# Cost-effective assessment of somatic mutational load

> **NIH NIH U01** · ALBERT EINSTEIN COLLEGE OF MEDICINE · 2020 · $96,689

## Abstract

ABSTRACT
Somatic DNA mutation load is a true molecular endpoint of an interaction between DNA
damage and the DNA repair machinery and is the only direct indicator of a loss in genome
sequence integrity. DNA mutations cause cancer and have also been implicated in other
pathologies. For this reason, attempts have been made to develop assays for the quantitative
analysis of various types of mutations in cells and tissues. This is important in genetic
toxicology, in which the potential genetic risk associated with human exposure to the
various damaging agents is evaluated. With the advent of next-generation sequencing somatic
mutations can be quantitatively assessed, but only in clonal lineages, such as tumors, in
which most cells share a substantial number of mutations. In normal tissues somatic mutations
are of very low abundance and cannot be distinguished from sequencing errors. Utilization
of single cell sequencing is the most sophisticated solution for this problem, but single
cell-based approach is labor intensive and expensive which significantly limits its application
for high throughput screening studies, a routine task in the field of genetic toxicology. An
alternative approach, Duplex-seq, is utilizing bulk DNA as an input material and is based
on comparative analysis of separately sequenced complementary DNA strands
composing each DNA duplex. While technically less challenging than single cell-based
technique, this method is still prohibitively costly due to unbalanced representation DNA
strands resulting in very low rate of sequencing data utilization. Here we introduce Linked
Strands Duplex-Seq (LSDS) assay which is designed to overcome this critical limitation of
Duplex-seq. To accomplish that we designed a new sequencing library preparation procedure
that ensures amplification of complementary DNA strands at equal rates. This will result in a
completely balanced sequencing library and we expect to achieve at least a 10-fold increase
in sequencing data utilization efficiency as compared to the original Duplex-seq
approach. If successful, this method will fill the gap in genetic toxicology methodology and
will provide a practical tool for accurate cost-effective genome-wide assessment of
somatic mutational load in a high throughput manner.

## Key facts

- **NIH application ID:** 10140637
- **Project number:** 3U01ES029519-04S2
- **Recipient organization:** ALBERT EINSTEIN COLLEGE OF MEDICINE
- **Principal Investigator:** SIMON D SPIVACK
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $96,689
- **Award type:** 3
- **Project period:** 2018-08-15 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10140637

## Citation

> US National Institutes of Health, RePORTER application 10140637, Cost-effective assessment of somatic mutational load (3U01ES029519-04S2). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10140637. Licensed CC0.

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