Somatic mutation load and spectra: A record of DNA damage and repair in healthy human cells

Abstract

Somatic genome instability is a hallmark of cancer genomes and has been linked to aging and a variety of other pathologies. Large-scale cancer genome and exome sequencing have revealed that mutation load and spectra in cancers can be influenced by environmental exposures, the anatomical site of exposures, and tissue type. There is now an abundance of data favoring the hypothesis that a substantial portion of the mutations in cancers originate prior to carcinogenesis in stem cells of the healthy individual. Rapid advances in sequencing of noncancer cells from healthy humans have shown that their mutation loads and spectra resemble cancer data. Similar to cancer genomes, mutation profiles of healthy cells show marked intra-individual variation, thus providing a metric of the various factors-environmental and endogenous-involved in mutagenesis in these individuals. This review focuses on the current methodologies to measure mutation loads and to determine mutation signatures for evaluating the environmental and endogenous sources of DNA damage in human somatic cells. We anticipate that in future, such large-scale studies aimed at exploring the landscapes of somatic mutations across different cell types in healthy people would provide a valuable resource for designing personalized preventative strategies against diseases associated with somatic genome instability. Environ. Mol. Mutagen. 59:672-686, 2018. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Keywords: genome-wide mutation rate; human somatic mutations; mutation signatures; next-generation sequencing.

Figure 1. Overview of the methods for detecting somatic mutations in healthy human cells

The various approaches to analyze somatic mutations in a heterogenous tissue sample are depicted using skin as an example. The colored circles (red, cyan, yellow and green) in the tissue denote nuclei within the cells with different somatic mutations respectively. The dark blue circles denote nuclei with germline polymorphisms present across all cells in the tissue. DNA extraction from the bulk cells followed by deep sequencing provides a measure of the diverse somatic mutations present in the sample (left panel). The gray lines denote individual reads in NGS, and the colored circles on them imply heterozygous somatic mutations or germline polymorphisms present in the tissue. The somatic mutations in bulk sequencing samples are often present in very low allele fractions. In addition, sequencing errors (crosses) may further confound analysis in deep-sequenced heterogenous samples. To determine the somatic mutations in a given cell whole genome amplification from a single cell followed by WGS may be used (middle panel). On the other hand, pluripotent stem cells may be derived from the tissue and grown clonally to get enough number of cells for WGS. The primary cells may also be either cultured directly, or organoid cultures may be established from the stem cells within the tissue allowing propagation in vitro to obtain DNA for WGS (right panel). In single cell sequencing, and clonal population sequencing somatic mutations are present as high frequency alleles, while errors generated during library preparation and sequencing are usually present in a smaller fraction of reads. Therefore, somatic mutation calling using these approaches is more accurate.