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Microarray analysis reveals key genes and pathways in Tetralogy of Fallot
The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched cont...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548054/ https://www.ncbi.nlm.nih.gov/pubmed/28713939 http://dx.doi.org/10.3892/mmr.2017.6933 |
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author | He, Yue-E Qiu, Hui-Xian Jiang, Jian-Bing Wu, Rong-Zhou Xiang, Ru-Lian Zhang, Yuan-Hai |
author_facet | He, Yue-E Qiu, Hui-Xian Jiang, Jian-Bing Wu, Rong-Zhou Xiang, Ru-Lian Zhang, Yuan-Hai |
author_sort | He, Yue-E |
collection | PubMed |
description | The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log(2) fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF. |
format | Online Article Text |
id | pubmed-5548054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-55480542017-10-24 Microarray analysis reveals key genes and pathways in Tetralogy of Fallot He, Yue-E Qiu, Hui-Xian Jiang, Jian-Bing Wu, Rong-Zhou Xiang, Ru-Lian Zhang, Yuan-Hai Mol Med Rep Articles The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age-matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t-test, and the R/limma package, with a log(2) fold-change of >2 and a false discovery rate of <0.01 set as thresholds. The biological functions of DEGs were analyzed using the ToppGene database. The ReactomeFIViz application was used to construct functional interaction (FI) networks, and the genes in each module were subjected to pathway enrichment analysis. The iRegulon plugin was used to identify transcription factors predicted to regulate the DEGs in the FI network, and the gene-transcription factor pairs were then visualized using Cytoscape software. A total of 878 DEGs were identified, including 848 upregulated genes and 30 downregulated genes. The gene FI network contained seven function modules, which were all comprised of upregulated genes. Genes enriched in Module 1 were enriched in the following three neurological disorder-associated signaling pathways: Parkinson's disease, Alzheimer's disease and Huntington's disease. Genes in Modules 0, 3 and 5 were dominantly enriched in pathways associated with ribosomes and protein translation. The Xbox binding protein 1 transcription factor was demonstrated to be involved in the regulation of genes encoding the subunits of cytoplasmic and mitochondrial ribosomes, as well as genes involved in neurodegenerative disorders. Therefore, dysfunction of genes involved in signaling pathways associated with neurodegenerative disorders, ribosome function and protein translation may contribute to the pathogenesis of TOF. D.A. Spandidos 2017-09 2017-07-06 /pmc/articles/PMC5548054/ /pubmed/28713939 http://dx.doi.org/10.3892/mmr.2017.6933 Text en Copyright: © He et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles He, Yue-E Qiu, Hui-Xian Jiang, Jian-Bing Wu, Rong-Zhou Xiang, Ru-Lian Zhang, Yuan-Hai Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title | Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title_full | Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title_fullStr | Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title_full_unstemmed | Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title_short | Microarray analysis reveals key genes and pathways in Tetralogy of Fallot |
title_sort | microarray analysis reveals key genes and pathways in tetralogy of fallot |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5548054/ https://www.ncbi.nlm.nih.gov/pubmed/28713939 http://dx.doi.org/10.3892/mmr.2017.6933 |
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