A single-cell hematopoietic landscape resolves 8 lineage trajectories and defects in Kit mutant mice

Novel biomarkers of intervertebral disc cells and evidence of stem cells in the intervertebral disc

OBJECTIVE

Rat intervertebral disc (IVD) is one of the most commonly used and cost-effective alternative models for human IVD. Many IVD related clinical studies need to be pre-tested on rat IVDs. However, studies on the heterogeneous cell clusters of the rat IVD are inadequate, and a further understanding of the marker genes and cell phenotypes of healthy mature IVD cells is essential.

METHODS

In this study, we used the 10X Genomics technology to analyze the single-cell transcriptome of purified wild-type rat IVDs.

RESULTS

We identified potentially new gene markers of IVDs via single-cell sequencing. Based on the unsupervised cluster analysis of 13,578 single-cell transcripts, 3 known IVD cell types were identified. We provided a complete single-cell gene expression map of the IVD. Immunohistochemical and immunofluorescence images of rat disc sections confirmed the new marker genes of all cell types. One group of heterologous cell groups expressed multi-functional stem cell (MSC)-specific genes, indicating the stem cell potential of IVD cells.

CONCLUSION

We provided the phenotype and marker genes of IVD cells at the single-cell level, reconfirmed existing data, and proposed new marker genes, including MSC marker genes. By identifying more accurate target cells and genes, our results pave the way for further study of the response of individual disc cells to disease states and provide the basis for future disc regeneration therapies.

JMJD6 promotes self-renewal and regenerative capacity of hematopoietic stem cells

Lifelong multilineage hematopoiesis critically depends on rare hematopoietic stem cells (HSCs) that reside in the hypoxic bone marrow microenvironment. Although the role of the canonical oxygen sensor hypoxia-inducible factor prolyl hydroxylase has been investigated extensively in hematopoiesis, the functional significance of other members of the 2-oxoglutarate (2-OG)-dependent protein hydroxylase family of enzymes remains poorly defined in HSC biology and multilineage hematopoiesis. Here, by using hematopoietic-specific conditional gene deletion, we reveal that the 2-OG-dependent protein hydroxylase JMJD6 is essential for short- and long-term maintenance of the HSC pool and multilineage hematopoiesis. Additionally, upon hematopoietic injury, Jmjd6-deficient HSCs display a striking failure to expand and regenerate the hematopoietic system. Moreover, HSCs lacking Jmjd6 lose multilineage reconstitution potential and self-renewal capacity upon serial transplantation. At the molecular level, we found that JMJD6 functions to repress multiple processes whose downregulation is essential for HSC integrity, including mitochondrial oxidative phosphorylation (OXPHOS), protein synthesis, p53 stabilization, cell cycle checkpoint progression, and mTORC1 signaling. Indeed, Jmjd6-deficient primitive hematopoietic cells display elevated basal and maximal mitochondrial respiration rates and increased reactive oxygen species (ROS), prerequisites for HSC failure. Notably, an antioxidant, N-acetyl-l-cysteine, rescued HSC and lymphoid progenitor cell depletion, indicating a causal impact of OXPHOS-mediated ROS generation upon Jmjd6 deletion. Thus, JMJD6 promotes HSC maintenance and multilineage differentiation potential by suppressing fundamental pathways whose activation is detrimental for HSC function.

E-cadherin is regulated by GATA-2 and marks the early commitment of mouse hematopoietic progenitors to the basophil and mast cell fates

E-cadherin is a calcium-dependent cell-cell adhesion molecule extensively studied for its involvement in tissue formation, epithelial cell behavior, and suppression of cancer. However, E-cadherin expression in the hematopoietic system has not been fully elucidated. Combining single-cell RNA-sequencing analyses and immunophenotyping, we revealed that progenitors expressing high levels of E-cadherin and contained within the granulocyte-monocyte progenitors (GMPs) fraction have an enriched capacity to differentiate into basophils and mast cells. We detected E-cadherin expression on committed progenitors before the expression of other reported markers of these lineages. We named such progenitors pro-BMPs (pro-basophil and mast cell progenitors). Using RNA sequencing, we observed transcriptional priming of pro-BMPs to the basophil and mast cell lineages. We also showed that GATA-2 directly regulates E-cadherin expression in the basophil and mast cell lineages, thus providing a mechanistic connection between the expression of this cell surface marker and the basophil and mast cell fate specification.

Cutting down the hematopoietic tree: E-cadherin reveals a landscape of differentiating basophils and mast cells

GATA-2-mediated E-cadherin expression marks early progenitors primed to the basophil and mast cell lineages in mouse hematopoiesis (see the related Research Article by Wanet et al.).

Single-cell fate decisions of bipotential hematopoietic progenitors

PURPOSE OF REVIEW

In hematopoiesis, rapid cell fate decisions are necessary for timely responses to environmental stimuli resulting in the production of diverse types of blood cells. Early studies have led to a hierarchical, tree-like view of hematopoiesis with hematopoietic stem cells residing at the apex and serially branching out to give rise to bipotential progenitors with increasingly restricted lineage potential. Recent single-cell studies have challenged some aspects of the classical model of hematopoiesis. Here, we review the latest articles on cell fate decision in hematopoietic progenitors, highlighting single-cell studies that have questioned previously established concepts and those that have reaffirmed them.

