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Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches

Award Number: R35HG011292
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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ABSTRACT The overall goal of the proposed research program is to improve our understanding of single cell biology through information maximization techniques, by applying molecular engineering and computational approaches in sequencing. Specifically, single cell sequencing is rapidly becoming the predominant method for studying human biology and disease because it removes the confounding factor of sequencing cell mixtures in bulk. However, it has major pitfalls: significant material consumption during library preparation, noisy data readouts and signal dropout, and unclear paths for data integration across datasets. The overall vision of the proposed research program is to develop a pan-omic analysis strategy that enables perpetual re-use of any single cell source material. It revolves around a hybrid molecular engineering and computational framework that is loosely inspired by principles found in computing. The experimental core of the proposed research program revolved around a new molecular technology referred to as APEX (‘Attachment- based Primer EXtension’). The major innovation of APEX is the covalent conjugation of genomic material (i.e. DNA or cDNA) to a solid phase support such as an agarose magnetic bead, followed by utilizing only polymerase- based assays for non-destructive molecular interrogation. In this project, we will focus APEX development on single cell transcriptome sequencing applications, with general applicability to genome biology. As a model system, we will utilize peripheral lymphocytes as they consist of complex subpopulations with distinct characteristics at multiple levels of omic features. The project will focus on assay development and optimization, development of bioinformatic algorithms for data integration, and scale up to large cohorts as a demonstration of the scalability of the technology.


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: 2023 ( Subtotal = $471,022 )
2023	2023	THE LELAND STANFORD JUNIOR UNIVERSITY	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Human Genome Research	000	4	6/7/2023	NON-COMPETING CONTINUATION	$471,022
														Subtotal = $471,022

Issue Date FY: 2022 ( Subtotal = $471,022 )
2022	2022	LELAND STANFORD JUNIOR UNIVERSITY, THE	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Human Genome Research	000	3	7/1/2022	NON-COMPETING CONTINUATION	$471,022
														Subtotal = $471,022

Issue Date FY: 2021 ( Subtotal = $471,022 )
2021	2021	LELAND STANFORD JUNIOR UNIVERSITY, THE	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Human Genome Research	000	2	6/18/2021	NON-COMPETING CONTINUATION	$471,022
														Subtotal = $471,022

Issue Date FY: 2020 ( Subtotal = $438,480 )
2020	2020	LELAND STANFORD JUNIOR UNIVERSITY, THE	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Human Genome Research	001	1	9/28/2020	NEW	$0
2020	2020	LELAND STANFORD JUNIOR UNIVERSITY, THE	450 JANE STANFORD WAY	STANFORD	CA	94305	SANTA CLARA	USA	Human Genome Research	000	1	9/1/2020	NEW	$438,480
														Subtotal = $438,480

Grand Total All Awards = $1,851,546

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Omics information maximization in single-cell sequencing with hybrid molecular and computational approaches

Award Number: R35HG011292

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

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