative rates for all methods in the absence of a reference method.
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            The Drosophila microRNA Mir-14 suppresses cell death and is required for normal fat metabolism.

            MicroRNAs (miRNAs) are small regulatory RNAs that are between 21 and 25 nucleotides in length and repress gene function through interactions with target mRNAs. The genomes of metazoans encode on the order of several hundred miRNAs, but the processes they regulate have been defined for only two in C. elegans. We searched for new inhibitors of apoptotic cell death by testing existing collections of P element insertion lines for their ability to enhance a small-eye phenotype associated with eye-specific expression of the Drosophila cell death activator Reaper. Here we report the identification of the Drosophila miRNA mir-14 as a cell death suppressor. Loss of mir-14 enhances Reaper-dependent cell death, whereas ectopic expression suppresses cell death induced by multiple stimuli. Animals lacking mir-14 are viable. However, they are stress sensitive and have a reduced lifespan. Mir-14 mutants have elevated levels of the apoptotic effector caspase Drice, suggesting one potential site of action. Mir-14 also regulates fat metabolism. Deletion of mir-14 results in animals with increased levels of triacylglycerol and diacylglycerol, whereas increases in mir-14 copy number have the converse effect. We discuss possible relationships between these phenotypes.
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              Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation.

              Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets. The first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data. The method has been implemented in a publicly available computer package, GENECLUSTER, that performs the analytical calculations and provides easy data visualization. To illustrate the value of such analysis, the approach is applied to hematopoietic differentiation in four well studied models (HL-60, U937, Jurkat, and NB4 cells). Expression patterns of some 6,000 human genes were assayed, and an online database was created. GENECLUSTER was used to organize the genes into biologically relevant clusters that suggest novel hypotheses about hematopoietic differentiation-for example, highlighting certain genes and pathways involved in "differentiation therapy" used in the treatment of acute promyelocytic leukemia.
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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, USA )
                1932-6203
                2013
                29 July 2013
                : 8
                : 7
                : e70823
                Affiliations
                [1 ]Faculty of Sport Sciences, Waseda University, Cooperative Major in Advanced Health Science, Tokyo University of Agriculture and Technology/Waseda University, Tokorozawa, Saitama, Japan
                [2 ]Department of Sports Sciences, Japan Institute of Sports Sciences, Nishigaoka, Tokyo, Japan
                [3 ]Division of Regenerative Medical Engineering, Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, The University of Tokyo, Hongo, Tokyo, Japan
                UT MD Anderson Cancer Center, United States of America
                Author notes

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

                Conceived and designed the experiments: TA. Performed the experiments: SS MK SW. Analyzed the data: SS MK TA. Wrote the paper: TA. Supervision: TU KS.

                Article
                PONE-D-13-09524
                10.1371/journal.pone.0070823
                3726615
                23923026
                6e685ae8-a19b-4e59-b4c9-0cb74b850c7c
                Copyright @ 2013

                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
                : 6 March 2013
                : 23 June 2013
                Page count
                Pages: 8
                Funding
                This study was supported in part by a Grant-in Aid for Scientific Research (A) from the Ministry of Education, Culture, Sports, Science, and Technology, Japan (23240097 to K.S.), and by Grants-in-Aid for Scientific Research from the Japan Institute of Sports Sciences (to M.K.). M.K. was supported by a fellowship from the Japan Society for the Promotion of Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Molecular Genetics
                Gene Expression
                Microarrays
                Genetics
                Epigenetics
                RNA interference
                Gene Expression
                Medicine
                Clinical Immunology
                Immune System
                Cytokines
                Sports and Exercise Medicine

                Uncategorized
                Uncategorized

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