Inference and validation of an integrated regulatory network of autism

Autism is a complex neurodevelopmental disorder. Non-coding transcripts, including long non-coding RNAs (lncRNAs), have been shown to influence the pathobiology of autism. Based on the data provided by the Simons Foundation Autism Research Initiative, we composed a three-component regulatory network comprising mRNAs, microRNAs and lncRNAs which were associated with neurologically relevant pathways and functions. Four candidate lncRNAs: Gm10033, 1500011B03Rik, A930005H10Rik and Gas5 were confirmed through quantitative real-time reverse transcription polymerase chain reaction analysis in the brain of valproic acid-exposed mice. We furthermore identified a novel splice variant of Gm10033, designated as Gm10033-ΔEx2, which was expressed in various mouse tissues. This integrative approach combines the analysis of a three-component regulatory network with experimental validation of targets in an animal model of autism. As a result of the analysis, we prioritized a set of candidate autism-associated lncRNAs. These links add to the common understanding of the molecular and cellular mechanisms that are involved in disease etiology, specifically in the autism.