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      Integrated ordination of miRNA and mRNA expression profiles

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          Abstract

          Background

          Several studies have investigated miRNA and mRNA co-expression to identify regulatory networks at the transcriptional level. A typical finding of these studies is the presence of both negative and positive miRNA-mRNA correlations. Negative correlations are consistent with the expected, faster degradation of target mRNAs, whereas positive correlations denote the existence of feed-forward regulations mediated by transcription factors. Both mechanisms have been characterized at the molecular level, although comprehensive methods to represent miRNA-mRNA correlations are lacking. At present, genome-wide studies are able to assess the expression of more than 1000 mature miRNAs and more than 35,000 well-characterized human genes. Even if studies are generally restricted to a small subset of genes differentially expressed in specific diseases or experimental conditions, the number of potential correlations remains very high, and needs robust multivariate methods to be conveniently summarized by a small set of data.

          Results

          Nonparametric Kendall correlations were calculated between miRNAs and mRNAs differentially expressed in livers of patients with acute liver failure (ALF) using normal livers as controls. Spurious correlations due to the histopathological composition of samples were removed by partial correlations. Correlations were then transformed into distances and processed by multidimensional scaling (MDS) to map the miRNA and mRNA relationships. These showed: (a) a prominent displacement of miRNA and mRNA clusters in ALF livers, as compared to control livers, indicative of gene expression dysregulation; (b) a clustering of mRNAs consistent with their functional annotations [CYP450, transcription factors, complement, proliferation, HLA class II, monocytes/macrophages, T cells, T-NK cells and B cells], as well as a clustering of miRNAs with the same seed sequence; and (c) a tendency of miRNAs and mRNAs to populate distinct regions of the MDS plot. MDS also allowed to visualize the network of miRNA-mRNA target pairs.

          Conclusions

          Different features of miRNA and mRNA relationships can be represented as thematic maps within the framework of MDS obtained from pairwise correlations. The symmetric distribution of positive and negative correlations between miRNA and mRNA expression suggests that miRNAs are involved in a complex bidirectional molecular network, including, but not limited to, the inhibitory regulation of miRNA targets.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-015-1971-9) contains supplementary material, which is available to authorized users.

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          Most cited references22

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Control of translation and mRNA degradation by miRNAs and siRNAs.

            The control of translation and mRNA degradation is an important part of the regulation of gene expression. It is now clear that small RNA molecules are common and effective modulators of gene expression in many eukaryotic cells. These small RNAs that control gene expression can be either endogenous or exogenous micro RNAs (miRNAs) and short interfering RNAs (siRNAs) and can affect mRNA degradation and translation, as well as chromatin structure, thereby having impacts on transcription rates. In this review, we discuss possible mechanisms by which miRNAs control translation and mRNA degradation. An emerging theme is that miRNAs, and siRNAs to some extent, target mRNAs to the general eukaryotic machinery for mRNA degradation and translation control.
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              Singular value decomposition for genome-wide expression data processing and modeling.

              We describe the use of singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.
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                Author and article information

                Contributors
                gdiaz@unica.it
                faustozamboni@aob.it
                ashleytice@gmail.com
                pfarci@niaid.nih.gov
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                12 October 2015
                12 October 2015
                2015
                : 16
                : 767
                Affiliations
                [ ]Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
                [ ]Liver Transplantation Center, Brotzu Hospital, Cagliari, Italy
                [ ]Hepatic Pathogenesis Section, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
                Article
                1971
                10.1186/s12864-015-1971-9
                4603994
                26459852
                d1c9741f-8fed-48d5-a192-f83aa85cdf79
                © Diaz et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 March 2015
                : 2 October 2015
                Categories
                Methodology Article
                Custom metadata
                © The Author(s) 2015

                Genetics
                micrornas,mrna,multidimensional scaling,gene expression,kendall correlation,partial correlations,normal liver,acute liver failure (alf),hepatitis b virus

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