Which dataset
would you like to
analyze in BBrowser?

Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia.

Jeffrey M. Granja, Sandy Klemm, Lisa M. McGinnis, Arwa S. Kathiria, Anja Mezger, M. Ryan Corces, Benjamin Parks, Eric Gars, Michaela Liedtke, Grace X. Y. Zheng, Howard Y. Chang, Ravindra Majeti, William J. Greenleaf

Identifying the causes of human diseases requires deconvolution of abnormal molecular phenotypes spanning DNA accessibility, gene expression and protein abundance1,2,3. We present a single-cell framework that integrates highly multiplexed protein quantification, transcriptome profiling and analysis of chromatin accessibility. Using this approach, we establish a normal epigenetic baseline for healthy blood development, which we then use to deconvolve aberrant molecular features within blood from patients with mixed-phenotype acute leukemia4,5. Despite widespread epigenetic heterogeneity within the patient cohort, we observe common malignant signatures across patients as well as patient-specific regulatory features that are shared across phenotypic compartments of individual patients. Integrative analysis of transcriptomic and chromatin-accessibility maps identified 91,601 putative peak-to-gene linkages and transcription factors that regulate leukemia-specific genes, such as RUNX1-linked regulatory elements proximal to the marker gene CD69. These results demonstrate how integrative, multiomic analysis of single cells within the framework of normal development can reveal both distinct and shared molecular mechanisms of disease from patient samples.

Download bbrowser to analyze now

Species: human
Number of cells: 53632
Number of downloads: 88
Study size: 3GB
Uploaded at: