Comparative study of whole genome amplification and next generation sequencing performance of single cancer cells

Abstract

// Anna Babayan 1 , Malik Alawi 2, 3 , Michael Gormley 4 , Volkmar Müller 5 , Harriet Wikman 1 , Ryan P. McMullin 6 , Denis A. Smirnov 4 , Weimin Li 4 , Maria Geffken 7 , Klaus Pantel 1 and Simon A. Joosse 1 1 Department of Tumor Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 2 Bioinformatics Core, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 3 Heinrich-Pette-Institute, Leibniz-Institute for Experimental Virology (HPI), Hamburg, Germany 4 Janssen Research and Development, Spring House, PA, USA 5 Department of Gynecology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 6 LabConnect LLC, Seattle, WA, USA 7 Department of Transfusion Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany Correspondence to: Klaus Pantel, email: pantel@uke.de Simon A. Joosse, email: s.joosse@uke.de Keywords: NGS, WGA, SNP, allelic dropout, CellSave Received: April 06, 2016      Accepted: June 09, 2016      Published: July 19, 2016 ABSTRACT BACKGROUND: Whole genome amplification (WGA) is required for single cell genotyping. Effectiveness of currently available WGA technologies in combination with next generation sequencing (NGS) and material preservation is still elusive. RESULTS: In respect to the accuracy of SNP/mutation, indel, and copy number aberrations (CNA) calling, the HiSeq2000 platform outperformed IonProton in all aspects. Furthermore, more accurate SNP/mutation and indel calling was demonstrated using single tumor cells obtained from EDTA-collected blood in respect to CellSave-preserved blood, whereas CNA analysis in our study was not detectably affected by fixation. Although MDA-based WGA yielded the highest DNA amount, DNA quality was not adequate for downstream analysis. PCR-based WGA demonstrates superiority over MDA-PCR combining technique for SNP and indel analysis in single cells. However, SNP calling performance of MDA-PCR WGA improves with increasing amount of input DNA, whereas CNA analysis does not. The performance of PCR-based WGA did not significantly improve with increase of input material. CNA profiles of single cells, amplified with MDA-PCR technique and sequenced on both HiSeq2000 and IonProton platforms, resembled unamplified DNA the most. MATERIALS AND METHODS: We analyzed the performance of PCR-based, multiple-displacement amplification (MDA)-based, and MDA-PCR combining WGA techniques (WGA kits Ampli1, REPLI-g, and PicoPlex, respectively) on single and pooled tumor cells obtained from EDTA- and CellSave-preserved blood and archival material. Amplified DNA underwent exome-Seq with the Illumina HiSeq2000 and ThermoFisher IonProton platforms. CONCLUSION: We demonstrate the feasibility of single cell genotyping of differently preserved material, nevertheless, WGA and NGS approaches have to be chosen carefully depending on the study aims.