Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq

Karen M. Mann, Justin Y. Newberg, Michael A. Black, Devin J. Jones, Felipe Amaya-Manzanares, Liliana Guzman-Rojas, Takahiro Kodama, Jerrold M. Ward, Alistair G. Rust, Louise Van Der Weyden, Christopher Chin Kuan Yew, Jill L. Waters, Marco L. Leung, Keith Rogers, Susan M. Rogers, Leslie A. Mcnoe, Luxmanan Selvanesan, Nicholas Navin, Nancy A. Jenkins, Neal G. CopelandMichael B. Mann

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


A central challenge in oncology is how to kill tumors containing heterogeneous cell populations defined by different combinations of mutated genes. Identifying these mutated genes and understanding how they cooperate requires single-cell analysis, but current single-cell analytic methods, such as PCR-based strategies or whole-exome sequencing, are biased, lack sequencing depth or are cost prohibitive. Transposon-based mutagenesis allows the identification of early cancer drivers, but current sequencing methods have limitations that prevent single-cell analysis. We report a liquid-phase, capture-based sequencing and bioinformatics pipeline, Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq), that facilitates sequencing of transposon insertion sites from single tumor cells in a SB mouse model of myeloid leukemia (ML). SBCapSeq analysis of just 26 cells from one tumor revealed the tumor's major clonal subpopulations, enabled detection of clonal insertion events not detected by other sequencing methods and led to the identification of dominant subclones, each containing a unique pair of interacting gene drivers along with three to six cooperating cancer genes with SB-driven expression changes.

Original languageEnglish (US)
Pages (from-to)962-972
Number of pages11
JournalNature Biotechnology
Issue number9
StatePublished - Sep 1 2016

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology
  • Molecular Medicine
  • Biomedical Engineering


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