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      Identification of common differentially expressed genes in Turner (45,X) and Klinefelter (47,XXY) syndromes using bioinformatics analysis

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          Abstract

          Background

          Analysis of patients with chromosomal abnormalities, including Turner syndrome and Klinefelter syndrome, has highlighted the importance of X‐linked gene dosage as a contributing factor for disease susceptibility. Escape from X‐inactivation and X‐linked imprinting can result in transcriptional differences between normal men and women as well as in patients with sex chromosome abnormalities.

          Objective

          To identify differentially expressed genes among patients with Turner (45,X) and Klinefelter (46,XXY) syndrome using bioinformatics analysis.

          Methodology

          Two gene expression data sets of Turner (45,X) and Klinefelter syndrome (47,XXY) were obtained from the Gene Omnibus Expression (GEO) database of the National Center for Biotechnology Information (NCBI). Statistical analysis was performed using R Bioconductor libraries. Differentially expressed genes (DEGs) were determined using significance analysis of microarray (SAM). The functional annotation of the DEGs was performed with DAVID v6.8 (The Database for Annotation, Visualization, and Integrated Discovery).

          Results

          There are no genes over‐expressed simultaneously in both diseases. However, when crossing the list of under‐expressed genes for 45,X cells and the list of over‐expressed genes for 47,XXY cells, there are 16 common genes: SLC25A6, AKAP17A, ASMTL, KDM5C, KDM6A, ATRX, CSF2RA, DHRSX, CD99, ZBED1, EIF1AX, MVB12B, SMC1A, P2RY8, DOCK7, DDX3X, eight of which are involved in the regulation of gene expression by epigenetic mechanisms, regulation of splicing processes and protein synthesis.

          Conclusion

          Of the 16 identified as under‐expressed in 45,X cells and over‐expressed in 47,XXY cells, 14 are located in X chromosome and 2 in autosomal chromosome; 8 of these genes are involved in the regulation of gene expression: 5 genes are related to epigenetic mechanisms, 2 in regulation of splicing processes, and 1 in the protein synthesis process. Our results are limited by it being the product of a bioinformatic analysis from mRNA isolated from whole blood, this makes necessary further exploration of the relationships between these genes and Turner syndrome and Klinefelter syndrome in the future.

          Abstract

          In this manuscript we identify differentially expressed genes among patients with Turner and Klinefelter syndrome. Our results suggest that global epigenetic and RNA expression changes play a central role to the phenotype.

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          Most cited references39

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Significance analysis of microarrays applied to the ionizing radiation response.

            Microarrays can measure the expression of thousands of genes to identify changes in expression between different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. We describe a method, Significance Analysis of Microarrays (SAM), that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements. For genes with scores greater than an adjustable threshold, SAM uses permutations of the repeated measurements to estimate the percentage of genes identified by chance, the false discovery rate (FDR). When the transcriptional response of human cells to ionizing radiation was measured by microarrays, SAM identified 34 genes that changed at least 1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and 84% by using conventional methods of analysis. Of the 34 genes, 19 were involved in cell cycle regulation and 3 in apoptosis. Surprisingly, four nucleotide excision repair genes were induced, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.
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              • Record: found
              • Abstract: found
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              Is Open Access

              DAVID-WS: a stateful web service to facilitate gene/protein list analysis

              Summary: The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of ∼1200 gene lists from ∼400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions. Availability: The web service and sample clients (written in Java, Perl, Python and Matlab) are made freely available under the DAVID License at http://david.abcc.ncifcrf.gov/content.jsp?file=WS.html. Contact: xiaoli.jiao@nih.gov; rlempicki@nih.gov
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                Author and article information

                Contributors
                rojas-adriana@javeriana.edu.co
                Journal
                Mol Genet Genomic Med
                Mol Genet Genomic Med
                10.1002/(ISSN)2324-9269
                MGG3
                Molecular Genetics & Genomic Medicine
                John Wiley and Sons Inc. (Hoboken )
                2324-9269
                21 September 2020
                November 2020
                : 8
                : 11 ( doiID: 10.1002/mgg3.v8.11 )
                : e1503
                Affiliations
                [ 1 ] Institute of Human Genetics. Faculty of Medicine Pontificia Universidad Javeriana Bogotá Colombia
                [ 2 ] Department of Statistics Faculty of Science Universidad Nacional de Colombia Ciudad Universitaria Bogotá Colombia
                Author notes
                [*] [* ] Correspondence

                Adriana Rojas, Institute of Human Genetics, Faculty of Medicine, Pontificia Universidad Javeriana, Cra. 7 No. 40-62, Bogotá 110231, Colombia.

                Email: rojas-adriana@ 123456javeriana.edu.co

                Author information
                https://orcid.org/0000-0002-4900-4948
                https://orcid.org/0000-0002-3433-272X
                https://orcid.org/0000-0001-9325-9529
                https://orcid.org/0000-0003-1005-2210
                https://orcid.org/0000-0002-0826-6191
                https://orcid.org/0000-0001-8528-4433
                Article
                MGG31503
                10.1002/mgg3.1503
                7667333
                32959501
                1b0dba32-f9cc-4419-887b-f8a1271de693
                © 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals LLC.

                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
                : 08 April 2020
                : 14 August 2020
                : 30 August 2020
                Page count
                Figures: 3, Tables: 1, Pages: 10, Words: 5929
                Funding
                Funded by: Pontificia Universidad Javeriana , open-funder-registry 10.13039/501100009543;
                Award ID: ID9369
                Funded by: Hospital Universitario San Ignacio
                Award ID: HUSI2017/171
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                November 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.4 mode:remove_FC converted:16.11.2020

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