# Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells

> **NIH NIH UG3** · STANFORD UNIVERSITY · 2024 · $352,905

## Abstract

Abstract
Understanding somatic genomic variation presents unique challenges, primarily stemming from
the individual rarity of most somatic mutations across cells in a multicellular organism. Hence,
both sensitivity and accuracy (due to the need to distinguish somatic variation from noise) become
crucially important. The Analysis of bulk DNA, even with ultraprecise approaches, only ascertains
a portion of the human genome. The analysis of single cells, either by cloning or in vitro whole-
genome amplification (WGA), enables discovering theoretically all mutations in a cell independent
of their frequency in bulk. However, amplifying single cell genomes in vitro represents still a
significant challenge in terms of accuracy of amplification. The novel PTA technique (primary
template directed amplification) offers substantially improved quality of amplified DNA. However,
PTA produces a relatively small amount of DNA fragments of moderate length. This limits the
application of long read sequencing. Long read sequencing is expected to be the most
comprehensive approach to somatic mutation detection. In the proposed project, we will, first,
perform long-read sequencing in single cells cloned via the production of iPSC lines to study
somatic mutation of all types using non-enzymatically amplified genomic DNA, from telomere to
telomere, and generate a gold-standard benchmarking resource for methods development.
Second, we will address a significant shortcoming of the analysis of single cell genomes, which
is the lack of direct information about the exact type of cell being analyzed, or about potential
functional consequences of mutations in that cell. For that, we will benchmark the new
ResolveOme method, an expansion of PTA, that can analyze in parallel the genome and
transcriptome of a single cell. Third, we will address the challenge of high-throughput analysis of
single cells to detect somatic structural variants. Specifically, we will establish and benchmark for
SMaHT the Strand-seq method that allows for high-throughput detection and characterization of
structural variants (SVs) in single cells. Together, this will address 3 critical needs in the analysis
of somatic mutations in normal tissues: comprehensive mosaic mutation discovery, phenotyping
the cell harboring mutations and directly assessing functional consequences of mutations, and
accurate and high-throughput detection of SVs. Another important aspect of the project will be
comprehensive comparative analyses of detected somatic variants across all Aims.

## Key facts

- **NIH application ID:** 10830440
- **Project number:** 5UG3NS132146-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Alexander Eckehart Urban
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $352,905
- **Award type:** 5
- **Project period:** 2023-04-19 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10830440

## Citation

> US National Institutes of Health, RePORTER application 10830440, Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells (5UG3NS132146-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10830440. Licensed CC0.

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