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Updated: Jan 20, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing
Allegra A Petti1,2, Stephen R Williams3, Christopher A Miller1,2
1Division of Oncology, Washington University School of Medicine, St. Louis, MO, USA.
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.
Insights
This study links genetic mutations to gene expression in Acute Myeloid Leukemia (AML) cells. Researchers identified distinct expression patterns for different AML cell groups, aiding in subclone identification.
Area of Science:
- Genomics
- Molecular Biology
- Cancer Research
Background:
- Tumors exhibit genetic heterogeneity with distinct subclonal populations and phenotypes.
- Single-cell RNA sequencing reveals transcriptional heterogeneity in tumors, but its link to subclonal architecture is unclear.
Purpose of the Study:
- To investigate the relationship between gene expression heterogeneity and subclonal architecture in Acute Myeloid Leukemia (AML).
- To integrate whole genome sequencing with single-cell RNA sequencing to connect genotype with phenotype in AML.
Main Methods:
- Applied whole genome sequencing and 10x Genomics Chromium Single Cell 5' Gene Expression workflow to five cryopreserved AML samples.
- Analyzed data to identify tumor-specific mutations within individual cells and distinguish AML cells from normal cells.
Main Results:
- Identified hundreds to thousands of cells with tumor-specific mutations per sample.
- Discovered expression signatures associated with subclonal mutations in AML.
- Found potential cell surface markers for purifying AML subclones.
Conclusions:
- The integrated approach successfully connects genotype to phenotype in heterogeneous AML samples.
- This method is broadly applicable for studying phenotypically and genetically heterogeneous samples.
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