Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing.

Emma Laks, Andrew McPherson, Hans Zahn, Daniel Lai, Adi Steif, Jazmine Brimhall, Justina Biele, Beixi Wang, Tehmina Masud, Jerome Ting, Diljot Grewal, Cydney Nielsen, Samantha Leung, Viktoria Bojilova, Maia Smith, Oleg Golovko, Steven Poon, Peter Eirew, Farhia Kabeer, Teresa Ruiz de Algara, So Ra Lee, M Jafar Taghiyar, Curtis Huebner, Jessica Ngo, Tim Chan, Spencer Vatrt-Watts, Pascale Walters, Nafis Abrar, Sophia Chan, Matt Wiens, Lauren Martin, R Wilder Scott, T Michael Underhill, Elizabeth Chavez, Christian Steidl, Daniel Da Costa, Yussanne Ma, Robin J N Coope, Richard Corbett, Stephen Pleasance, Richard Moore, Andrew J Mungall, Colin Mar, Fergus Cafferty, Karen Gelmon, Stephen Chia, , Marco A Marra, Carl Hansen, Sohrab P Shah, Samuel Aparicio, Cell 179, 1207-1221.e22 (2019)
DOI
10.1016/j.cell.2019.10.026
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Abstract

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.