TY - JOUR
T1 - A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing
AU - Petti, Allegra A.
AU - Williams, Stephen R.
AU - Miller, Christopher A.
AU - Fiddes, Ian T.
AU - Srivatsan, Sridhar N.
AU - Chen, David Y.
AU - Fronick, Catrina C.
AU - Fulton, Robert S.
AU - Church, Deanna M.
AU - Ley, Timothy J.
N1 - Funding Information:
Supported by the NCI K12 program (CA167540, R. Govindan, PI) to A.P., an R50 CA211782 to C.M., and an R35 CA197561 and P01 CA101937 to T.L. We thank Jonathan L. Weinstein, PhD for advice on statistical methodology, and Julia Lau for construction of the Chromium single-cell gene expression libraries. We also thank Matthew Christopher, MD, PhD and Amanda Smith, PhD for developing the methods used for preparing cryovials of AML cells for scRNA-seq.
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85070753846&partnerID=8YFLogxK
U2 - 10.1038/s41467-019-11591-1
DO - 10.1038/s41467-019-11591-1
M3 - Article
C2 - 31413257
AN - SCOPUS:85070753846
SN - 2041-1723
VL - 10
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 3660
ER -