CHD7 and Runx1 interaction provides a braking mechanism for hematopoietic differentiation.

Hematopoietic stem and progenitor cell (HSPC) formation and lineage differentiation involve gene expression programs orchestrated by transcription factors and epigenetic regulators. Genetic disruption of the chromatin remodeler chromodomain-helicase-DNA-binding protein 7 (CHD7) expanded phenotypic HSPCs, erythroid, and myeloid lineages in zebrafish and mouse embryos. CHD7 acts to suppress hematopoietic differentiation. Binding motifs for RUNX and other hematopoietic transcription factors are enriched at sites occupied by CHD7, and decreased RUNX1 occupancy correlated with loss of CHD7 localization. CHD7 physically interacts with RUNX1 and suppresses RUNX1-induced expansion of HSPCs during development through modulation of RUNX1 activity. Consequently, the RUNX1:CHD7 axis provides proper timing and function of HSPCs as they emerge during hematopoietic development or mature in adults, representing a distinct and evolutionarily conserved control mechanism to ensure accurate hematopoietic lineage differentiation.

BNC1 regulates cell heterogeneity in human pluripotent stem cell-derived epicardium.

The murine developing epicardium heterogeneously expresses the transcription factors TCF21 and WT1. Here, we show that this cell heterogeneity is conserved in human epicardium, regulated by BNC1 and associated with cell fate and function. Single cell RNA sequencing of epicardium derived from human pluripotent stem cells (hPSC-epi) revealed that distinct epicardial subpopulations are defined by high levels of expression for the transcription factors BNC1 or TCF21. WT1+ cells are included in the BNC1+ population, which was confirmed in human foetal hearts. THY1 emerged as a membrane marker of the TCF21 population. We show that THY1+ cells can differentiate into cardiac fibroblasts (CFs) and smooth muscle cells (SMCs), whereas THY1- cells were predominantly restricted to SMCs. Knocking down BNC1 during the establishment of the epicardial populations resulted in a homogeneous, predominantly TCF21high population. Network inference methods using transcriptomic data from the different cell lineages derived from the hPSC-epi delivered a core transcriptional network organised around WT1, TCF21 and BNC1. This study unveils a list of epicardial regulators and is a step towards engineering subpopulations of epicardial cells with selective biological activities.

Resolving early mesoderm diversification through single-cell expression profiling.

In mammals, specification of the three major germ layers occurs during gastrulation, when cells ingressing through the primitive streak differentiate into the precursor cells of major organ systems. However, the molecular mechanisms underlying this process remain unclear, as numbers of gastrulating cells are very limited. In the mouse embryo at embryonic day 6.5, cells located at the junction between the extra-embryonic region and the epiblast on the posterior side of the embryo undergo an epithelial-to-mesenchymal transition and ingress through the primitive streak. Subsequently, cells migrate, either surrounding the prospective ectoderm contributing to the embryo proper, or into the extra-embryonic region to form the yolk sac, umbilical cord and placenta. Fate mapping has shown that mature tissues such as blood and heart originate from specific regions of the pre-gastrula epiblast, but the plasticity of cells within the embryo and the function of key cell-type-specific transcription factors remain unclear. Here we analyse 1,205 cells from the epiblast and nascent Flk1(+) mesoderm of gastrulating mouse embryos using single-cell RNA sequencing, representing the first transcriptome-wide in vivo view of early mesoderm formation during mammalian gastrulation. Additionally, using knockout mice, we study the function of Tal1, a key haematopoietic transcription factor, and demonstrate, contrary to previous studies performed using retrospective assays, that Tal1 knockout does not immediately bias precursor cells towards a cardiac fate.

Key regulators control distinct transcriptional programmes in blood progenitor and mast cells.

Despite major advances in the generation of genome-wide binding maps, the mechanisms by which transcription factors (TFs) regulate cell type identity have remained largely obscure. Through comparative analysis of 10 key haematopoietic TFs in both mast cells and blood progenitors, we demonstrate that the largely cell type-specific binding profiles are not opportunistic, but instead contribute to cell type-specific transcriptional control, because (i) mathematical modelling of differential binding of shared TFs can explain differential gene expression, (ii) consensus binding sites are important for cell type-specific binding and (iii) knock-down of blood stem cell regulators in mast cells reveals mast cell-specific genes as direct targets. Finally, we show that the known mast cell regulators Mitf and c-fos likely contribute to the global reorganisation of TF binding profiles. Taken together therefore, our study elucidates how key regulatory TFs contribute to transcriptional programmes in several distinct mammalian cell types.

Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model.

