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      Transcriptome analysis of endometrial tissues following GnRH agonist treatment in a mouse adenomyosis model

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          Abstract

          Purpose

          Adenomyosis is a common, benign gynecological condition of the female reproductive tract characterized by heavy menstrual bleeding and dysmenorrhea. Gonadotropin-releasing hormone (GnRH) agonists are one of the medications used in adenomyosis treatment; however, their underlying mechanisms are poorly understood. Moreover, it is difficult to obtain endometrial samples from women undergoing such treatment. To overcome this, we generated an adenomyosis mouse model, which we treated with an GnRH agonist to determine its effect on pregnancy outcomes. We also analyzed endometrial gene expression following GnRH agonist treatment to determine the mechanisms that may affect pregnancy outcome in individuals with adenomyosis.

          Methods

          Neonatal female mice were divided into a control group, an untreated adenomyosis group, and an adenomyosis group treated with a GnRH agonist (n=6 each). The pregnancy outcome was observed and compared among the groups. Then, three randomly chosen transcriptomes from endometrial tissues from day 4 of pregnancy were analyzed between the adenomyosis group and the GnRH agonist treatment group by RNA sequencing and quantitative reverse transcription polymerase chain reaction (PCR).

          Results

          The litter size was significantly smaller in the adenomyosis group than in the control group (7±0.28 vs 11±0.26; P<0.05). However, the average live litter size was increased (10±0.28 vs 7±0.28; P<0.05) after GnRH agonist treatment. Three hundred and fifty-nine genes were differentially expressed in the GnRH agonist-treated group compared with the untreated group (218 were downregulated and 141 were upregulated). Differentially expressed genes were related to diverse biological processes, including estrogen metabolism, cell cycle, and metabolite biosynthesis.

          Conclusion

          GnRH agonist treatment appears to improve the pregnancy outcome of adenomyosis in a mouse model. Besides pituitary down-regulation, other possible mechanisms such as the regulation of cell proliferation may play a role in this. These new insights into GnRH agonist mechanisms will be useful for future adenomyosis treatment.

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          Most cited references 48

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          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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            Cluster analysis of gene expression dynamics.

            This article presents a Bayesian method for model-based clustering of gene expression dynamics. The method represents gene-expression dynamics as autoregressive equations and uses an agglomerative procedure to search for the most probable set of clusters given the available data. The main contributions of this approach are the ability to take into account the dynamic nature of gene expression time series during clustering and a principled way to identify the number of distinct clusters. As the number of possible clustering models grows exponentially with the number of observed time series, we have devised a distance-based heuristic search procedure able to render the search process feasible. In this way, the method retains the important visualization capability of traditional distance-based clustering and acquires an independent, principled measure to decide when two series are different enough to belong to different clusters. The reliance of this method on an explicit statistical representation of gene expression dynamics makes it possible to use standard statistical techniques to assess the goodness of fit of the resulting model and validate the underlying assumptions. A set of gene-expression time series, collected to study the response of human fibroblasts to serum, is used to identify the properties of the method.
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              Genome-scale analysis of in vivo spatiotemporal promoter activity in Caenorhabditis elegans.

              Differential regulation of gene expression is essential for cell fate specification in metazoans. Characterizing the transcriptional activity of gene promoters, in time and in space, is therefore a critical step toward understanding complex biological systems. Here we present an in vivo spatiotemporal analysis for approximately 900 predicted C. elegans promoters (approximately 5% of the predicted protein-coding genes), each driving the expression of green fluorescent protein (GFP). Using a flow-cytometer adapted for nematode profiling, we generated 'chronograms', two-dimensional representations of fluorescence intensity along the body axis and throughout development from early larvae to adults. Automated comparison and clustering of the obtained in vivo expression patterns show that genes coexpressed in space and time tend to belong to common functional categories. Moreover, integration of this data set with C. elegans protein-protein interactome data sets enables prediction of anatomical and temporal interaction territories between protein partners.
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                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                1177-8881
                2017
                09 March 2017
                : 11
                : 695-704
                Affiliations
                [1 ]Department of Obstetrics and Gynecology, Reproductive Medicine Center, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China
                [2 ]Gynecology, Shanghai Ji Ai Genetics & In Vitro Fertilization Institute, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, People’s Republic of China
                [3 ]Department of Gynecology and Obstetrics, Jinan Military General Hospital, Jinan, People’s Republic of China
                Author notes
                Correspondence: Yijuan Sun, Shanghai Ji Ai Genetics & IVF Institute, Obstetrics and Gynecology Hospital, Fudan University, 588 Fangxie Road, Shanghai 200011, People’s Republic of China, Tel +86 21 6345 5468, Fax +86 21 3318 0478, Email yijuansss@ 123456163.com
                Yun Feng, Department of Obstetrics and Gynecology, Reproductive Medicine Center, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, 197 Rui-Jin 2nd Road, Shanghai 200025, People’s Republic of China, Tel +86 21 6437 4262, Fax +86 21 6437 4262, Email artruijin1@ 123456sina.com
                [*]

                These authors contributed equally to this work

                Article
                dddt-11-695
                10.2147/DDDT.S127889
                5352156
                © 2017 Guo et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Pharmacology & Pharmaceutical medicine

                pregnancy outcome, adenomyosis, rna-seq, mouse, gnrh agonist

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