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Computational Modeling of Lineage Decisions using Single-cell Data

Award Number: R35GM147125
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/17/2022
PERIOD OF PERFORMANCE END DATE: 07/31/2027

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Computational Modeling of Lineage Decisions using Single-cell Data - Project Summary Cellular differentiation is a fundamental biological process through which complex multi-cellular organisms develop from single-cell embryos and maintain tissue homeostasis throughout life. Cells integrate signals from the microenvironment and transmit them to downstream transcriptional regulators, which execute the expression and chromatin changes to define phenotypic state transitions in differentiation trajectories. Elucidating the principles of how cells choose their fate, and the path they take to get there, is a major challenge in the field. Single-cell (sc) RNA sequencing technologies are revolutionizing our understanding of the cellular spatio- temporal trajectories that shape differentiation. The emergence of additional high throughput, multimodal technologies such as paired RNA&ATAC-seq, scCUT&Tag and spatial technologies provide unprecedented opportunities to extract mechanistic insights into the lineage decisions that underly differentiation trajectories. This proposal aims to exploit this enormous potential by developing sophisticated new algorithms that integrate single-cell measurements to model and interpret complex biology. Through analysis of multiple single-cell RNA- seq datasets, we demonstrate that phenotypic asymmetries are a pervasive feature of lineage decisions. We will develop algorithms to unravel the mechanisms that drive lineage decisions and the underlying asymmetries in three broad research directions. We will investigate the role of: (i) enhancer priming and transcriptional regulation, (ii) open and heterochromatin dynamics, and (iii) cell communication in shaping differentiation trajectories. Our studies will lead to novel insights surrounding cell-autonomous and non-autonomous mechanisms engaged by cells as they navigate the phenotypic landscape. Successful completion of this research will provide a robust mechanistic basis to delineate normal differentiation events, decipher dysregulation of these mechanisms in disease, understand repurposing of differentiation mechanisms in wound healing and regeneration, and reconstruct differentiation processes in vivo and ex vivo to unlock the therapeutic potential of cell engineering.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $425,737 )
2024	2024	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Biomedical Research and Research Training	000	3	7/25/2024	NON-COMPETING CONTINUATION	$425,737
														Subtotal = $425,737

Issue Date FY: 2023 ( Subtotal = $426,153 )
2023	2023	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Biomedical Research and Research Training	000	2	7/17/2023	NON-COMPETING CONTINUATION	$426,153
														Subtotal = $426,153

Issue Date FY: 2022 ( Subtotal = $426,556 )
2022	2022	FRED HUTCHINSON CANCER CENTER	1100 FAIRVIEW AVE N	SEATTLE	WA	98109	KING	USA	Biomedical Research and Research Training	000	1	9/16/2022	NEW	$426,556
														Subtotal = $426,556

Grand Total All Awards = $1,278,446

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Computational Modeling of Lineage Decisions using Single-cell Data

Award Number: R35GM147125

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 09/17/2022

PERIOD OF PERFORMANCE END DATE: 07/31/2027

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