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R01NIH · NATIONAL HUMAN GENOME RESEARCH INSTITUTENIH

Versatile, exponentially scalable methods for single cell molecular profiling

Shendure, Jay Ashok (Contact)·University of Washington, WA·2019–2028·ACTIVE
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INSTITUTION

University of Washington, WA

PRINCIPAL INVESTIGATOR

Shendure, Jay Ashok (Contact)

FUNDING

$655K

YEAR

2019

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Abstract

ABSTRACT Within the past decade, single cell biology has exploded, and researchers now routinely characterize the molecular contents of individual cells obtained from both in vitro and in vivo contexts. However, the most widely used methods remain limited in critical ways. Through the first cycle of this award, we substantially broadened the scope and improved the performance of an exponentially scalable paradigm called single cell combinatorial indexing (“sci-*”). This included the development of new sci-* methods for nuclear oligo hashing, chemical transcriptomics, spatial transcriptomics and nascent transcriptomics, as well as markedly improved versions of sci-RNA-seq and sci-ATAC-seq. In parallel, we laid the foundation for a new generation of molecular recorders based on prime editing, termed DNA Typewriter and ENGRAM. In this renewal application, we propose to further advance sci-* and related methods with the goal of enabling the massively scalable perturbation and readout of multicellular model systems. Specifically, we propose to develop methods for: (1) “targeted molecular queries” of individual cells in sci-* experiments (payload, location, effect) that can be correlated with their genome-wide molecular states (Aim 1); (2) spatially-resolved chromatin accessibility and gene expression profiling with minimal or no optics, over a range of physical scales (Aim 2); and (3) molecular recording of both cell lineage and cell state to the genome, and efficient recovery of recorded histories via single cell profiling (Aim 3). Finally, in addition to continuing our practice of open and early sharing of protocols, data and software, we will proactively simplify and standardize newly developed methods and software for a broad range of users, in order to accelerate their adoption by the community (Aim 4). Of note, we have structured our plans to initially demonstrate QHZO\ GHYHORSHG PHWKRGV LQ D FRPPRQ VHW RI PRGHO V\VWHPVʊVSHFLILFDOO\ PDPPDOLDQ HPEU\RLG ERGLHV in vitro) and zebrafish organogenesis (in vivo). By facilitating the recovery of information pertaining to perturbation, spatial coordinates and lineage/state history in conjunction with a paradigm that now routinely scales to millions of single cells, we aim to lay the technical foundation for multiplex perturbational experiments of multicellular models of human biology at an unprecedented scale. Looking even further ahead, we envision that the systematic perturbation and single cell profiling of such complex model systems will powerfully inform quantitative models of gene regulation.

R01NATIONAL HUMAN GENOME RESEARCH INSTITUTEGenomics, Computational Biology and Technology Study Section[GCAT]throughchemicalmodelsefficientpracticepertainingreadoutzebrafishrecordershashingparadigmperturbationfacilitatingprghoordercomplexdemonstratetypewriterphwkrgv

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