bioRxivBioinformaticsPreprint
Identification of differentially expressed genes and enriched pathways in inflammatory bowel disease using bioinformatics and next generation sequencing data analysis
Basavaraj Mallikarjunayya VastradiD, Chanabasayya Mallikarjunayya VastradiD
Abstract
Inflammatory bowel disease (IBD) is the most common chronic digestive disorders and inflammation in the gastrointestinal tract globally that is characterized by episodes of abdominal pain, diarrhea, bloody stools and weight loss. However, the pathophysiologic mechanisms of IBD have not been thoroughly investigated. To explore potential targets for treatment of IBD, we reorganized and analyzed next generation sequencing (NGS) dataset (GSE186507). The R package DESeq2 tool was used to screen for differentially expressed genes (DEGs) between IBD and normal control samples. We used the g:Profiler database to perform Gene Ontology (GO) enrichment analysis and the REACTOME for pathway enrichment analysis. Protein-protein interaction (PPI) network construction and module analysis were performed to elucidate molecular mechanisms of DEGs and screen hub genes. Then miRNA-hub gene regulatory network and TF-hub gene regulatory network of these hub genes were visualized by Cytoscape. We also validated the identified hub genes via receiver operating characteristic (ROC) curve analysis. A total of 957 DEGs (478 up regulated genes and 479 down regulated genes) were detected in NGS dataset. And they were mainly enriched in the terms of multicellular organismal process, response to stimulus, GPCR ligand binding and immune system. Based on the data of PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network the top hub genes were ranked, including IL7R, ERBB2, SMAD1, RPS26, TLE1, HNF4A, CDKN1A, SRPK1, H3C12 and SFN. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the development and progression of IDB, and certain novel genes might be used as candidate target molecules to diagnose, monitor and treat IDB.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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