Abstract
Somatic mosaicism refers to the existence of somatic mutations in a fraction of somatic cells in a single biological sample. Its importance has mainly been discussed in theory although experimental work has started to emerge linking somatic mosaicism to disease diagnosis. Through novel statistical modeling of paired-end DNA-sequencing data using blood-derived DNA from healthy donors as well as DNA from tumor samples, we present an ultra-fast computational pipeline, LocHap that searches for multiple single nucleotide variants (SNVs) that are scaffolded by the same reads. We refer to scaffolded SNVs as local haplotypes (LH). When an LH exhibits more than two genotypes, we call it a local haplotype variant (LHV). The presence of LHVs is considered evidence of somatic mosaicism because a genetically homogeneous cell population will not harbor LHVs. Applying LocHap to whole-genome and whole-exome sequence data in DNA from normal blood and tumor samples, we find wide-spread LHVs across the genome. Importantly, we find more LHVs in tumor samples than in normal samples, and more in older adults than in younger ones. We confirm the existence of LHVs and somatic mosaicism by validation studies in normal blood samples. LocHap is publicly available at http://www.compgenome.org/lochap.
Highlights
Many cancers arise from a series of mutational events occurring throughout a person’s life span [1,2]
We present a conservative filtering pipeline that is heavily biased toward reducing false discovery rates (FDR), so that reported local haplotype variant (LHV) are of high confidence
In applications of LocHap using deep-sequencing data, we provide evidence that supports the existence of normal somatic mosaicism (NSM) and tumor somatic mosaicism (TSM) at single-nucleotide level
Summary
Many cancers arise from a series of mutational events occurring throughout a person’s life span [1,2]. Considerable evidence [3,4] has accumulated supporting the presence of genetically heterogeneous cells in a somatic sample, a phenomenon called somatic mosaicism, which may be a precursor to the onset of many cancers [5]. There are no effective and economical tools that can reliably measure the presence and degree of somatic mosaicism in a biological sample. Single cell sequencing [6] in principle provides the genetic landscape of each individual cells, in practice only up to hundreds or thousands of cells can be measured due to the formidable cost of money and effort. Next-generation sequencing (NGS) technologies assemble an average genome sequence of all the cells in a sample, assuming cellular homogeneity. In the presence of somatic mosaicism, the average genome may not be a good representation of the sample. Despite continuous breakthroughs in DNA sequencing since the completion of the human genome project [7], researchers are still unable to precisely dissect individual cellular genomes on large scales
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