Abstract
Somatic mosaicism occurs throughout normal development and contributes to numerous disease etiologies, including tumorigenesis and neurological disorders. Intratumor genetic heterogeneity is inherent to many cancers, creating challenges for effective treatments. Unfortunately, analysis of bulk DNA masks subclonal phylogenetic architectures created by the acquisition and distribution of somatic mutations amongst cells. As a result, single-cell genetic analysis is becoming recognized as vital for accurately characterizing cancers. Despite this, methods for single-cell genetics are lacking. Here we present an automated microfluidic workflow enabling efficient cell capture, lysis, and whole genome amplification (WGA). We find that ~90% of the genome is accessible in single cells with improved uniformity relative to current single-cell WGA methods. Allelic dropout (ADO) rates were limited to 13.75% and variant false discovery rates (SNV FDR) were 4.11x10-6, on average. Application to ER-/PR-/HER2+ breast cancer cells and matched normal controls identified novel mutations that arose in a subpopulation of cells and effectively resolved the segregation of known cancer-related mutations with single-cell resolution. Finally, we demonstrate effective cell classification using mutation profiles with 10X average exome coverage depth per cell. Our data demonstrate an efficient automated microfluidic platform for single-cell WGA that enables the resolution of somatic mutation patterns in single cells.
Highlights
Genetic mosaicism in somatic cells occurs naturally in an array of normal biological processes and contributes significantly to disease etiologies, tumorigenesis [1,2,3,4,5,6,7,8,9,10,11,12,13]
We find that contamination is, low within the C1 integrated fluidic circuits (IFCs), as evidenced by a 97.3% concordance between whole genome amplification (WGA) DNA yield and the presence/absence of a live cell visually confirmed using a viability assay
In this study we report the development of an automated hands-free workflow for the capture, lysis, and amplification of genomic DNA from single cells using nanoliter-scale microfluidics
Summary
Genetic mosaicism in somatic cells occurs naturally in an array of normal biological processes and contributes significantly to disease etiologies, tumorigenesis [1,2,3,4,5,6,7,8,9,10,11,12,13]. Cancers are known to manifest as dynamic evolutionary processes in which intratumor genetic and phenotypic diversity is an inherent feature of the disease [3]. While large-scale projects have performed extensive analysis of somatic mutations across cancer types [14, 15], such studies lack the ability to define how the identified mutations segregate amongst individual cells. Identification of somatic mutations from bulk DNA precludes the ability to determine
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