UNIT 7.14 Whole-Genome Amplification of Single-Cell Genomes for Next-Generation Sequencing

  1. Christian Korfhage,
  2. Evelyn Fisch,
  3. Evelyn Fricke,
  4. Silke Baedker,
  5. Dirk Loeffert

Published Online: 11 OCT 2013

DOI: 10.1002/0471142727.mb0714s104

Current Protocols in Molecular Biology

Current Protocols in Molecular Biology

How to Cite

Korfhage, C., Fisch, E., Fricke, E., Baedker, S. and Loeffert, D. 2013. Whole-Genome Amplification of Single-Cell Genomes for Next-Generation Sequencing. Current Protocols in Molecular Biology. 104:7.14:7.14.1–7.14.11.

Author Information

  1. Qiagen GmbH, Hilden, Germany

Publication History

  1. Published Online: 11 OCT 2013


DNA sequence analysis and genotyping of biological samples using next-generation sequencing (NGS), microarrays, or real-time PCR is often limited by the small amount of sample available. A single cell contains only one to four copies of the genomic DNA, depending on the organism (haploid or diploid organism) and the cell-cycle phase. The DNA content of a single cell ranges from a few femtograms in bacteria to picograms in mammalia. In contrast, a deep analysis of the genome currently requires a few hundred nanograms up to micrograms of genomic DNA for library formation necessary for NGS sequencing or labeling protocols (e.g., microarrays). Consequently, accurate whole-genome amplification (WGA) of single-cell DNA is required for reliable genetic analysis (e.g., NGS) and is particularly important when genomic DNA is limited. The use of single-cell WGA has enabled the analysis of genomic heterogeneity of individual cells (e.g., somatic genomic variation in tumor cells). This unit describes how the genome of single cells can be used for WGA for further genomic studies, such as NGS. Recommendations for isolation of single cells are given and common sources of errors are discussed. Curr. Protoc. Mol. Biol. 104:7.14.1-7.14.11. © 2013 by John Wiley & Sons, Inc.


  • single cell;
  • genome analysis;
  • next-generation sequencing;
  • somatic genome variation