Comprehensive study of transcriptional control processes will be required to enhance our understanding of both normal and malignant hematopoiesis. Modern sequencing technologies have revolutionized our ability to generate genome-scale expression and histone modification profiles, transcription factor (TF)-binding maps, and also comprehensive chromatin-looping information. Many of these technologies, however, require large numbers of cells, and therefore cannot be applied to rare hematopoietic stem/progenitor cell (HSPC) populations. The stem cell factor-dependent multipotent progenitor cell line HPC-7 represents a well-recognized cell line model for HSPCs. Here we report genome-wide maps for 17 TFs, 3 histone modifications, DNase I hypersensitive sites, and high-resolution promoter-enhancer interactomes in HPC-7 cells. Integrated analysis of these complementary data sets revealed TF occupancy patterns of genomic regions involved in promoter-anchored loops. Moreover, preferential associations between pairs of TFs bound at either ends of chromatin loops led to the identification of 4 previously unrecognized protein-protein interactions between key blood stem cell regulators. All HPC-7 data sets are freely available both through standard repositories and a user-friendly Web interface. Together with previously generated genome-wide data sets, this study integrates HPC-7 data into a genomic resource on par with ENCODE tier 1 cell lines and, importantly, is the only current model with comprehensive genome-scale data that is relevant to HSPC biology.

Single-cell analyses of regulatory network perturbations using enhancer-targeting TALEs suggest novel roles for PU.1 during haematopoietic specification.

Transcription factors (TFs) act within wider regulatory networks to control cell identity and fate. Numerous TFs, including Scl (Tal1) and PU.1 (Spi1), are known regulators of developmental and adult haematopoiesis, but how they act within wider TF networks is still poorly understood. Transcription activator-like effectors (TALEs) are a novel class of genetic tool based on the modular DNA-binding domains of Xanthomonas TAL proteins, which enable DNA sequence-specific targeting and the manipulation of endogenous gene expression. Here, we report TALEs engineered to target the PU.1-14kb and Scl+40kb transcriptional enhancers as efficient new tools to perturb the expression of these key haematopoietic TFs. We confirmed the efficiency of these TALEs at the single-cell level using high-throughput RT-qPCR, which also allowed us to assess the consequences of both PU.1 activation and repression on wider TF networks during developmental haematopoiesis. Combined with comprehensive cellular assays, these experiments uncovered novel roles for PU.1 during early haematopoietic specification. Finally, transgenic mouse studies confirmed that the PU.1-14kb element is active at sites of definitive haematopoiesis in vivo and PU.1 is detectable in haemogenic endothelium and early committing blood cells. We therefore establish TALEs as powerful new tools to study the functionality of transcriptional networks that control developmental processes such as early haematopoiesis.

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data.

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics.

Processing, visualising and reconstructing network models from single-cell data.

New single-cell technologies readily permit gene expression profiling of thousands of cells at single-cell resolution. In this review, we will discuss methods for visualisation and interpretation of single-cell gene expression data, and the computational analysis needed to go from raw data to predictive executable models of gene regulatory network function. We will focus primarily on single-cell real-time quantitative PCR and RNA-sequencing data, but much of what we cover will also be relevant to other platforms, such as the mass cytometry technology for high-dimensional single-cell proteomics.

Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling.

Transcriptional networks regulate cell fate decisions, which occur at the level of individual cells. However, much of what we know about their structure and function comes from studies averaging measurements over large populations of cells, many of which are functionally heterogeneous. Such studies conceal the variability between cells and so prevent us from determining the nature of heterogeneity at the molecular level. In recent years, many protocols and platforms have been developed that allow the high throughput analysis of gene expression in single cells, opening the door to a new era of biology. Here, we discuss the need for single cell gene expression analysis to gain deeper insights into the transcriptional control of cell fate decisions, and consider the insights it has provided so far into transcriptional regulatory networks in development.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data.

MOTIVATION: High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. RESULTS: We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. AVAILABILITY AND IMPLEMENTATION: The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm.

Transcriptional hierarchies regulating early blood cell development.

Hematopoiesis represents one of the paradigmatic systems for studying stem cell biology, but our understanding of how the hematopoietic system develops during embryogenesis is still incomplete. While many lessons have been learned from studying the mouse embryo, embryonic stem cells have come to the fore as an alternative and more tractable model to recapitulate hematopoietic development. Here we review what is known about the embryonic origin of blood from these complementary systems and how transcription factor networks regulate the emergence of hematopoietic tissue from the mesoderm. Furthermore, we have performed an integrated analysis of genome-wide microarray and ChIP-seq data sets from mouse embryos and embryonic stem (ES) cell lines deficient in key regulators and demonstrate how this type of analysis can be used to reconstruct regulatory hierarchies that both confirm existing regulatory linkages and suggest additional interactions.

Cyclin E is recruited to the nuclear matrix during differentiation, but is not recruited in cancer cells.

Cyclin E supports pre-replication complex (pre-RC) assembly, while cyclin A-associated kinase activates DNA synthesis. We show that cyclin E, but not A, is mounted upon the nuclear matrix in sub-nuclear foci in differentiated vertebrate cells, but not in undifferentiated cells or cancer cells. In murine embryonic stem cells, Xenopus embryos and human urothelial cells, cyclin E is recruited to the nuclear matrix as cells differentiate and this can be manipulated in vitro. This suggests that pre-RC assembly becomes spatially restricted as template usage is defined. Furthermore, failure to become restricted may contribute to the plasticity of cancer cells.

Defining the earliest step of cardiovascular lineage segregation by single-cell RNA-seq.

