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Title: Single-cell paired-end genome sequencing reveals structural variation per cell cycle
Authors: Voet, Thierry ×
Kumar, Parveen
Van Loo, Peter
Cooke, Susanna L
Marshall, John
Lin, Meng-Lay
Zamani Esteki, Masoud
Van der Aa, Niels
Mateiu, Ligia
McBride, David J
Bignell, Graham R
McLaren, Stuart
Teague, Jon
Butler, Adam
Raine, Keiran
Stebbings, Lucy A
Quail, Michael A
D'Hooghe, Thomas
Moreau, Yves
Futreal, P Andrew
Stratton, Michael R
Vermeesch, Joris #
Campbell, Peter J #
Issue Date: Jul-2013
Publisher: Oxford University Press
Series Title: Nucleic acids research vol:41 issue:12 pages:6119-6138
Abstract: The nature and pace of genome mutation is largely unknown. Because standard methods sequence DNA from populations of cells, the genetic composition of individual cells is lost, de novo mutations in cells are concealed within the bulk signal and per cell cycle mutation rates and mechanisms remain elusive. Although single-cell genome analyses could resolve these problems, such analyses are error-prone because of whole-genome amplification (WGA) artefacts and are limited in the types of DNA mutation that can be discerned. We developed methods for paired-end sequence analysis of single-cell WGA products that enable (i) detecting multiple classes of DNA mutation, (ii) distinguishing DNA copy number changes from allelic WGA-amplification artefacts by the discovery of matching aberrantly mapping read pairs among the surfeit of paired-end WGA and mapping artefacts and (iii) delineating the break points and architecture of structural variants. By applying the methods, we capture DNA copy number changes acquired over one cell cycle in breast cancer cells and in blastomeres derived from a human zygote after in vitro fertilization. Furthermore, we were able to discover and fine-map a heritable inter-chromosomal rearrangement t(1;16)(p36;p12) by sequencing a single blastomere. The methods will expedite applications in basic genome research and provide a stepping stone to novel approaches for clinical genetic diagnosis.
ISSN: 0305-1048
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Department of Human Genetics - miscellaneous
Laboratory of Reproductive Genomics
Human Genome Laboratory
Organ Systems (+)
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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