RUI: Molecular Modules of Aggression; Maternal Behavior in the African Cichlid Astatotilapia Burtoni

Reed College, Portland OR

Investigators

Abstract

In all animals, aggression is a complex social behavior with multiple causes and manifestations. Growing evidence suggests that different mechanisms underlie different forms of aggression. This project examines different forms of aggression in the African cichlid fish Astatotilapia burtoni. Aggression in males of this species is associated with territoriality and is regulated by social factors and testosterone. Previous research has identified brain regions, physiological mechanisms and patterns of gene expression that underlie the variety of aggression levels in males. Laboratory stock females do not care for their young nor do they show stereotypical forms of aggression. However, aggression can be induced in the laboratory through manipulation of the social environment. This form of female aggression, as in males, is associated with elevated testosterone levels. Recent observations of a newly acquired wild stock reveal a "good mother" phenotype that includes defensive aggression to protect free-swimming fry. This new stock will allow a comparison of different hormone levels correlated with different levels of maternal aggression. Furthermore, the availability of genomic tools for this species (a cDNA microarray) will allow the identification of gene expression associated with maternal aggression. The pattern of gene expression can be then compared between natural maternal aggression, induced female aggression and territorial male aggression. This work will answer questions regarding the extent of overlap between the gene sets that regulate each of these forms of aggression and will identify specific subsets of the gene expression pattern that are uniquely associated with male, female, and/or maternal forms of aggression. Through collaboration between the Renn Lab in the biology department and the Jones team in the math department, undergraduates at Reed College will engage in cutting edge genomic research and rigorous statistical analysis of datasets incorporating measures of behavior, physiology and gene expression.