Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires
| Autor: | Bojilova, Vatrt-Watts S, Underhill Mt, Emma Laks, Taghiyar Mj, Stephen Pleasance, Brimhall J, Samuel Aparicio, Chan Sy, Andrew McPherson, Richard D. Moore, Masud T, Ngo J, Costa Dd, Wang B, Abrar N, Martin L, Christian Steidl, Marco A. Marra, Elizabeth A. Chavez, Coope Rjn, Lee, Farhia Kabeer, Nielsen C, Yussanne Ma, Grewal D, Golovko O, Matt Wiens, Adi Steif, Carl L. Hansen, Hans Zahn, Pascale Walters, Sohrab P. Shah, Peter Eirew, Daniel Lai, Andrew J. Mungall, de Algara Tr, Scott Rw, Steven S.S. Poon, Justina Biele, Chan T, Leung S, Maia A. Smith, Huebner C, Richard Corbett |
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| Rok vydání: | 2018 |
| Předmět: |
Whole genome sequencing
0303 health sciences education.field_of_study Mutation Population Genomics Computational biology Biology medicine.disease_cause Genome DNA sequencing Replication (computing) 03 medical and health sciences 0302 clinical medicine 030220 oncology & carcinogenesis medicine education Mitosis 030304 developmental biology |
| Popis: | SummaryEssential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity. |
| Databáze: | OpenAIRE |
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