Bioinformatics analyses of differentially expressed genes associated with spinal cord injury: A microarray-based analysis in a mouse model

Neural Regeneration Research
Lei GuoJi-Jun Liu

Abstract

Gene spectrum analysis has shown that gene expression and signaling pathways change dramatically after spinal cord injury, which may affect the microenvironment of the damaged site. Microarray analysis provides a new opportunity for investigating diagnosis, treatment, and prognosis of spinal cord injury. However, differentially expressed genes are not consistent among studies, and many key genes and signaling pathways have not yet been accurately studied. GSE5296 was retrieved from the Gene Expression Omnibus DataSet. Differentially expressed genes were obtained using R/Bioconductor software (expression changed at least two-fold; P < 0.05). Database for Annotation, Visualization and Integrated Discovery was used for functional annotation of differentially expressed genes and Animal Transcription Factor Database for predicting potential transcription factors. The resulting transcription regulatory protein interaction network was mapped to screen representative genes and investigate their diagnostic and therapeutic value for disease. In total, this study identified 109 genes that were upregulated and 30 that were downregulated at 0.5, 4, and 24 hours, and 3, 7, and 28 days after spinal cord injury. The number of downregulated gen...Continue Reading

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Citations

Jul 30, 2020·Cellular and Molecular Neurobiology·Conghui ZhouXuehong Liu
Jul 18, 2021·International Journal of Urology : Official Journal of the Japanese Urological Association·Nobutaka ShimizuHirotsugu Uemura

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Datasets Mentioned

BETA
GSE5296

Methods Mentioned

BETA
transcription factor prediction

Software Mentioned

SPSS
Cytoscape
Bioconductor
R
gcRobust Average
limma
AnimalTFDB
Search Tool for the Retrieval of Interacting Genes Proteins ( ...
GraphPad Prism
DAVID

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