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      A transcriptomics model of estrogen action in the ovine fetal hypothalamus: evidence for estrogenic effects of ICI 182,780

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          Abstract

          Estradiol plays a critical role in stimulating the fetal hypothalamus–pituitary–adrenal axis at the end of gestation. Estradiol action is mediated through nuclear and membrane receptors that can be modulated by ICI 182,780, a pure antiestrogen compound. The objective of this study was to evaluate the transcriptomic profile of estradiol and ICI 182,780, testing the hypothesis that ICI 182,780 antagonizes the action of estradiol in the fetal hypothalamus. Chronically catheterized ovine fetuses were infused for 48 h with: vehicle (Control, n = 6), 17 β‐estradiol 500  μg/kg/day (Estradiol, n = 4), ICI 182,780 5  μg/kg/day ( ICIμg, n = 4) and ICI 182,780 5 mg/kg/day ( ICI 5 mg, n = 5). Fetal hypothalami were collected afterward, and gene expression was measured through microarray. Statistical analysis of transcriptomic data was performed with Bioconductor‐R and Cytoscape software. Unexpectedly, 35% and 15.5% of the upregulated differentially expressed genes ( DEG) by Estradiol significantly overlapped ( P < 0.05) with upregulated DEG by ICI 5 mg and ICIμg, respectively. For the downregulated DEG, these percentages were 29.9% and 15.5%, respectively. There was almost no overlap for DEG following opposite directions between Estradiol and ICI ICI 5 mg or ICIμg. Furthermore, most of the genes in the estrogen signaling pathway – after activation of the epidermal growth factor receptor – followed the same direction in Estradiol, ICIμg or ICI 5 mg compared to Control. In conclusion, estradiol and ICI 182,780 have estrogenic genomic effects in the developing brain, suggesting the possibility that the major action of estradiol on the fetal hypothalamus involves another receptor system rather than estrogen receptors.

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          Detecting overlapping protein complexes in protein-protein interaction networks.

          We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a high extent of functional homogeneity.
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            Linear models and empirical bayes methods for assessing differential expression in microarray experiments.

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              KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor

              Motivation: KEGG PATHWAY is a service of Kyoto Encyclopedia of Genes and Genomes (KEGG), constructing manually curated pathway maps that represent current knowledge on biological networks in graph models. While valuable graph tools have been implemented in R/Bioconductor, to our knowledge there is currently no software package to parse and analyze KEGG pathways with graph theory. Results: We introduce the software package KEGGgraph in R and Bioconductor, an interface between KEGG pathways and graph models as well as a collection of tools for these graphs. Superior to existing approaches, KEGGgraph captures the pathway topology and allows further analysis or dissection of pathway graphs. We demonstrate the use of the package by the case study of analyzing human pancreatic cancer pathway. Availability:KEGGgraph is freely available at the Bioconductor web site (http://www.bioconductor.org). KGML files can be downloaded from KEGG FTP site (ftp://ftp.genome.jp/pub/kegg/xml). Contact: j.zhang@dkfz-heidelberg.de Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                woodc@ufl.edu
                Journal
                Physiol Rep
                Physiol Rep
                10.1002/(ISSN)2051-817X
                PHY2
                physreports
                Physiological Reports
                John Wiley and Sons Inc. (Hoboken )
                2051-817X
                16 September 2018
                September 2018
                : 6
                : 18 ( doiID: 10.1002/phy2.2018.6.issue-18 )
                : e13871
                Affiliations
                [ 1 ] Department of Physiology and Functional Genomics College of Medicine University of Florida Gainesville Florida USA
                [ 2 ] Pharmacodynamics College of Pharmacy University of Florida Gainesville Florida USA
                Author notes
                [*] [* ] Correspondence

                Charles E. Wood, Department of Physiology and Functional Genomics, College of Medicine, University of Florida, PO Box 100274, Gainesville, FL 32610‐0274, USA.

                Tel: (352)‐294‐5064

                Fax: (352)‐846‐0270

                E‐mail: woodc@ 123456ufl.edu

                Article
                PHY213871
                10.14814/phy2.13871
                6139289
                30221477
                7bb9f72c-5bc1-4722-8db9-83a08ef74e01
                © 2018 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 August 2018
                : 28 August 2018
                Page count
                Figures: 4, Tables: 1, Pages: 14, Words: 7681
                Funding
                Funded by: University of Florida Opportunity Fund
                Funded by: Eunice Kennedy Shriver National Institute of Child Health and Human Development
                Award ID: HD057561
                Funded by: National Institute of Environmental Health Sciences
                Award ID: ES019651
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                phy213871
                September 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.7.1 mode:remove_FC converted:16.09.2018

                brain development,estrogen signaling pathway,fetal programming,microarray

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