Abstract 2394: Scalable, rapid and affordable low-pass whole genome sequencing method for single-cell copy-number profiling on LM-PCR based WGA products

Abstract

Abstract Introduction: Genome-wide profiling of copy-number alterations (CNA) in single cells enables the characterization and investigation of genomic heterogeneity and evolution in tumor cell populations such as individual circulating tumor cells (CTCs), or disaggregated solid tumors. Ampli1™ WGA is a commercially available kit for whole-genome amplification from single cells suitable for array comparative genomic hybridization (aCGH), which is currently the gold standard for genetic diagnosis of CNA. However, labor and reagent costs limit aCGH applicability. Here we introduce for the first time a rapid, high-throughput low-pass Whole Genome Sequencing (WGS)-based method for CNA analysis (LPCNA) on single cells, enabling simultaneous profiling of multiple cells at lower cost and effort. Methods: Six single cells from NCI-H23, NCI-H661 and NCI-H1650 cell lines and 19 white blood cells (WBCs) were amplified using Ampli1™ WGA Kit. Only 5μl (1/10th of total WGA product) were used as sample input for LPCNA. Purified WGA products were processed for each sample in a single-tube, one-step reaction resulting in IonTorrent-compatible indexed libraries. Samples were pooled and size-selected to recover fragments with a length ranging from 300 to 400 bp. Following purification and template preparation, pools were sequenced on Ion 318™v2 Chips. Array CGH was performed for comparison, using Agilent SurePrint 4×180k arrays as previously reported. CNA analysis was performed using Control-FREEC for low-pass WGS data, or Agilent Genome Workbench for aCGH. Results: By exploiting the deterministic nature of Ampli1™ whole genome amplification, we devised a method to generate IonTorrent compatible libraries in a single reaction, drastically reducing time of bench work and cost. Method accuracy has been assessed by comparing the copy number profiles generated by our approach with about 870,000 reads/sample (average genome coverage of 0.064x, range 0.051-0.073) with those obtained by a validated aCGH method. Very good agreement in gain and loss profiles was achieved for all single tumor cells analyzed. As expected WBC analysis resulted in normal copy-number profiles with autosomes copy number = 2, with minimal false-positive rate (<0.6% at a resolution of 760kb with 618k reads). Highlights: This innovative low-pass sequencing approach for CNA detection on single cells enables high level multiplexing on different NGS platforms. The approach is highly scalable and flexible. From few (6-8) samples (IonTorrent PGM, 318™v2 Chip), up to 96 samples (Ion Proton, Ion PI™ Chip v3) can be processed in a single run. This approach meets the need for rapid results (<7h turnaround time for library preparation) and affordable cost required for massively parallel single-cell analysis such as multiple tumor cells or CTCs. This work has been carried out within IMI CANCER-ID consortium (www.cancer-id.eu). Citation Format: Genny Buson, Paola Tononi, Claudio Forcato, Francesca Fontana, Gianni Medoro, Rui Neves, Birte Möhlendick, Nikolas Stoecklein, Nicolò Manaresi. Scalable, rapid and affordable low-pass whole genome sequencing method for single-cell copy-number profiling on LM-PCR based WGA products. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2394.