Role of Recurrent DNA Break Cluster Genes in Brain Development and Disease
Our
work suggested recurrent DNA double-stranded (DSBs) in developing neural stem
and progenitor cells (NSPCs) may predispose to genomic variations associated
with medulloblastomas (MB), the major pediatric brain cancer. To search for
such DSBs, we developed and applied a sensitive genome-wide DSB-detection
method to discover recurrent DSB clusters (“RDCs”) in mouse NSPC
genomes. All RDCs were in genes, of which most have roles neural cell
communication and/or are implicated in neuropsychiatric diseases and
cancer. Based on robust preliminary
data, we propose three inter-related specific aims that will elucidate
mechanisms of RDC generation, extend studies to human neural progenitors, and
evaluate contributions of RDCs to recurrent genomic rearrangements in MB. In
Aim 1 we will evaluate roles of transcription and replication stress in NSPC
RDC formation, elucidate relationships between RDC chromosome domain structure
with RDC DSB generation/resolution and gene expression, and develop a new
approach to assay NSPC RDC formation in vivo to better elucidate developmental
and disease implications. Aim 2 studies
will elucidate human RDC genes, which is necessary to directly assess their
relevance to genomic alterations found in neuropsychiatric diseases and cancer.
We will use our recently developed chromosome-specific targeting approach to
identify and characterize human NSPC RDCs. Aim 3 will exploit a mouse MB model
developed in our lab in which tumors harbor recurrent chromosomal
rearrangements similar to those found in an aggressive class of human MBs to
test the hypothesis that RDC DSBs may contribute to the generation of recurrent
genomic variations found in MBs. To achieve this goal, we are collaborating
with Peter Lichter (DKFZ, Heidelberg, Germany) to perform whole genome
sequencing of mouse MBs from our model. If correlations between recurrent MB
genomic breakpoints and RDC locations are established, we will test implicated
RDC function with an approach adapted from our MB model.