Densely Interconnected Transcriptional Circuits Control Cell States in Human Hematopoiesis

Abstract

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.

Far Upstream Element Binding Protein Plays a Crucial Role in Embryonic Development, Hematopoiesis, and Stabilizing Myc Expression Levels

“…Deficits were noted in erythroid, granulocyte-macrophage, and lymphoid lineages from FBP KO livers. Of note, on the basis of mRNA expression profiles and on the disposition of cis elements for known transcription factors, FBP had been predicted by Ebert and colleagues 46 to regulate hematopoiesis, especially erythropoiesis and granulocytopoiesis, and was placed just below PBX1 and SOX4 in the hierarchy of hematopoietic master regulators; however direct evidence to confirm a hematopoietic role for FBP was lacking. A recent study also reported the involvement of FBP in embryonic and adult HSC function.…”

“…52 A transcriptional map of human hematopoietic cells suggests that FBP is an important regulator of an expression module up-regulated in HSCs and primitive erythroid cells. 46 Therefore, conditional deletion of FBP in lymphoid progenitors (with the use of RAG1-Cre, Lck-Cre, or CD4-Cre) may be expected to be less deleterious than deletion of FBP in HSC (through a Vav-Cre) or erythroid progenitors (GATA1-Cre).…”

Pluripotent stem cells reveal erythroid-specific activities of the GATA1 N-terminus

“…273 genes were differentially expressed between T21/GATA1s and T21/WT GATA1, with a fold change of mean expression of less than 2 (217 genes, blue) or 2-fold or greater (56 genes, green). (B) GSEA on 273 differentially expressed genes using erythroid, megakaryocytic, and myeloid expression profiles from Novershtern et al (30). Top: enrichment of 154 genes that were upregulated in T21/GATA1s as compared with T21/WT GATA1 progenitors in myeloid versus erythroid signature genes and in megakaryocytic versus erythroid genes.…”

“…NES, normalized enrichment score; P values shown are from modified KolmogorovSmirnov test as implemented in GSEA. (C) Heat maps showing expression levels of 2-fold or greater upregulated (top) and downregulated (bottom) genes in T21/GATA1s versus T21/WT GATA1 progenitors (left) as well as in lineage-committed cells (right) based on expression levels in erythroid (n = 7 replicates of CD34 -CD71 lo GlyA + , 6 of CD34 -CD71 -GlyA + cells), myeloid (n = 6 replicates of basophils, 5 of eosinophils, 4 of neutrophils), and megakaryocytic (n = 5 replicates of CFU-megakaryocytes, CD34 + CD41 + CD61 + CD45 -, 7 of mature megakaryocytes, CD34 -CD41 + CD61 + CD45 -) cells from Novershtern et al (30). Color scheme is row normalized from blue to red corresponding to minimum to maximum expression values in a given row, respectively.…”

Cell division curtails helper phenotype plasticity and expedites helper T‐cell differentiation

“…[4][5][6][7] The availability of quantitative data and the apparent complexity of cellular regulatory networks have led to a data-driven mathematical modelling approach that is usually referred to as computational or systems biology. Mathematical models have revealed nonlinearity in genetic networks that allow cells to switch between states.…”