Development and application of microscale technology for single-cell sequencing

Genomic heterogeneity is a central feature of many cancers and plays a critical role in disease initiation, progression, and response to treatment. As a result, development of robust, scalable and high-fidelity single-cell genomics has become critical to understanding the structure and dynamics of cellular heterogeneity in cancer. However, conventional methods based on library construction from pre-amplified samples introduce artefacts and coverage bias, and are also prohibitively expensive for large-scale studies of thousands of single cells. In this thesis I describe the development and application of technology that uses nanolitre volume transposase reactions to enable the streamlined preparation of single-cell next-generation sequencing libraries without the need for prior amplification. This workflow permits the economical and high-throughput analysis of large numbers of cells. I show the application of the direct library preparation (DLP) method to examine whole genomes from cell lines and murine xenografts derived from a primary triple-negative human breast cancer tumour. Low-coverage sequencing and analysis revealed that the lack of pre-amplification resulted in high uniform coverage amenable to copy number inference, with greater uniformity of coverage and more reliable detection of megabase-scale copy number alterations than existing methods. Pooling of individual cells was used to generate “bulk-equivalent” genomes with equal coverage breadth and uniformity to a standard bulk genome with the same sequencing depth. Phylogenetic analysis of hundreds of single-cell copy number profiles revealed minor clonal sub-populations that were undetectable in bulk measurements. This thesis presents new technology for low-depth sequencing and pooling of single-cell libraries constructed without pre-amplification, and demonstrates that this strategy can provide an effective replacement for conventional bulk sequencing strategies, permitting detailed reconstruction of copy number clonal lineages as well as standard inference of other variants, without significantly increasing the total sequencing effort.Science, Faculty ofGraduat