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      Death Processes in Bovine Theca and Granulosa Cells Modelled and Analysed Using a Systems Biology Approach

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          Abstract

          In this paper, newly discovered mechanisms of atresia and cell death processes in bovine ovarian follicles are investigated. For this purpose the mRNA expression of receptor interacting protein kinases 1 and 3 ( RIPK1 and RIPK3) of the granulosa and theca cells derived from healthy and atretic follicles are studied. The follicles were assigned as either healthy or atretic based on the estradiol to progesterone ratio. A statistically significant difference was recorded for the mRNA expression of a RIPK1 and RIPK3 between granulosa cells from healthy and atretic follicles. To further investigate this result a systems biology approach was used. The genes playing roles in necroptosis, apoptosis and atresia were chosen and a network was created based on human genes annotated by the IMEx database in Cytoscape to identify hubs and bottle-necks. Moreover, correlation networks were built in the Cluepedia plug-in. The networks were created separately for terms describing apoptosis and programmed cell death. We demonstrate that necroptosis (RIPK—dependent cell death pathway) is an alternative mechanism responsible for death of bovine granulosa and theca cells. We conclude that both apoptosis and necroptosis occur in the granulosa cells of dominant follicles undergoing luteinisation and in the theca cells from newly selected follicles.

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          Most cited references54

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          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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            Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

            R. Edgar (2002)
            The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
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              ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

              Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                05 May 2021
                May 2021
                : 22
                : 9
                : 4888
                Affiliations
                [1 ]Mathematical Modelling Research Group, Institute of Technology Sligo, Ash Lane, Sligo, F91 YW50 Sligo, Ireland; m.mcevoy@ 123456pan.olsztyn.pl (M.J.M.); mcafee.marion@ 123456itsligo.ie (M.M.)
                [2 ]Department of Reproductive Immunology and Pathology, Institute of Animal Reproduction and Food Research, Polish Academy of Sciences, Tuwima 10, 10-748 Olsztyn, Poland; a.jonczyk@ 123456pan.olsztyn.pl (A.W.J.); k.piotrowska-tomala@ 123456pan.olsztyn.pl (K.K.P.-T.)
                [3 ]Laboratory of Regenerative Medicine, Department of Neurosurgery, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; emilia.sinderewicz@ 123456uwm.edu.pl
                Author notes
                [* ]Correspondence: creedon.leo@ 123456itsligo.ie (L.C.); d.skarzynski@ 123456pan.olsztyn.pl (D.J.S.); Tel.: +353-71-930-5643 (L.C.); +48-89-539-31-30 (D.J.S.)
                Author information
                https://orcid.org/0000-0002-2363-7579
                https://orcid.org/0000-0001-8259-3441
                https://orcid.org/0000-0002-8798-7455
                https://orcid.org/0000-0002-1434-1215
                https://orcid.org/0000-0002-6867-0823
                https://orcid.org/0000-0001-6989-9243
                https://orcid.org/0000-0001-9537-3560
                Article
                ijms-22-04888
                10.3390/ijms22094888
                8125194
                34063056
                9affeed1-f0b6-4ee2-bbac-6a6f25896bd8
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 24 February 2021
                : 29 April 2021
                Categories
                Article

                Molecular biology
                systems biology,atresia,necroptosis,apoptosis,cluepedia,theca,granulosa,follicle,bovine reproduction

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