Genes and Gene Networks Implicated in Aggression Related Behaviour

• Published in: Neurogenetics Vol. 15; no. 4; pp. 255 - 266
• Main Authors: Malki, Karim, Pain, Oliver, Du Rietz, Ebba, Tosto, Maria Grazia, Paya-Cano, Jose, Sandnabba, Kenneth N., de Boer, Sietse, Schalkwyk, Leonard C., Sluyter, Frans
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-10-2014; Springer Nature B.V
• Subjects: Aggression - physiology; Aggressiveness; Animals; Behavioral psychology; Biomedical and Life Sciences; Biomedicine; Disease Models, Animal; Female; Gene Expression Profiling; Gene Regulatory Networks; Genes; Genetic Variation; Human Genetics; Male; MAP Kinase Signaling System - genetics; Mice; Mice, Inbred Strains - genetics; Molecular Medicine; Neurosciences; Original Article; Prefrontal Cortex - metabolism; RankProd; SAL/LAL; TA/TNA; NC900/NC100; Aggression; WGCNA
• ISSN: 1364-6745; 1364-6753
• DOI: 10.1007/s10048-014-0417-x

Aggressive behaviour is a major cause of mortality and morbidity. Despite of moderate heritability estimates, progress in identifying the genetic factors underlying aggressive behaviour has been limited. There are currently three genetic mouse models of high and low aggression created using selective breeding. This is the first study to offer a global transcriptomic characterization of the prefrontal cortex across all three genetic mouse models of aggression. A systems biology approach has been applied to transcriptomic data across the three pairs of selected inbred mouse strains (Turku Aggressive (TA) and Turku Non-Aggressive (TNA), Short Attack Latency (SAL) and Long Attack Latency (LAL) mice and North Carolina Aggressive (NC900) and North Carolina Non-Aggressive (NC100)), providing novel insight into the neurobiological mechanisms and genetics underlying aggression. First, weighted gene co-expression network analysis (WGCNA) was performed to identify modules of highly correlated genes associated with aggression. Probe sets belonging to gene modules uncovered by WGCNA were carried forward for network analysis using ingenuity pathway analysis (IPA). The RankProd non-parametric algorithm was then used to statistically evaluate expression differences across the genes belonging to modules significantly associated with aggression. IPA uncovered two pathways, involving NF-kB and MAPKs. The secondary RankProd analysis yielded 14 differentially expressed genes, some of which have previously been implicated in pathways associated with aggressive behaviour, such as
Adrbk2
. The results highlighted plausible candidate genes and gene networks implicated in aggression-related behaviour.