Quantification of somatic mutation flow across individual cell division events by lineage sequencing
Name
Genome Res.-2018-Brody-1901-18.pdf
Size
4.14 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Kimmerling, Robert John
Elacqua, Juniper J.
Blainey, Paul C
Manalis, Scott R
Date Issued
November 2018
Journal
Genome research
Publisher
Cold Spring Harbor Laboratory
Citation
Brody, Yehuda et al. “Quantification of somatic mutation flow across individual cell division events by lineage sequencing.” Genome research 28 (2018): 1901-1918 © 2018 The Author(s)
Version
Final published version
Abstract
Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1101/GR.238543.118
