Genetics of Chiari Malformation

We have assembled a cohort of >1000 CM patients and family members and have performed exome sequencing to identify genetic factors that contribute to CM1 risk. It is our goal to leverage the vast infrastructure of the Park-Reeves Syringomyelia Research Consortium to assemble the largest cohort of CM1 patients in the world. Further, we have access to >20,000 unrelated control exome sequenced individuals through long-time collaboration at Washington University which greatly aid in association studies. We compare the frequency of genetic variants in patients to the frequency in our large control cohort to identify genes and variants associated with CM1. Variants with significantly higher or lower frequency in patients will give a better understanding of disease pathophysiology.

Zebrafish Models of Neurological Disorders

We use zebrafish as a model system to study the development of various neurological disorders including Chiari I malformation, syringomyelia and hydrocephalus. By “knocking-out” disease-assiciated genes in zebrafish, we are able to see what role these genes play in the development of analogous traits in the zebrafish.

High-throughput functional studies

We are interested in developing high-throughput methods for dissecting the functional impact of genetic variation in their genes or non-coding regions of interest. The production of libraries of DNA molecules, each different from the reference by one and only one position currently requires the purchase of many thousands of synthesized oligonucleotides either to be directly cloned into a vector, used as the donor DNA with CRISPR-Cas9 or used as primers in multiplex mutagenesis protocol. We have developed a method of massively parallel single nucleotide mutagenesis in which such libraries can be made in a single day for<$30/RXN. This method was published at Nature Methods and we currently hold a patent. We are currently using this method to functionally assess all possible single nucleotide changes in several Mendelian disease genes to predict which variants are capable of causing disease.