Identification of key pathways and genes responsible for aggressive behavior.


Journal

Computational biology and chemistry
ISSN: 1476-928X
Titre abrégé: Comput Biol Chem
Pays: England
ID NLM: 101157394

Informations de publication

Date de publication:
Oct 2020
Historique:
received: 29 04 2019
revised: 03 03 2020
accepted: 26 07 2020
pubmed: 9 8 2020
medline: 21 5 2021
entrez: 9 8 2020
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 32763796
pii: S1476-9271(19)30387-1
doi: 10.1016/j.compbiolchem.2020.107349
pii:
doi:

Substances chimiques

Protein Aggregates 0
Transcription Factors 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

107349

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Nasir Uddin (N)

Department of Computer Science, IBA, Karachi, Pakistan. Electronic address: nuddin@iba.edu.pk.

Mushtaq Hussain (M)

Bioinformatics and Molecular Medicine Research Group, Dow Research Institute of Biotechnology and Biomedical Sciences, Dow College of Biotechnology, Dow University of Health Sciences, Karachi, Pakistan. Electronic address: mushtaq.hussain@duhs.edu.pk.

Imran Rauf (I)

Department of Computer Science, IBA, Karachi, Pakistan. Electronic address: irauf@iba.edu.pk.

Syed Farooq Zaidi (SF)

Department of Computer Science, IBA, Karachi, Pakistan. Electronic address: szaidi@iba.edu.pk.

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