Single-Cell Genetic Analysis Using Automated Microfluidics to Resolve Somatic Mosaicism

PLoS One. 2015 Aug 24;10(8):e0135007. doi: 10.1371/journal.pone.0135007. eCollection 2015.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / genetics*
  • Breast Neoplasms / pathology
  • Cell Line, Tumor
  • DNA Copy Number Variations / genetics
  • Exome
  • Female
  • Genetic Heterogeneity
  • Genome, Human
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Microfluidics / methods*
  • Mosaicism*
  • Mutation
  • Single-Cell Analysis*

Associated data

  • BioProject/PRJNA287813

Grant support

All funding was provided by Fluidigm Corporation who provided support in the form of salaries for all authors [KES, PC, XW, JW, LSW, MG, GS, MAU and RR], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the 'author contributions' section.