National Academy of Agricultural Sciences (NAAS)
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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Down syndrome (DS) is a widespread genetic disorder associated with a range of physical and intellectual disabilities, and it can also lead to several metabolic and health-related issues. Modernization and technological innovation have simplified next-generation sequencing through the use of open-source online software like Galaxy, which enables users to easily share their data and workflow mappings. Current study is to identify candidate genes for DS by performing differential expression of genes. RNA-Seq analysis was performed for different datasets retrieved from the GEO database. The 10 datasets from DS patients and 10 datasets from healthy control were analysed for differentially expressed genes (DEGs). DEGs analysis showed 10 upregulated and 10 downregulated genes with log2FC counts > 2.5 and p-values <0.05. To further investigate these differentially expressed genes (DEGs), WebGestalt was used for comprehensive in silico analysis, visualizing enrichment via volcano plots. Additionally, protein-protein interaction (PPI) networks were constructed using STRING, identifying three gene modules and ten hub genes through Cytoscape cluster analysis. Molecular docking studies were then conducted on these hub genes using PyRx software. This included the addition of polar hydrogen atoms, the assignment of partial charges, and the removal of water molecules to prepare for efficient molecular docking. This research enhances our understanding of gene interactions and protein-phytochemical binding mechanisms, thereby contributing to therapeutic advancements in the biopharmaceutical sector.
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