# Versatile, exponentially scalable methods for single cell molecular profiling

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2021 · $989,600

## Abstract

The field of single cell genomics is exploding. However, the vast majority of studies restrict themselves to
quantifying mRNA transcription, typically in a few thousand cells. We have recently pioneered a new class of
methods based on the concept of single cell combinatorial indexing (“sci”), wherein several rounds of splitting,
molecular indexing, and pooling are used to uniquely label nucleic acids of cells or nuclei, without requiring the
isolation or compartmentalization of each cell. The number of cells that can be uniquely labeled scales
exponentially with the number of rounds of indexing, ​e.g. ​millions of cells can be profiled with as few as three
rounds of indexing. Since 2015, we have developed sci- methods for quantifying chromatin accessibility
(sci-ATAC-seq), transcription (sci-RNA-seq), chromatin architecture (sci-Hi-C), and genome sequence
(sci-LIANTI), as well as a co-assay of chromatin accessibility and transcription (sci-CAR). Here, we propose to
develop a much broader range of single cell methods, all based on the unifying concept of single cell
combinatorial indexing. In our first aim, we will develop additional “single channel” sci- assays of various
aspects of molecular state. In our second aim, we will develop additional “two channel” sci- assays, ​e.g.
co-assays of RNA and DNA. In our third aim, we will adapt sci- assays to enable large-scale chemical and
genetic screens in single cells. In our final aim, we will work to make the methods and associated software
widely available to the research community. As a versatile, exponentially scalable platform, we anticipate that
single cell combinatorial indexing will deepen and broaden the impact of single cell genomics for diverse goals,
including for descriptive molecular atlases of organisms, for functional studies of genes and regulatory
elements, and for modeling gene regulation.

## Key facts

- **NIH application ID:** 10216319
- **Project number:** 5R01HG010632-03
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Jay Ashok Shendure
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $989,600
- **Award type:** 5
- **Project period:** 2019-09-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10216319

## Citation

> US National Institutes of Health, RePORTER application 10216319, Versatile, exponentially scalable methods for single cell molecular profiling (5R01HG010632-03). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10216319. Licensed CC0.

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