Densely interconnected transcriptional circuits control cell states in human hematopoiesis

By Noa Novershtern, Aravind Subramanian, Lee N. Lawton, Raymond H. Mak, W. Nicholas Haining, M. McConkey, Naomi Habib, Nir Yosef, Cindy Y. Chang, T. Shay and 15 more. Cell, 2011

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While many individual transcription factors are known to regulate hematopoietic differentiation, major aspects of the global architecture of hematopoiesis remain unknown. Here, we profiled gene expression in 38 distinct purified populations of human hematopoietic cells and used probabilistic models of gene expression and analysis of cis-elements in gene promoters to decipher the general organization of their regulatory circuitry. We identified modules of highly co-expressed genes, some of which are restricted to a single lineage, but most are expressed at variable levels across multiple lineages. We found densely interconnected cis-regulatory circuits and a large number of transcription factors that are differentially expressed across hematopoietic states. These findings suggest a more complex regulatory system for hematopoiesis than previously assumed.

Subfields: Cell Biology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c6a692b09271e7aa593c5a6048a177e76f13e6a7

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Citations in the corpus

Hematopoiesis: a human perspective. (2012, background): “human hematopoietic cell types, including precursors and mature cells (Novershtern et al., 2011).”
NK Cells Stimulate Recruitment of cDC1 into the Tumor Microenvironment Promoting Cancer Immune Control (2018, background): “See also Figure S5. dataset of 38 populations of human hematopoietic cells (Novershtern et al., 2011).”
Revealing the vectors of cellular identity with single-cell genomics (2016, background): “In pathological settings, especially cancer 99,135,136 , such hybrid states may reflect either transitions (below) or the intrinsic abnormal mixture of different functional modules (N.Y., A.R. and colleagues 135 ).”
The genetic basis of early T-cell precursor acute lymphoblastic leukaemia (2012, result): “Comparison of the gene expression profile of ETP ALL with those of purified norma”
ISMARA: automated modeling of genomic signals as a democracy of regulatory motifs (2014, background): “SREBF1 expression increases with age in rat brains (Okamoto et al. 2006), SREBF1-mediated lipogenesis is involved in senescence (Kim et al. 2010), SREBF2 regulates autophagy (Seo et al. 2011), and SREBF activity is regulated by mTOR complex 1 (Peterson et al. 2011).”
Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin (2020, background): “Regulation of chromatin structure and gene expression underlies key developmental transitions in cell lineages (Novershtern et al., 2011; Shema et al., 2019; Spitz and Furlong, 2012).”
Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity (2018, background): “…TFs promoting myelopoiesis (Cebpe, Id1, and Id2) were upregulated in LT-HSCs from b-glucan-treated mice, while lymphopoiesis-related TFs (Pax5, Ebf1, Irf4, Spib, and Lef1) were downregulated (Nimmo et al., 2015; Novershtern et al., 2011; Paul et al., 2015; Rosenbauer and Tenen, 2007) (Figure 5D).”
The dendritic cell lineage: ontogeny and function of dendritic cells and their subsets in the steady state and the inflamed setting. (2013, background): “Although few genes are uniquely expressed by cDCs in the context of all hematopoietic cells (24), a group of transcripts discriminates cDCs from macrophages and includes Flt3 (25, 26), c-kit (the receptor for stem cell factor), the chemokine receptor CCR7 (27), and the zinc finger transcription fact”
xCell: digitally portraying the tissue cellular heterogeneity landscape (2017, methodology): “Raw Affymetrix microarray CEL files were downloaded from the Gene Expression Omnibus (GEO), accessions GSE22886 (IRIS) [35], GSE24759 (Novershtern) [36], and GSE49910 (HPCA) [37], and analyzed using the Robust Multi-array Average (RMA) procedure on probe-level data using Matlab functions.”
Personalized Immunomonitoring Uncovers Molecular Networks That Stratify Lupus Patients (2016, positive): “To assess their specific enrichment in sorted hematopoietic cell populations, we applied our modular analysis to two public datasets (Figures S1A and S1B) (Noversh- tern et al., 2011; Streicher et al., 2014).”