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Nat Methods. 2017 Mar;14(3):302-308. doi: 10.1038/nmeth.4154. Epub 2017 Jan 30.

Sequencing thousands of single-cell genomes with combinatorial indexing.

Author information

1
Department of Molecular &Medical Genetics, Oregon Health &Science University, Portland, Oregon, USA.
2
Program in Molecular &Cellular Biosciences, Oregon Health &Science University, Portland, Oregon, USA.
3
Oregon National Primate Research Center, Beaverton, Oregon, USA.
4
Advanced Research Group, Illumina Inc., San Diego, California, USA.
5
Department of Cell, Developmental &Cancer Biology, Oregon Health &Science University, Portland, Oregon, USA.
6
Knight Cancer Institute, Portland, Oregon, USA.
7
Department of Behavioral Neurosciences, Oregon Health &Science University, Portland, Oregon, USA.
8
Knight Cardiovascular Institute, Portland, Oregon, USA.

Abstract

Single-cell genome sequencing has proven valuable for the detection of somatic variation, particularly in the context of tumor evolution. Current technologies suffer from high library construction costs, which restrict the number of cells that can be assessed and thus impose limitations on the ability to measure heterogeneity within a tissue. Here, we present single-cell combinatorial indexed sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single-cell libraries for detection of somatic copy-number variants. We constructed libraries for 16,698 single cells from a combination of cultured cell lines, primate frontal cortex tissue and two human adenocarcinomas, and obtained a detailed assessment of subclonal variation within a pancreatic tumor.

PMID:
28135258
PMCID:
PMC5908213
DOI:
10.1038/nmeth.4154
[Indexed for MEDLINE]
Free PMC Article

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