Identification of key pathways and genes responsible for aggressive behavior. (October 2020)

• Record Type: Journal Article
• Authors: Uddin, Nasir; Hussain, Mushtaq; Rauf, Imran; Zaidi, Syed Farooq
• Is Part Of: Computational biology and chemistry. Volume 88(2020)
• Publication Date: 2020-10
• Subjects: Aggression -- Systems network -- STRING -- Behaviour -- Ubiquitination; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107349
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: A molecular system network has been developed by systematic analysis using the genes and/or proteins known for their role in aggression biology. The molecules were coalesced in terms of modules and their biological roles. In addition, using modules and major interactors, potential novel candidate genes were predicted employing multiple bootstrap replicates. Highlights: From 275 finally selected repertoire of genes, 14 molecular modules were observed. Modules with high gene clustering entail both serotonin and dopamine related pathways. Several novel genes were predicted that potentially contributes in aggression physiology. Abstract: Aggression is a complex behavior, underpinned by cross talk between several biomolecules. To date a composite molecular network of the behavioral disorder has not been constructed. The present study aims to develop the same from the system network analyses recruiting genes with empirical evidence demonstrating their role in the incidence and progression of aggression. In short, 327 genes were recruited in the study after extensive literature survey and subsequent shortlisting by sieving out the comorbidities like cancer and other pathological and physiological ailments, other languages and repeated citations. Subsequent String network analysis coalesces 275 genes in a network with 2223 edges. The developed network was then subjected to delineate modules using MCODE which via gene clustering on the basis of gene ontology segregate all genes into 14 modules. Of these, as expected top 5 modules involved entailing of neuronal signaling pathways with redundant repetitions. Finally, 10 genes (known) were picked randomly, accounting average module size, and subjected to the network analysis with 100, 000 bootstrap replicates. This results in the detection of certain novel genes that lacks empirical evidence for their association with the aggression. Amongst those, most notable are genes involved in protein turnover regulation like UBC, UBA, mitogenic proteins such as Rho and Myc, transcription factors like Tp53 . The findings in turn fill caveats in the molecular resolution of cross talk that underscore the development of aggressive behavior and may then be exploited as screening biomarker and/or therapeutic intervention for aggression.