My goal is to identify novel genetic factors that regulate normal and pathological anxiety. Anxiety disorders are complex diseases with genetic and environmental susceptibility factors. Stressful life events, especially in childhood are well-known risk factors for anxiety disorders. We have previously used inbred mouse strains to identify genes underlying innate anxiety. Here I propose a new approach using a mouse model of anxiety induced by social stress to identify gene regulatory networks, to show the causality of the selected networks in vivo, and to investigate involvement of these networks in the genetic predisposition to human anxiety disorders. Gene regulatory networks will be identified by using massively parallel sequencing methods (i.e. miRNA-seq and mRNA-seq). We will generate from four brain regions known to regulate anxiety a complete gene and miRNA expression atlas, which is used to identify genes, transcripts, miRNAs and isomiRs differentially expressed between anxious and control animals. Pathway and network analysis tools are employed to identify molecular pathways affected by induced anxiety. Datasets consisting of different levels of data from individual brain regions will then be integrated in light of existing molecular and anatomical information to construct draft network models that will be curated, filtered and enhanced. On the basis of these models, we will generate specific hypotheses that are tested in vivo in mice to show the causality of the most interesting networks. To identify the networks important for human anxiety disorders, we have access to a unique population-based cohort from Finland characterized for anxiety disorders. Candidate genes and miRNAs from selected networks are tested in a genetic association analysis. This multidisciplinary project will increase understanding of the genetic and neurobiological basis of anxiety in mouse and human, and has potential to provide targets for the development of improved anxiolytics.