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Differentially expressed gene (DEG) based protein-protein interaction (PPI) network identifies a spectrum of gene interactome, transcriptome and correlated miRNA in nondisjunction Down syndrome.

Authors :
Sriroopreddy, Ramireddy
Sajeed, Rakshanda
P., Raghuraman
C., Sudandiradoss
Source :
International Journal of Biological Macromolecules. Feb2019, Vol. 122, p1080-1089. 10p.
Publication Year :
2019

Abstract

Abstract Down syndrome, a genetic disorder of known attribution reveals several types of brain abnormalities resulting in mental retardation, inadequacy in speech and memory. In this study, we have presented a consolidative network approach to comprehend the intricacy of the associated genes of Down syndrome. In this analysis, the differentially expressed genes (DEG's) were identified and the central networks were constructed as upregulated and downregulated. Subsequently, GNB5, CDC42, SPTAN1, GNG2, GNAZ, PRKACB, SST, CD44, FGF2, PHLPP1, APP, and FYN were identified as the candidate hub genes by using topological parameters. Later, Fpclass a PPI tool identified WASP gene, a co-expression interacting partner with highest network topology. Moreover, an enhanced enrichment pathway namely Opioid signaling was obtained using ClueGo, depicting the roles of the hub genes in signaling and neuronal mechanisms. The transcriptional regulatory factors and the common miRNA connected to them were identified by using MatInspector and miRTarbase. Later, a regulatory network constructed showed that PLAG, T2FB, CREB, NEUR, and GATA were the most commonly connected transcriptional factors and hsa-miR-122-5p was the most prominent miRNA. In a nutshell, these hub genes and the enriched pathway could help understand at a molecular level and eventually used as therapeutic targets for Down syndrome. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01418130
Volume :
122
Database :
Academic Search Index
Journal :
International Journal of Biological Macromolecules
Publication Type :
Academic Journal
Accession number :
133643155
Full Text :
https://doi.org/10.1016/j.ijbiomac.2018.09.056