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High-probability grants
According to our matching algorithm, Prashanth Rajarajan is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2017 — 2020 |
Rajarajan, Prashanth |
F30Activity Code Description: Individual fellowships for predoctoral training which leads to the combined M.D./Ph.D. degrees. |
3d Genome Mapping in the Human Brain and Its Implications For Schizophrenia @ Icahn School of Medicine At Mount Sinai
PROJECT SUMMARY The human genome has traditionally been studied as a linear entity, ignoring how three-dimensional looping interactions that bring together distal non-coding regulatory elements and proximal promoters may modulate gene expression. Even with innovations in chromosome conformation capture techniques, the 3D neuroepigenome remains largely underexplored. Exploration of cell-type-specific chromosomal conformations will advance insight into hitherto unknown roles of non-coding sequences in the neurobiology of psychiatric disorders such as schizophrenia. The basic mechanisms of these processes can be elucidated using a human induced pluripotent stem cell-based platform, where isogenic neural cell types can be inexhaustibly derived from one individual. In this proposal, we seek to explore how 3D chromatin interactions and topology change based on cell type given an identical genotypic background in normal human neural differentiation, from neural progenitor to either astrocyte or excitatory neuron. I hypothesize that identity-specific regulatory element- promoter loops will emerge that connect noncoding sequences to transcription start sites, thereby modulating gene expression. By overlaying known schizophrenia ?risk loci,? many of which are in noncoding regions, on neuron-specific chromatin loops, I will attempt to find those loci that occur in sequences of the genome critical for loop formation. Finally, I hypothesize that by manipulating such candidate (i.e., risk-loci-bearing) loops with targeted CRISPR epigenetic editing, I will observe changes in gene expression. Findings from the proposed project will greatly advance knowledge in the field of how the 3D genome can quite literally contribute to the risk architecture of psychiatric disease, promoting the development of more effective diagnosis and treatment in the future.
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