# Molecular and Computational Tools for Identifying Somatic Mosaicism in Human Tissues

> **NIH NIH UG3** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $387,347

## Abstract

Abstract
Human genomes harbor significant variation both between and within individuals. Numerous studies have
explored inherited variation across human populations and linked various germline polymorphisms to human
traits and disease susceptibility. Genomic sequences also vary within an individual, occurring after zygote
formation and leading to variation present in a frequency spectrum ranging from individual cells to entire tissues.
This somatic mosaicism of genome variation has been well established in cells of phenotypically normal
individuals and has been shown to also be associated with some disease phenotypes, particularly cancers.
However, these investigations have been mostly limited to higher frequency mosaicism (e.g. >5-10% variant
allele frequency) due to technical limitations in both molecular assays and computational methodology.
Compounding these technological challenges is that each human tissue exhibits apparently different rates of
somatic mosaicism. For example, it is currently estimated that each cell within the human brain contains
hundreds to a few thousand somatic single-nucleotide variants (SNVs) and that a smaller fraction of cells harbor
somatic copy number variations (CNVs), mobile element insertions (MEIs), and short tandem repeat expansions
(STRs). In contrast, somatic mutation rates have been reported to be significantly higher in the large and small
intestines and lower in gastric and prostatic glands. These rates have been ascertained through a variety of
approaches, including SNP microarrays, bulk and single cell whole genome sequencing, and direct amplification
and sequencing of candidate events, each with its own advantages and limitations. However, there has yet to
be a systematic investigation of human somatic mosaicism across the entire frequency spectrum within human
tissues. Our team has extensive collective experience developing tools for identifying somatic mosaicism in the
human brain, including recent surveys of SNV prevalence from whole genome and exome sequencing, CNVs
from single cell short-read and nanopore genome sequencing, and retrotransposons through targeted capture.
Here, we propose to improve, optimize, and extend our approaches to other human tissues as part of
the SMaHT initiative, which will provide an excellent platform for systematically identifying, cataloging,
and exploring human somatic mosaicism across tissues. We will achieve this through two phases: in the
UG3 phase of this project, we will (1) improve molecular assays for nanopore targeted bulk capture and single
cell sequencing and (2) improve computational approaches for detecting somatic mosaicism from single cell and
bulk tissue data, while in the UH3 phase we will (3) optimize, benchmark, and validate molecular assays for high-
throughput application across human tissues and (4) improve efficiency, runtime, and structured reporting of
somatic variants. Collectively, these efforts will enhance our ability to detect at scale p...

## Key facts

- **NIH application ID:** 10827996
- **Project number:** 5UG3NS132084-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Alan P Boyle
- **Activity code:** UG3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $387,347
- **Award type:** 5
- **Project period:** 2023-04-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10827996

## Citation

> US National Institutes of Health, RePORTER application 10827996, Molecular and Computational Tools for Identifying Somatic Mosaicism in Human Tissues (5UG3NS132084-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10827996. Licensed CC0.

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