A complex genetic architecture that underlies risk for autism spectrum disorders (ASD) has emerged. This complexity is reflected in two general principles: i) gene misregulation underlies a wide range of human disease; ii) there is enrichment of common disease-associated variation in regulatory DNA that is not randomly distributed throughout the genome. Thus the genetic factors that control gene expression (transcriptional regulation) are responsible for two related phenomena-normal biological diversity at the cellular level and disruption in human disease. But translating specific disruptions in transcriptional regulatory networks that are identified through discovery science into causal mechanisms has been challenging. A serious effort was recently made to determine the repertoire of genes regulated by specific transcription factors (TFs; e.g.Chromosome Immunoprecipitation and sequencing -ChIPseq–ENCODE). Yet most of the identified genes controlled by a specific TF are not relevant for understanding ASD risk. What really is needed to fill the knowledge gap is a risk gene 'centric' approach to generate an enriched profile of TFs that regulate the expression of ASD risk genes. To address this gap, differential ASD gene expression can be studied at a systems level using gene regulatory network (GRN) models that capture physical and regulatory interactions between genes and their regulators. These GRNs can be generated using a rapid, gene-centered discovery technology, enhanced yeast 1 hybrid (eY1H) assay. An eY1H screen was used to generate proof-of-principle data for 4 neurodevelopmental risk genes, including MET and FOXP2. This screen validated the few TFs in ENCODE that were discovered by ChIP but also greatly expanded the GRN for each of the genes that were not reported in ENCODE or the literature (>15 new TFs identified for each gene). This study also revealed shared TFs for MET and FOXP2. Interestingly FOXP2 is itself a TF and acts as a suppressor of MET transcription. The eY1H screen has made even more robust connections between these factors. These studies will generate a rich, new understanding of GRNs of ASD risk genes and provide the field with opportunities to advance hypotheses addressing specific neurodevelopmental mechanisms of ASD. This project has great potential to provide an understanding of aspects of brain development that are at risk in ASD, information that can be rapidly translated into novel diagnostic and intervention strategies.
Interagency Autism Coordinating Committee (IACC)
Autism Research Database (AFD)
