Single-cell RNA-seq reveals a distinct transcriptome signature of aneuploid hematopoietic cells

Xin Zhao, Shouguo Gao, Zhijie Wu, Sachiko Kajigaya, Xingmin Feng, Qingguo Liu, Danielle M. Townsley, James Cooper, Jinguo Chen, Keyvan Keyvanfar, Maria del Pilar Fernandez Ibanez, Xujing Wang and Neal S. Young

Key points

  • We distinguished aneuploid cells from diploid cells within the hematopoietic stem/progenitor cells using single-cell RNA-seq.

  • Monosomy 7 cells showed downregulated pathways involved in immune response and maintenance of DNA stability.


Cancer cells frequently exhibit chromosomal abnormalities. Specific cytogenetic aberrations often are predictors of outcome, especially in hematologic neoplasms, as for example monosomy 7 in myeloid malignancies. The functional consequences of aneuploidy at the cellular level are difficult to assess, due to lack of convenient markers to distinguish abnormal from diploid cells. We performed single-cell RNA sequencing (scRNA-seq) to study hematopoietic stem and progenitor cells (HSPCs) from the bone marrow of four healthy donors and of five patients with bone marrow failure and chromosome gain or loss. In total, transcriptome sequences were obtained from 391 control cells and 588 cells from patients. We characterized normal hematopoiesis as binary differentiation from stem cells to erythroid and myeloid-lymphoid pathways. Aneuploid cells were distinguished from diploid cells in patient samples by computational analyses of read fractions and gene expression of individual chromosomes. We confirmed assignment of aneuploidy to individual cells: quantitatively, by copy number variation and, qualitatively, by loss of heterozygosity. When we projected patients' single cells onto the map of normal hematopoiesis, diverse patterns were observed, broadly reflecting clinical phenotypes. Patients' monosomy 7 cells showed downregulation of genes involved in immune response, and DNA damage checkpoint and apoptosis pathways, which may contribute to the clonal expansion of monosomy 7 cells with accumulated gene mutations. scRNA-seq is a powerful technique to infer the functional consequences of chromosome gain and loss and to explore gene targets for directed therapy.

  • Submitted August 30, 2017.
  • Accepted October 3, 2017.