# Spatially resolved high throughput lineage tracing by targeted in situ DNA diversification

> **NIH NIH R21** · UNIVERSITY OF CHICAGO · 2022 · $205,000

## Abstract

Project Summary
Cell division and differentiation are fundamental processes in biology. Lineage information for individual cells in
an adult represents the missing key to understanding the origins of different cell types and how cells choose
certain developmental trajectories. However, lineage tracing, especially that at a high resolution, is technically
demanding. We reason that an ideal lineage tracing tool must meet two requirements: (1) a programable
recording mechanism with large storage capacity that labels every cell division in a developmental window of
interest, and (2) an error-robust readout mechanism that can reveal the lineage labels in individual cells without
disrupting their spatial distribution. With these two requirements in mind, we propose to develop a widely
applicable tool for spatially resolved single-cell lineage tracing.
Our lineage tracing tool constitutes two modular key technologies: targeted in situ DNA diversification for
lineaging recording and 2D multiplexed imaging for lineaging reading. To enable dynamic tracing at single-cell
resolution, every cell division must be uniquely labeled, and these lineage labels must be stable and inheritable.
To this end, we will develop a targeted in situ DNA diversification technology using base editors, which are
precise genome-editing agents that introduce C:G to T:A or A:T to G:C transitions in double-stranded DNA. Our
simulation suggests that by including 20 editable bases for base editors in a short DNA sequence, a maximum
of 300k unique reads can be obtained with 20 generations of unrestricted cell division from a single ancestor
cells, reinforcing the large sequence diversity that can be accessed by our recording technology. To retrieve
these lineage labels from intact tissue samples, we will develop and validate a 2D multiplexed imaging platform
that can efficiently read out the mutations generated during lineage recording. In this imaging platform, each
editing position will be read out in a sequential way by each hybridization-imaging cycle, and each cassette will
be presented by unique color codes in each hybridization-imaging cycle using degenerate probes. This 2D
multiplexed imaging platform can efficiently read out the 220 unique labels from 20 editable bases using 5 colors
in only 4 imaging cycles, dramatically facilitating the information retrieval process. This multiplexed imaging
platform is only made possible by the unique binary functional mode of base editing and is not compatible with
the vast majority of CRSIPR-based tracers, which function by introducing random DNA mutations to label cell
lineage. Finally, we will apply both technologies for a proof-of-concept tracing experiment in HeLa cells.
Collectively, the proposed technologies, once developed, will enable the collection of spatially resolved lineage
information from single cells in intact tissues. We expect our tool can be widely applicable to various biological
systems.

## Key facts

- **NIH application ID:** 10412030
- **Project number:** 5R21GM141670-02
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Jingyi Fei
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $205,000
- **Award type:** 5
- **Project period:** 2021-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10412030

## Citation

> US National Institutes of Health, RePORTER application 10412030, Spatially resolved high throughput lineage tracing by targeted in situ DNA diversification (5R21GM141670-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10412030. Licensed CC0.

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