Optimizing sparse sequencing of single cells for highly multiplex copy number profiling
- Timour Baslan1,2,9,
- Jude Kendall1,
- Brian Ward3,
- Hilary Cox1,
- Anthony Leotta1,
- Linda Rodgers1,
- Michael Riggs1,
- Sean D'Italia1,
- Guoli Sun1,
- Mao Yong4,
- Kristy Miskimen5,
- Hannah Gilmore6,
- Michael Saborowski7,
- Nevenka Dimitrova4,
- Alexander Krasnitz1,
- Lyndsay Harris5,8,
- Michael Wigler1 and
- James Hicks1
- 1Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA;
- 2Department of Molecular and Cellular Biology, Stony Brook University, Stony Brook, New York 11790, USA;
- 3Sigma-Aldrich Research Technology, Saint Louis, Missouri 63103, USA;
- 4Phillips Research North America, Biomedical Informatics, Briarcliff Manor, New York 10510, USA;
- 5Division of Hematology/Oncology, Department of Medicine, Case Western Reserve School of Medicine, Cleveland, Ohio 44106, USA;
- 6Department of Pathology, University Hospitals Case Medical Center and Case Western Reserve University, Cleveland, Ohio 44106, USA;
- 7Clinic for Gastroenterology, Hepatology, and Endocrinology, Hannover Medical School, 30625 Hannover, Germany;
- 8Seidman Cancer Center, University Hospitals of Case Western, Cleveland, Ohio 44106, USA
- Corresponding author: hicks{at}cshl.edu
Abstract
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.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.188060.114. Freely available online through the Genome Research Open Access option
- Received December 3, 2014.
- Accepted March 19, 2015.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0.
