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      Age-associated increased stiffness of the ovarian microenvironment impairs follicle development and oocyte quality and rapidly alters follicle gene expression

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          Abstract

          In humans, aging triggers cellular and tissue deterioration, and the female reproductive system is the first to show signs of decline. Reproductive aging is associated with decreased ovarian reserve, decreased quality of the remaining oocytes, and decreased production of the ovarian hormones estrogen and progesterone. With aging, both mouse and human ovaries become pro-fibrotic and stiff. However, whether stiffness directly impairs ovarian function, folliculogenesis, and oocyte quality is unknown. To answer this question, we cultured mouse follicles in alginate gels that mimicked the stiffness of reproductively young and old ovaries. Follicles cultured in stiff hydrogels exhibited decreased survival and growth, decreased granulosa cell viability and estradiol synthesis, and decreased oocyte quality. We also observed a reduction in the number of granulosa cell-oocyte transzonal projections. RNA sequencing revealed early changes in the follicle transcriptome in response to stiffness. Follicles cultured in a stiff environment had lower expression of genes related to follicle development and greater expression of genes related to inflammation and extracellular matrix remodeling than follicles cultured in a soft environment. Altogether, our findings suggest that ovarian stiffness directly modulates folliculogenesis and contributes to the progressive decline in oocyte quantity and quality observed in women of advanced maternal age.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

              DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                2692-8205
                10 June 2024
                : 2024.06.09.598134
                Affiliations
                [1 ]Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO, USA
                Author notes

                Author contribution: S.P. and F.A. designed the methodology, performed experiments, data analysis and visualization, and wrote the manuscript. M.P. Performed TZPs imaging and quantification. F.A. conceived the study, supervised the study, and provided the resources and funding.

                [* ]Correspondence: Farners Amargant i Riera. Washington University in St. Louis, 425 S. Euclid Street, laboratory 10-111. St. Louis, MO 63110. farners@ 123456wustl.edu
                Author information
                http://orcid.org/0000-0003-0300-7657
                http://orcid.org/0000-0002-8273-1434
                Article
                10.1101/2024.06.09.598134
                11195110
                38915651
                9c743f67-d93a-482f-ab09-461cbb3dfea2

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.

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                Funding
                This work was supported by the National Institutes of Health K99/R00 Pathway to Independence Award K99HD108424 (F.A) and Washington University in St. Louis start-up funds (F.A).
                Categories
                Article

                ovarian aging,folliculogenesis,oocyte quality,in vitro 3d culture,biomechanics,stiffness

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