RT Journal
A1 Baslan, Timour
A1 Kendall, Jude
A1 Ward, Brian
A1 Cox, Hilary
A1 Leotta, Anthony
A1 Rodgers, Linda
A1 Riggs, Michael
A1 D'Italia, Sean
A1 Sun, Guoli
A1 Yong, Mao
A1 Miskimen, Kristy
A1 Gilmore, Hannah
A1 Saborowski, Michael
A1 Dimitrova, Nevenka
A1 Krasnitz, Alexander
A1 Harris, Lyndsay
A1 Wigler, Michael
A1 Hicks, James
T1 Optimizing sparse sequencing of single cells for highly multiplex copy number profiling
JF Genome Research 
JO Genome Research 
YR 2015 
FD May 01 
VO 25 
IS 5 
SP 714 
OP 724 
DO 10.1101/gr.188060.114 
UL http://genome.cshlp.org/content/25/5/714.abstract 
AB Genome-wide analysis at the level of single cells has recently emerged as a powerful tool to dissect genome heterogeneity in cancer, neurobiology, and development. To be truly transformative, single-cell approaches must affordably accommodate large numbers of single cells. This is feasible in the case of copy number variation (CNV), because CNV determination requires only sparse sequence coverage. We have used a combination of bioinformatic and molecular approaches to optimize single-cell DNA amplification and library preparation for highly multiplexed sequencing, yielding a method that can produce genome-wide CNV profiles of up to a hundred individual cells on a single lane of an Illumina HiSeq instrument. We apply the method to human cancer cell lines and biopsied cancer tissue, thereby illustrating its efficiency, reproducibility, and power to reveal underlying genetic heterogeneity and clonal phylogeny. The capacity of the method to facilitate the rapid profiling of hundreds to thousands of single-cell genomes represents a key step in making single-cell profiling an easily accessible tool for studying cell lineage.