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Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Authors :
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
Publication Year :
2018
Publisher :
Cold Spring Harbor Laboratory, 2018.

Abstract

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.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....66e1c35ff77b4312f0f0395f98937d5c
Full Text :
https://doi.org/10.1101/411058