PROJECT SUMMARY Initiation and evolution of most solid tumors involve complex genomic rearrangements in addition to point mutations – all of which can contribute to cancer progression and to the evolution of resistance to therapeutics. Single-cell whole genome sequencing (scWGS) has proven invaluable for the identification of tumor subpopulations and in advancing our understanding of clonal dynamics and tumor evolution. Despite the value of scWGS, there is a dearth of commercially-available options that provide enough cell throughput (i.e. power) and/or genomic coverage to fully catalogue and characterize clonal populations within a tumor sample. This can be particularly problematic when rare, possible therapy-resistant, subpopulations are present within a tumor that may elude detection using existing methodologies. Here we will solve the accessibility problem by developing technologies that leverage widely-available instrumentation and off-the-shelf reagents. We previously described proof-of-principle technologies to construct scWGS libraries contained within the nucleus (in situ) of each cell that are then carried through cell barcoding using our custom workflow. We will extend, develop, and adapt these technologies to provide three workflows that will meet the needs of the cancer research community by providing readily-accessible order-of-magnitude improvements to cell throughput, cell coverage and cost savings for scWGS analysis over current options. The first is focused on high cell throughput using widely available instrumentation; the second leverages our high- content chemistry to produce high-coverage single cell genomic profiles with reduced reagents and improved throughput; and finally, the third approach implements target capture to target exonic sequence or other regions of interest to reduce sequencing costs. Each of these is targeted to meet the needs of specific areas of cancer research, from basic science to clinical, and share the theme of accessibility.

PROJECT NARRATIVE Single-cell genome sequencing has proven to be a valuable tool to advance our understanding of tumor initiation, evolution, and resistance by providing the ability to catalogue the genetic subclones present within a tumor. However, current methodologies to profile single-cell genomes are either underpowered and expensive, or require designer reagents that are inaccessible to most research groups. Here we will develop technologies that produce improved data quantity and quality at a reduced cost that target the three major applications of single-cell genomics in cancer biology.