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Single cell mapping of developmental trajectories underlying health and disease

Single cell mapping of developmental trajectories underlying health and disease
健康和疾病的发育轨迹的单细胞图谱
批准号:
9312128
负责人:
Dana Pe'er
金额:
$86.4万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-12-21 至 2019-06-30

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DESCRIPTION (provided by applicant): Multi-cellular organisms develop from a single cell that undergoes many stages of proliferation and differentiation that result in the vast array of progenitor and terminal cell types. While dogma defines development as a series of discrete steps, it is actually a continuous process, characterized by transitional stages and intermediate cell types that have yet to be described. We propose reframing development in terms of branching trajectories: We will develop computational algorithms that use high dimensional single cell data to map each individual cell into a lineage tree representing the chronological order of development. Rather than grouping cells into nodes of this tree (cell types), single cells will fill in the branches in a continuum ordered according to their developmental chronology. Thus, each branch is a developmental trajectory that represents all the transitional stages between cell states. In essence, combining single cell technologies with sophisticated computation will empower us to do for Homo sapiens what John Sulston and colleagues did for C. elegans-to construct a complete and detailed map of normal development. This map will provide both a full catalog of all cell types in our body, as well as the developmental relations between them. The detailed resolution of the resulting map will empower developmental studies, help elucidate how and where development is derailed in disease, and guide the next generation of regenerative medicine.
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Shared Resource Core: Computational and technology development for spatial expression analysis.
Shared Resource Core: Computational and technology development for spatial expression analysis.
Administrative Core
Molecular, Cellular, and Tissue Characterization Unit
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