Our parent grant U01-MH108898 entitled ?Mosaicism in focal cortical dysplasias spectrum seen in neuropsychiatric disease? has a focus on understanding the mechanisms of dysplasia of the cerebral cortex, and the contribution of brain somatic mosaicism to this process. Mosaicism is the occurrence of two (or more) genomes in an individual who is derived from a single zygote. Members of the NIMH-supported Brain Somatic Mosaicism Network (BSMN) are characterizing mosaic variation in other neuropsychiatric disorders with a common goal of assessing the role of somatic mosaic variation across diseases including BPD, schizophrenia, autism spectrum disorder, Tourette syndrome, and dysplasias. We propose three capstone projects to map the full spectrum of somatic variation in human brain and characterize the contributions of mosaic variants to neuropsychiatric disease risk. These capstones can advance the mission of the BSMN, to both achieve greater power of discovery of somatic mutations by combining and harmonizing deep coverage whole genome sequencing data that have been generated across nodes, as well as placing the variants identified through the study of brain somatic mosaicism (BSM) in the context of neurodevelopment and disease. To integrate this multi- dimensional data from the BSMN, as well as other consortia, administrative supplements are requested to continue, in the final two years of the award, three capstone projects, as well as to contribute to the Data Coordinating Center (DCC) and data analytic core (DAC). We expect these Capstone Projects to increase the profile of the BSMN by creating an unprecedented data resource of somatic mosaicism variants across development and diseases widely available to the scientific community. The enhanced power provided by the combined analyses of the BSMN will provide foundational knowledge that will guide future work, and lead to new insight into brain somatic mosaicism.
The specific aims are (1) for Capstone 2, to assess the somatic mutational landscape in the human brain, by an unprecedented, comprehensive mapping of brain mosaicism in a single person; (2) for Capstone 3, to exploit deeply sequenced bulk short-read WGS to detect somatic structural variation by refining and employing a novel machine-learning classifier approach named CHONK that was developed in our lab.
This project assesses the natural mosaic variation in the human brain using unprecedented depth on comprehensive sampling to analyze the mosaicism within a single individual. We will further extend our analysis of mosaic variation to structural variants by employing a novel, machine-learning based, classifier. 1
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