Open AccessBioinformatics analysis of the molecular mechanism underlying Huntington's disease
Author(s) -
Zhimin Wang,
Xiaoyu Dong,
Shuyan Cong
Publication year - 2019
Publication title -
journal of integrative neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.336
H-Index - 33
eISSN - 1757-448X
pISSN - 0219-6352
DOI - 10.31083/j.jin.2019.04.1176
Subject(s) - kegg , gene , huntington's disease , biology , gene expression , genome , genetics , disease , computational biology , bioinformatics , transcriptome , medicine , pathology
We explore the underlying molecular mechanisms and to identify key molecules in Huntington's disease by utilizing bioinformatics methods. The gene expression profile of GSE3621 was extracted from the gene expression omnibus. Differentially expressed genes between the R6/1 transgenic mouse model of Huntington's disease and controls at different time points were screened by limma package in R. Kyoto encyclopedia of genes and genomes database. It was used to analyze the pathways of differentially expressed genes. A searching tool of the protein-protein interaction network was constructed and visualized by Cytoscape. Molecular complex detection was utilized to performed module analysis. There were 513, 483, and 528 differentially expressed genes identified at weeks 18, 22 and 27, respectively, when compared with the control samples. Also, 24 significantly enriched R. Kyoto encyclopedia of genes and genomes database pathways were identified (9 in week 18, 6 in week 22, 9 in week 27), and 31 significant modules were identified from the protein-protein interaction network (13 in week 18, 8 in week 22, 10 in week 27). Hoxd8, Atf3, and Egr2 were confirmed as transcription factors related to Huntington's disease. There are widespread gene expression changes in Huntington's disease at different time points. Some hub genes, such as Usp18, Oasl2, and Rtp4, may play important roles in the pathogenesis of Huntington's disease.