Mouse heart development arises from Mesp1-expressing cardiovascular progenitors (CPs) that are specified during gastrulation. The molecular processes that control early regional and lineage segregation of CPs have been unclear. We performed single-cell RNA sequencing of wild-type and Mesp1-null CPs in mice. We showed that populations of Mesp1 CPs are molecularly distinct and span the continuum between epiblast and later mesodermal cells, including hematopoietic progenitors. Single-cell transcriptome analysis of Mesp1-deficient CPs showed that Mesp1 is required for the exit from the pluripotent state and the induction of the cardiovascular gene expression program. We identified distinct populations of Mesp1 CPs that correspond to progenitors committed to different cell lineages and regions of the heart, identifying the molecular features associated with early lineage restriction and regional segregation of the heart at the early stage of mouse gastrulation.

Dissecting stem cell differentiation using single cell expression profiling.

Many assumptions about the way cells behave are based on analyses of populations. However, it is now widely recognized that even apparently pure populations can display a remarkable level of heterogeneity. This is particularly true in stem cell biology where it hinders our understanding of normal development and the development of strategies for regenerative medicine. Over the past decade technologies facilitating gene expression analysis at the single cell level have become widespread, providing access to rare cell populations and insights into population structure and function. Here we review the contributions of single cell biology to understanding stem cell differentiation so far, both as a new methodology for defining cell types and a tool for understanding the complexities of cellular decision-making.

GFI1 proteins orchestrate the emergence of haematopoietic stem cells through recruitment of LSD1.

In vertebrates, the first haematopoietic stem cells (HSCs) with multi-lineage and long-term repopulating potential arise in the AGM (aorta-gonad-mesonephros) region. These HSCs are generated from a rare and transient subset of endothelial cells, called haemogenic endothelium (HE), through an endothelial-to-haematopoietic transition (EHT). Here, we establish the absolute requirement of the transcriptional repressors GFI1 and GFI1B (growth factor independence 1 and 1B) in this unique trans-differentiation process. We first demonstrate that Gfi1 expression specifically defines the rare population of HE that generates emerging HSCs. We further establish that in the absence of GFI1 proteins, HSCs and haematopoietic progenitor cells are not produced in the AGM, revealing the critical requirement for GFI1 proteins in intra-embryonic EHT. Finally, we demonstrate that GFI1 proteins recruit the chromatin-modifying protein LSD1, a member of the CoREST repressive complex, to epigenetically silence the endothelial program in HE and allow the emergence of blood cells.

An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability.

Transcription factor (TF) networks determine cell-type identity by establishing and maintaining lineage-specific expression profiles, yet reconstruction of mammalian regulatory network models has been hampered by a lack of comprehensive functional validation of regulatory interactions. Here, we report comprehensive ChIP-Seq, transgenic and reporter gene experimental data that have allowed us to construct an experimentally validated regulatory network model for haematopoietic stem/progenitor cells (HSPCs). Model simulation coupled with subsequent experimental validation using single cell expression profiling revealed potential mechanisms for cell state stabilisation, and also how a leukaemogenic TF fusion protein perturbs key HSPC regulators. The approach presented here should help to improve our understanding of both normal physiological and disease processes.

Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.

Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis.

T helper 2 (Th2) cells regulate helminth infections, allergic disorders, tumor immunity, and pregnancy by secreting various cytokines. It is likely that there are undiscovered Th2 signaling molecules. Although steroids are known to be immunoregulators, de novo steroid production from immune cells has not been previously characterized. Here, we demonstrate production of the steroid pregnenolone by Th2 cells in vitro and in vivo in a helminth infection model. Single-cell RNA sequencing and quantitative PCR analysis suggest that pregnenolone synthesis in Th2 cells is related to immunosuppression. In support of this, we show that pregnenolone inhibits Th cell proliferation and B cell immunoglobulin class switching. We also show that steroidogenic Th2 cells inhibit Th cell proliferation in a Cyp11a1 enzyme-dependent manner. We propose pregnenolone as a "lymphosteroid," a steroid produced by lymphocytes. We speculate that this de novo steroid production may be an intrinsic phenomenon of Th2-mediated immune responses to actively restore immune homeostasis.

Generation of multipotent foregut stem cells from human pluripotent stem cells.

Human pluripotent stem cells (hPSCs) could provide an infinite source of clinically relevant cells with potential applications in regenerative medicine. However, hPSC lines vary in their capacity to generate specialized cells, and the development of universal protocols for the production of tissue-specific cells remains a major challenge. Here, we have addressed this limitation for the endodermal lineage by developing a defined culture system to expand and differentiate human foregut stem cells (hFSCs) derived from hPSCs. hFSCs can self-renew while maintaining their capacity to differentiate into pancreatic and hepatic cells. Furthermore, near-homogenous populations of hFSCs can be obtained from hPSC lines which are normally refractory to endodermal differentiation. Therefore, hFSCs provide a unique approach to bypass variability between pluripotent lines in order to obtain a sustainable source of multipotent endoderm stem cells for basic studies and to produce a diversity of endodermal derivatives with a clinical value.

Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis.

Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease.