The epigenetic network mediated by Ehmt1 and its role in neurodevelopment disorders (NDD)

This project investigates how the epigenetic regulator EHMT1 controls the gene regulatory network that underlies human neurodevelopment, and how its dysfunction leads to Kleefstra Syndrome (KS) and increased risk for schizophrenia. It will combine computational analysis of existing and new sequencing data, and then use functional genomic and new CRIPSR-based technologies to test predictions arising from the sequence data.
Ehmt1(KMT1D) is a dimethyltransferase, responsible for methylation of Lysine-9 of the H3 subunit of nucleosomes (H3K9me2) and is associated with transcriptional gene repression. Deletion of one copy of Ehmt1 confers high risk for KS but has also been associated with elevated risk for schizophrenia. In a recent project, we demonstrated that reduced ehmt1 activity in KS patient iPSC cells is associated with deregulation of NRSF/REST, a second epigenetic regulator that suppresses neuronal gene expression, and leads to aberrant neurodevelopment in cell culture. We further showed that this is due to elevated expression of miRNAs that control NRSF/REST mRNA stability.
In this project, you will further explore this gene regulatory mechanism. miRNA can target multiple mRNAs, resulting a complex network of gene interactions. In its first phase this project will use existing and newly generated miRNA-seq data to map out the interaction network of miRNAs and their target genes. As NRSF/REST is both regulated by miRNA and can in turn regulate miRNA expression, often in a feedback loop, ChIP and ChIP-seq will be employed to identify miRNA that are primary targets of H3K9me2, and those that are downstream effectors. Finally, the predictions on gene expression will be validated using qRT-PCR and/or RNA-seq.
In its second phase, you will use a newly created epi-CRISPR toolkit to target suppress individual miRNA genes.This will further validate the network map, identify key interactions (nodes) and map miRNA genes to neurodevelopmental function. This information may ultimately reveal genes within the network for effective therapeutic targeting.