Dataset Information

Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape.

ABSTRACT: Large-scale single-cell RNA sequencing (scRNA-seq) studies that profile hundreds of thousands of cells are becoming increasingly common, overwhelming existing analysis pipelines. Here, we describe how to enhance and accelerate single-cell data analysis by summarizing the transcriptomic heterogeneity within a dataset using a small subset of cells, which we refer to as a geometric sketch. Our sketches provide more comprehensive visualization of transcriptional diversity, capture rare cell types with high sensitivity, and reveal biological cell types via clustering. Our sketch of umbilical cord blood cells uncovers a rare subpopulation of inflammatory macrophages, which we experimentally validated. The construction of our sketches is extremely fast, which enabled us to accelerate other crucial resource-intensive tasks, such as scRNA-seq data integration, while maintaining accuracy. We anticipate our algorithm will become an increasingly essential step when sharing and analyzing the rapidly growing volume of scRNA-seq data and help enable the democratization of single-cell omics.

SUBMITTER: Hie B

PROVIDER: S-EPMC6597305 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape.

Hie Brian B Cho Hyunghoon H DeMeo Benjamin B Bryson Bryan B Berger Bonnie B

Cell systems 20190605 6

Large-scale single-cell RNA sequencing (scRNA-seq) studies that profile hundreds of thousands of cells are becoming increasingly common, overwhelming existing analysis pipelines. Here, we describe how to enhance and accelerate single-cell data analysis by summarizing the transcriptomic heterogeneity within a dataset using a small subset of cells, which we refer to as a geometric sketch. Our sketches provide more comprehensive visualization of transcriptional diversity, capture rare cell types wi ...[more]

PMID: 31176620

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Project description:Key Points • A heme rheostat regulates normal erythropoiesis as well as the ineffective erythropoiesis of DBA and MDS-5q.• Marrow cells from patients with MDS-5q with or without the deletion of 5q share transcription profiles. Visual Abstract Abstract The anemias of myelodysplastic syndrome (MDS) and Diamond Blackfan anemia (DBA) are generally macrocytic and always reflect ineffective erythropoiesis yet result from diverse genetic mutations. To delineate shared mechanisms that lead to cell death, we studied the fate of single erythroid marrow cells from individuals with DBA or MDS-5q. We defined an unhealthy (vs healthy) differentiation trajectory using transcriptional pseudotime and cell surface proteins. The pseudotime trajectories diverge immediately after cells upregulate transferrin receptor (CD71), import iron, and initiate heme synthesis, although cell death occurs much later. Cells destined to die express high levels of heme-responsive genes, including ribosomal protein and globin genes, whereas surviving cells downregulate heme synthesis and upregulate DNA damage response, hypoxia, and HIF1 pathways. Surprisingly, 24% ± 12% of cells from control subjects follow the unhealthy trajectory, implying that heme might serve as a rheostat directing cells to live or die. When heme synthesis was inhibited with succinylacetone, more DBA cells followed the healthy trajectory and survived. We also noted high numbers of messages with retained introns that increased as erythroid cells matured, confirmed the rapid cycling of colony forming unit–erythroid, and demonstrated that cell cycle timing is an invariant property of differentiation stage. Including unspliced RNA in pseudotime determinations allowed us to reliably align independent data sets and accurately query stage-specific transcriptomic changes. MDS-5q (unlike DBA) results from somatic mutation, so many normal (unmutated) erythroid cells persist. By independently tracking erythroid differentiation of cells with and without chromosome 5q deletions, we gained insight into why 5q+ cells cannot expand to prevent anemia.

Dataset Information

Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape.

Publications

Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape.

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