PO-336 ThruPLEX® and PicoPLEX® technologies for rare alleles and copy number variation detection from cell-free DNA and single human cancer cells

Introduction Liquid biopsies provide a non-invasive method to acquire the genetic information provided in cell-free DNA (cfDNA) as well as in single circulating tumour cells. Access to this genetic information through next-generation sequencing (NGS) identifies mutations and alterations such as Copy Number Variation (CNV) that play a role in cancer and other diseases. Material and methods The key to identifying rare mutations is improved sequencing accuracy and the ability to distinguish between biological and PCR duplicates. ThruPLEX Tag-seq was developed with the addition of unique molecular tags (UMTs) to improve sequencing accuracy by accounting for polymerase and sequencing errors and to increase confidence in rare allele identification. Whole Genome Amplification (WGA) for CNV detection was achieved by the thermal cycling quasi-random primed library chemistry of the PicoPLEX DNA-seq single-cell NGS library prep kit. Results and discussions ThruPLEX Tag-seq libraries were prepared using 10–30 ng of Horizon Discovery’s Multiplex I cfDNA Reference Standard Set containing six single nucleotide variants (SNV) for 4 different genes (EGFR, KRAS, NRAS, PIK3CA) present at 0.5%–5% allele frequency. The libraries were enriched with either a 110 kb or 240 kb custom panel or the Agilent ClearSeq Comprehensive Cancer Panel. Enriched libraries were sequenced witan average total read coverage of approximately 5,000X and analysed with and without the UMTs. For CNV analysis in single cells, a bar-coded PicoPLEX DNA-seq library was synthesised and amplified from 6 single cells from either PBMCs and clonally-expanded PC3 prostate cancer cells. Sequencing was performed on a MiSeq v2 and reads were mapped using BWA-MEM, processed in Picard_Mark_Duplicates, and further characterised in DNA nexus.classic. All PC3 cells showed reproducible CNV calling, however none of the lymphocyte samples showed any CNVs. Accurate CNV calls for PC3 cells were achieved even at when fastq files were randomly downsampled to 1 50 000 read pairs. Conclusion Therefore, use of UMTs in the preparation of NGS libraries from cfDNA enhances sequencing accuracy: by distinguishing between biological duplicates and PCR duplicates, increasing read coverage and decreasing background noise, reducing false positives, and in more confident mutation calls. PicoPLEX DNA-seq NGS libraries have a very simple and fast workflow that is suitable reproducible CNV detection in single cells even at low 0.002X average coverage.