Calibrating genomic and allelic coverage bias in single-cell sequencing

Nat Commun. 2015 Apr 16;6:6822. doi: 10.1038/ncomms7822.

Abstract

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1-10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles*
  • Bias
  • Calibration
  • Cell Line
  • Gene Library
  • Genome, Human*
  • Genomics / methods*
  • Humans
  • Nucleic Acid Amplification Techniques
  • Polymerase Chain Reaction
  • Sequence Analysis, DNA
  • Single-Cell Analysis / methods*
  • Statistics as Topic*