# Developing mutable barcodes for high-resolution single-cell lineage tracing

> **NIH NIH F31** · WASHINGTON UNIVERSITY · 2022 · $32,686

## Abstract

PROJECT SUMMARY
Just as gene and protein expression are common characteristics to identify a cell, lineage is an important aspect
of cell identity. In the past, lineage tracing has been used to determine what cells arise from a specific cell type,
as defined by the expression of a cell-type-specific gene; however, the establishment of single-cell genomics
techniques has ushered in lineage tracing at single-cell resolution. New technologies for lineage tracing can track
the progeny of single cells, regardless of their initial gene expression. The Morris lab has developed a single-cell
lineage tracing (scLT) method, called CellTagging. CellTagging demonstrated the ability of scLT approaches to
identify similarities in cells based on lineage and offer mechanistic insights to cell reprogramming. CellTagging
and other virus-based scLT technologies still present limitations, though, in that they require multiple
transductions to increase lineage resolution, and may fail to capture biologically relevant bifurcation events due
to cell labeling at discrete time points. These technologies are also subject to transgene silencing in certain cell
models, such as iPSC-derived organoids, rendering them ineffective for use in many models of development
and disease. To overcome these limitations, it is necessary to develop new scLT tools that can be applied without
repeated manipulation of cells and be used in iPSC differentiation and reprogramming systems without silencing
hindering the readout of lineage information. Here, I propose to utilize a CRISPR-Cas12a-guided cytidine
deaminase as a method to continuously record heritable lineage data through targeted cytidine to
thymine editing. I have developed and validated the ability of a novel CRISPR-Cas12a-guided cytidine
deaminase to accrue base edits on a targeted synthetic DNA region over time in vitro and recovered these
synthetic sequences via single-cell RNA-sequencing (scRNA-seq). These two outcomes are a promising proof-
of-concept that scLT can be performed with these accrued single base edits. Here, I propose to (1) increase the
resolution of CellTagging to capture bifurcation events, using this novel DNA editor to constantly edit single
bases in a targeted editing region (TER) and dispense with the need for multiple transductions, and (2) integrate
this base editor system into a safe harbor locus within an iPSC line to shield the transgenic components of the
technology from silencing, validating this approach in kidney organoid differentiation. My proposed developments
of the CellTagging technology increase the potential for discovery because they can be broadly applied to model
systems that are either not amenable to multiple manipulations or are prone to transgene silencing. By making
all plasmids, cell lines, protocols, and analysis tools for these systems publicly available, I aim to provide a
valuable resource across several areas of cell biology. These resources will provide an experimental toolki...

## Key facts

- **NIH application ID:** 10536930
- **Project number:** 1F31HG012321-01A1
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Sadie M VanHorn
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $32,686
- **Award type:** 1
- **Project period:** 2022-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10536930

## Citation

> US National Institutes of Health, RePORTER application 10536930, Developing mutable barcodes for high-resolution single-cell lineage tracing (1F31HG012321-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10536930. Licensed CC0.

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