A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing

Allegra A. Petti, Stephen R. Williams, Christopher A. Miller, Ian T. Fiddes, Sridhar N. Srivatsan, David Y. Chen, Catrina C. Fronick, Robert S. Fulton, Deanna M. Church, Timothy J. Ley

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Virtually all tumors are genetically heterogeneous, containing mutationally-defined subclonal cell populations that often have distinct phenotypes. Single-cell RNA-sequencing has revealed that a variety of tumors are also transcriptionally heterogeneous, but the relationship between expression heterogeneity and subclonal architecture is unclear. Here, we address this question in the context of Acute Myeloid Leukemia (AML) by integrating whole genome sequencing with single-cell RNA-sequencing (using the 10x Genomics Chromium Single Cell 5’ Gene Expression workflow). Applying this approach to five cryopreserved AML samples, we identify hundreds to thousands of cells containing tumor-specific mutations in each case, and use the results to distinguish AML cells (including normal-karyotype AML cells) from normal cells, identify expression signatures associated with subclonal mutations, and find cell surface markers that could be used to purify subclones for further study. This integrative approach for connecting genotype to phenotype is broadly applicable to any sample that is phenotypically and genetically heterogeneous.

Original languageEnglish
Article number3660
JournalNature communications
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2019

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