Center for Multiomic Human Brain Cell Atlas
- Institution
- SALK INSTITUTE FOR BIOLOGICAL STUDIES, CA
- Principal investigator
- Joseph R Ecker
- Funding
- $17.6M
- Duration
- 2022–2027
Moonbase score
Still being scored
Abstract
Abstract Understanding cell identities and their spatial distributions throughout different regions of the human brain is a fundamental step when trying to integrate physiological, behavioral, neurochemical and molecular data. At present, although major categories of the cell-types present in the human brain have been defined molecularly, the different subtypes within these categories along with their locations are far from understood. Gene expression drives cell programs and states that underlie distinct brain functions. Open chromatin and modified histones mark gene-regulatory elements that control cell type-specific gene expression patterns. Cytosine DNA methylation (mC) is a stable epigenomic signature that persists in post-mitotic cells throughout their lifetime, defining their cellular identity. Single-cell gene expression, open chromatin profiles and DNA methylation assays have been successfully used to identify distinct cell types in an unbiased fashion in heterogeneous tissues including the human brain. This UM1 proposal builds on our earlier successes in mouse brain mapping to produce detailed single-cell multimomic and spatial cell maps at the single-cell level across 100 anatomically defined regions in the human brain. Profiling human brain samples will permit the discovery of unique gene expression patterns for each molecularly-defined cell type, identify their spatial organization, and their specific non-coding DNA regulatory regions. Multi-modal integration between epigenomic and transcriptomic signatures will allow the identification of new cell types and unique cell-type markers that will rapidly be made available to the entire community. This UM1 project will also provide new tools for genetic access of previously inaccessible brain regions as well as facilitate the functional analysis of genetic variants associated with neuropsychiatric and neurological disorders.
Research team
- M Margarita BehrensPI
- Joseph R EckerPI
- Daofeng LiPI
- Bing RenPI
- Xiangmin XuPI
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