# In situ transcriptome imaging in single cells

> **NIH NIH R01** · HARVARD UNIVERSITY · 2020 · $973,165

## Abstract

Project Summary/Abstract
The function of multi-cellular systems emerges from the complex interactions between cells that have distinct
behaviors and functions. Because cellular behaviors are in large part determined by their transcriptomes, the
ability to quantify all transcripts in every single cell in a biological system would transform our understanding
of a wide range of systems as well our ability to diagnose and treat diseases. Although single-cell
transcriptomics methods based on high-throughput sequencing provide a powerful approach towards this
goal, these methods requires dissociation of cells from their native tissue and extraction of RNA from the
cells. As a result, it is difficult for these sequencing-based approaches to retain an important class of
information that is crucial to a wide variety of biological processes: the spatial context of RNAs, i.e. where
these RNAs are located within a cell and where the cells are located within the tissue. On the other hand, the
spatial positions of RNAs within the cell can have a potent effect on their post-transcriptional fate and have
been implicated in a diverse set of cellular behaviors from cell motility to cell polarization. Furthermore, the
spatial organization of different types of cells within a tissue is of paramount importance to the tissue function:
such spatial context modulates cell behavior, directs cell differentiation, and shapes the emergent behavior of
the tissue as a whole. Therefore, a spatially-resolved approach to single-cell transcriptomics is in great
demand and promises to transform many areas of biology.
 Here we propose to develop an imaging-based method that is capable of determining the precise copy
numbers and spatial locations of most, if not all, RNA species (i.e. the whole transcriptome) within individual
cells preserved in their native context. This approach functions by massively multiplexing single-molecule
fluorescence in situ hybridization. In this approach, we will encode each RNA species in the cell with a
barcode that is defined by a set of specially designed DNA probes that can specifically bind to and uniquely
encode the target RNA. This barcode will then be read by a series of hybridization and imaging rounds,
allowing us to determine the identity the RNA. Using an error-robust encoding scheme, we estimate that we
should be able to image the entire mammalian transcriptome, i.e. several tens of thousands of RNA species,
with high accuracy in just a few tens of imaging rounds or even fewer with multicolor imaging! This technique
also promises a very high throughput of measuring hundreds of thousands of cells per single-day experiment.
In this project, we will not only develop this technology and the above-mentioned capabilities, but also
demonstrate the transformative impact of this technology in biology by mapping the spatial organization of the
transcriptome inside individual cultured neurons and determining the number of transcriptionally distinct c...

## Key facts

- **NIH application ID:** 9967106
- **Project number:** 5R01MH113094-05
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Catherine Dulac
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $973,165
- **Award type:** 5
- **Project period:** 2016-09-19 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9967106

## Citation

> US National Institutes of Health, RePORTER application 9967106, In situ transcriptome imaging in single cells (5R01MH113094-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9967106. Licensed CC0.

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