Integrated single-cell analysis maps the continuous regulatory landscape of human hematopoietic differentiation

By Jason D. Buenrostro, M. Corces, Caleb A Lareau, Beijing Wu, Alicia N. Schep, Martin J. Aryee, R. Majeti, Howard Y. Chang, W.J. Greenleaf. Cell, 2018

609 citations recorded by the source corpus.

Human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While the chromatin accessibility landscape of this process has been explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging. We collected single-cell chromatin accessibility profiles across 10 populations of immunophenotypically-defined human hematopoietic cell types and constructed a chromatin accessibility landscape of human hematopoiesis to characterize differentiation trajectories. We find variation consistent with lineage-bias toward different developmental branches in multipotent cell-types. We observe heterogeneity within common myeloid progenitors (CMPs) and granulocyte-macrophage progenitors (GMPs), and develop a strategy to partition GMPs along their differentiation trajectory. Furthermore, we integrated scRNA-seq data to associate transcription factors to chromatin accessibility changes, and regulatory elements to target genes through correlations of expression and regulatory element accessibility. Overall, this work provides a framework for integrative exploration of complex regulatory dynamics in a primary human tissue at single-cell resolution.

Subfields: Immunology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2774e4b8eca2041a3bc9f41dc7f4cb0368d4474b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Caleb A. Lareau
2. Miguel Andrade
3. Jason D. Buenrostro

Citations in the corpus

• CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data (2022, background): “One of the most widespread and remarkable applications is to dissect complex cellular heterogeneity and construct comprehensive maps of all cell types in different tissues or organs (8,9).”
• CellMarker: a manually curated resource of cell markers in human and mouse (2018, background): “One of the most attractive applications of single-cell RNA sequencing technique is to decode complex cellular heterogeneity and create comprehensive reference maps of all cell types in different tissues/organs (8,9).”
• Assessment of computational methods for the analysis of single-cell ATAC-seq data (2019, methodology): “We observed that for 10X Genomics and sci-ATAC-seq the percentage of reads mappable to blacklisted regions is only ~ 1%, while for the Fluidigm C1 based assay used in Buenrostro2018 is much higher, ~ 50%.”
• cisTopic: cis-Regulatory topic modelling on single-cell ATAC-seq data (2019, positive): “This work (GSE114557) + H3K27Ac profiles of 3 melanoma cell lines: A375, MM029 and MM032 + Omni-ATAC during an EMT-like transition in melanoma (8 samples): Two cell lines (MM057 and MM087) under SOX10KD and sampling on different time points (0h, 24h, 48h, 72h) + scATAC-seq during an EMT-like transit”