# Hybrid approach for comprehensive mutation detection in a cell

> **NIH NIH UG3** · MAYO CLINIC ROCHESTER · 2024 · $350,314

## Abstract

Abstract
 Numerous recent studies have consistently shown that likely no two cells in the human body have the
same genomes, a phenomenon called somatic mosaicism. Mosaicism can be studied using various approaches,
but the study of mutations directly in the cell promises a comprehensive characterization of mosaicism in any
tissue. Analysis of single cell genome by cloning relies on natural DNA replication machinery in cells and, thus,
minimizes errors in DNA during cloning; however, cloning is limited by the ability of cells to proliferate. Analysis
by whole genome amplification (WGA) is hampered by introduced errors and non-uniformity of amplification.
Here we propose to address the limitations of single cell cloning and single cell WGA by developing a hybrid
approach that proceeds in two stages: 1) limited culturing of single cells to a micro-sized colony of 2-50 cells;
and 2) WGA of the micro-size colonies to yield enough DNA material for sequencing. An optimized hybrid
approach will enable rigorously and unbiasedly studying somatic mosaic at a single cell level throughout the
human body without WGA artifacts. Finally, to preserve tissue cell heterogeneity and enable biobanking of
tissues amenable to the developed hybrid approach, we will develop a storing protocol for tissues to preserve
proliferative potential of cells in the stored tissues. Success of the project would enable comprehensive and
accurate discovery of mutations in a single cell in a variety of tissues prioritized by SMaHT and beyond,
deepening our understanding of the mosaicism of humans.
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## Key facts

- **NIH application ID:** 10825576
- **Project number:** 5UG3NS132128-02
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** ALEXEJ ABYZOV
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $350,314
- **Award type:** 5
- **Project period:** 2023-04-15 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10825576

## Citation

> US National Institutes of Health, RePORTER application 10825576, Hybrid approach for comprehensive mutation detection in a cell (5UG3NS132128-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10825576. Licensed CC0.

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