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      Estrogen Receptor Alpha (ESR1)-Dependent Regulation of the Mouse Oviductal Transcriptome

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          Abstract

          Estrogen receptor-α (ESR1) is an important transcriptional regulator in the mammalian oviduct, however ESR1-dependent regulation of the transcriptome of this organ is not well defined, especially at the genomic level. The objective of this study was therefore to investigate estradiol- and ESR1-dependent regulation of the transcriptome of the oviduct using transgenic mice, both with (ESR1KO) and without (wild-type, WT) a global deletion of ESR1. Oviducts were collected from ESR1KO and WT littermates at 23 days of age, or ESR1KO and WT mice were treated with 5 IU PMSG to stimulate follicular development and the production of ovarian estradiol, and the oviducts collected 48 h later. RNA extracted from whole oviducts was hybridized to Affymetrix Genechip Mouse Genome 430–2.0 arrays (n = 3 arrays per genotype and treatment) or reverse transcribed to cDNA for analysis of the expression of selected mRNAs by real-time PCR. Following microarray analysis, a statistical two-way ANOVA and pairwise comparison (LSD test) revealed 2428 differentially expressed transcripts (DEG’s, P < 0.01). Genotype affected the expression of 2215 genes, treatment (PMSG) affected the expression of 465 genes, and genotype x treatment affected the expression of 438 genes. With the goal of determining estradiol/ESR1-regulated function, gene ontology (GO) and bioinformatic pathway analyses were performed on DEG’s in the oviducts of PMSG-treated ESR1KO versus PMSG-treated WT mice. Significantly enriched GO molecular function categories included binding and catalytic activity. Significantly enriched GO cellular component categories indicated the extracellular region. Significantly enriched GO biological process categories involved a single organism, modulation of a measurable attribute and developmental processes. Bioinformatic analysis revealed ESR1-regulation of the immune response within the oviduct as the primary canonical pathway. In summary, a transcriptomal profile of estradiol- and ESR1-regulated gene expression and related bioinformatic analysis is presented to increase our understanding of how estradiol/ESR1 affects function of the oviduct, and to identify genes that may be proven as important regulators of fertility in the future.

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          Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays

          Background DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. Results In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. Conclusion Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan® Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.
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            Signaling from axon guidance receptors.

            Determining how axon guidance receptors transmit signals to allow precise pathfinding decisions is fundamental to our understanding of nervous system development and may suggest new strategies to promote axon regeneration after injury or disease. Signaling mechanisms that act downstream of four prominent families of axon guidance cues--netrins, semaphorins, ephrins, and slits--have been extensively studied in both invertebrate and vertebrate model systems. Although details of these signaling mechanisms are still fragmentary and there appears to be considerable diversity in how different guidance receptors regulate the motility of the axonal growth cone, a number of common themes have emerged. Here, we review recent insights into how specific receptors for each of these guidance cues engage downstream regulators of the growth cone cytoskeleton to control axon guidance.
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              IL-18 in autoimmunity: review.

              IL-18 is among the cytokines responsible for immune-mediated pathologies and is probably one of the factors that contribute to the pathogenesis of autoimmune diseases. Identification of the causes of uncontrolled IL-18 production and activity in autoimmunity would allow for novel therapeutic targets to effectively block autoimmune activation and inhibit concomitant tissue damage. IL-18 is produced mainly by monocytes/macrophages in response to stimuli of viral/bacterial origin, its production being therefore one of the effects of innate immunity initiated by host-pathogen interaction. In this review, we summarise the evidence supporting both the effector and the pathogenic role of IL-18 in autoimmunity, and propose that the disturbed mechanism of innate immunity, resulting from macrophage activation through innate immunity receptors (TLR/IL-1R family), may be the basis of pathologically high levels of IL-18 production and activation. Unravelling the mechanisms of IL-18 production and activity in autoimmune diseases will allow the identification of targets for more effective therapeutic intervention.
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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
                25 January 2016
                2016
                : 11
                : 1
                : e0147685
                Affiliations
                [1 ]Department of Animal and Food Sciences, University of Kentucky, Lexington, KY 40546, United States of America
                [2 ]Department of Clinical Sciences, University of Kentucky, Lexington, KY 40536, United States of America
                [3 ]Department of Comparative Biosciences, University of Illinois at Urbana-Champaign, Urbana, IL 61802, United States of America
                University of Quebec at Trois-Rivieres, CANADA
                Author notes

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

                Conceived and designed the experiments: PB CK. Performed the experiments: KC RR MJ. Analyzed the data: KC. Contributed reagents/materials/analysis tools: PB CK. Wrote the paper: CK PB.

                Article
                PONE-D-15-38821
                10.1371/journal.pone.0147685
                4725743
                26808832
                e3c8e992-f3ab-48c4-8068-79116a9887b4
                © 2016 Cerny 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
                : 2 September 2015
                : 7 January 2016
                Page count
                Figures: 4, Tables: 8, Pages: 17
                Funding
                This work was supported by National Institutes of Health Grants P20 RR15592 (P.B., C.K.), K12 DA014040 (P.B.), and P01 HD071875 (P.B., C.K.), the University of Kentucky, and Kentucky Agricultural Experiment Station.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Physiology
                Immune Physiology
                Cytokines
                Interleukins
                Medicine and Health Sciences
                Physiology
                Immune Physiology
                Cytokines
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                Biology and Life Sciences
                Immunology
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                Innate Immune System
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                Biology and Life Sciences
                Developmental Biology
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                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Microarrays
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
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                Molecular Biology
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
                Polymerase Chain Reaction
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                Research and Analysis Methods
                Molecular Biology Techniques
                Artificial Gene Amplification and Extension
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                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Coreceptors
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                Genetics
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                Biology and Life Sciences
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                Estradiol
                Custom metadata
                The data (*.cel files) plus the GCRMA-normalized and log2 transformed transcript data (Park Genomics Suite), have been deposited into the Gene Expression Omnibus (National Center for Biotechnology Information) as accession number GSE72614 ( http://www.ncbi.nlm.nih.gov/geo).

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