RECENT FINDINGS

The hierarchical organization of hematopoiesis and the importance of transcription factors have been largely validated at the single-cell level. In contrast, single-cell studies have shown that lineage commitment is progressive rather than switch-like as originally proposed. Furthermore, the reconstruction of cell fate paths suggested the existence of a gradient of hematopoietic progenitors that are in a continuum of changing fate probabilities rather than in a static bipotential state, leading us to reconsider the notion of bipotential progenitors.

SUMMARY

Single-cell transcriptomic and proteomic studies have transformed our view of lineage commitment and offer a drastically different perspective on hematopoiesis.

Decoding myofibroblast origins in human kidney fibrosis

Kidney fibrosis is the hallmark of chronic kidney disease progression; however, at present no antifibrotic therapies exist^1-3. The origin, functional heterogeneity and regulation of scar-forming cells that occur during human kidney fibrosis remain poorly understood^1,2,4. Here, using single-cell RNA sequencing, we profiled the transcriptomes of cells from the proximal and non-proximal tubules of healthy and fibrotic human kidneys to map the entire human kidney. This analysis enabled us to map all matrix-producing cells at high resolution, and to identify distinct subpopulations of pericytes and fibroblasts as the main cellular sources of scar-forming myofibroblasts during human kidney fibrosis. We used genetic fate-tracing, time-course single-cell RNA sequencing and ATAC-seq (assay for transposase-accessible chromatin using sequencing) experiments in mice, and spatial transcriptomics in human kidney fibrosis, to shed light on the cellular origins and differentiation of human kidney myofibroblasts and their precursors at high resolution. Finally, we used this strategy to detect potential therapeutic targets, and identified NKD2 as a myofibroblast-specific target in human kidney fibrosis.

Single-Cell Analysis of Hematopoietic Stem Cells

The study of hematopoiesis has been revolutionized in recent years by the application of single-cell RNA sequencing technologies. The technique coupled with rapidly developing bioinformatic analysis has provided great insight into the cell type compositions of many populations previously defined by their cell surface phenotype. Moreover, transcriptomic information enables the identification of individual molecules and pathways which define novel cell populations and their transitions including cell lineage decisions. Combining single-cell transcriptional profiling with molecular perturbations allows functional analysis of individual factors in gene regulatory networks and better understanding of the earliest stages of malignant transformation. In this chapter we describe a comprehensive protocol for scRNA-Seq analysis of the mouse bone marrow, using both plate-based (low throughput) and droplet-based (high throughput) methods. The protocol includes instructions for sample preparation, an antibody panel for flow cytometric purification of hematopoietic progenitors with index sorting for plate-based analysis or in bulk for droplet-based methods. The plate-based protocol described in this chapter is a combination of the Smart-Seq2 and mcSCRB-Seq protocols, optimized in our laboratory. It utilizes off-the-shelf reagents for cDNA preparation, is amenable to automation using a liquid handler, and takes 4 days from preparation of the cells for sorting to producing a sequencing-ready library. The droplet-based method (using for instance the 10× Genomics platform) relies on the manufacturer's user guide and commercial reagents, and takes 3 days from isolation of the cells to the production of a library ready for sequencing.

Two Aldehyde Clearance Systems Are Essential to Prevent Lethal Formaldehyde Accumulation in Mice and Humans

Reactive aldehydes arise as by-products of metabolism and are normally cleared by multiple families of enzymes. We find that mice lacking two aldehyde detoxifying enzymes, mitochondrial ALDH2 and cytoplasmic ADH5, have greatly shortened lifespans and develop leukemia. Hematopoiesis is disrupted profoundly, with a reduction of hematopoietic stem cells and common lymphoid progenitors causing a severely depleted acquired immune system. We show that formaldehyde is a common substrate of ALDH2 and ADH5 and establish methods to quantify elevated blood formaldehyde and formaldehyde-DNA adducts in tissues. Bone-marrow-derived progenitors actively engage DNA repair but also imprint a formaldehyde-driven mutation signature similar to aging-associated human cancer mutation signatures. Furthermore, we identify analogous genetic defects in children causing a previously uncharacterized inherited bone marrow failure and pre-leukemic syndrome. Endogenous formaldehyde clearance alone is therefore critical for hematopoiesis and in limiting mutagenesis in somatic tissues.

Interactions between lineage-associated transcription factors govern haematopoietic progenitor states

Recent advances in molecular profiling provide descriptive datasets of complex differentiation landscapes including the haematopoietic system, but the molecular mechanisms defining progenitor states and lineage choice remain ill-defined. Here, we employed a cellular model of murine multipotent haematopoietic progenitors (Hoxb8-FL) to knock out 39 transcription factors (TFs) followed by RNA-Seq analysis, to functionally define a regulatory network of 16,992 regulator/target gene links. Focussed analysis of the subnetworks regulated by the B-lymphoid TF Ebf1 and T-lymphoid TF Gata3 revealed a surprising role in common activation of an early myeloid programme. Moreover, Gata3-mediated repression of Pax5 emerges as a mechanism to prevent precocious B-lymphoid differentiation, while Hox-mediated activation of Meis1 suppresses myeloid differentiation. To aid interpretation of large transcriptomics datasets, we also report a new method that visualises likely transitions that a progenitor will undergo following regulatory network perturbations. Taken together, this study reveals how molecular network wiring helps to establish a multipotent progenitor state, with experimental approaches and analysis tools applicable to dissecting a broad range of both normal and perturbed cellular differentiation landscapes.

Interactions between lineage-associated transcription factors govern haematopoietic progenitor states

Recent advances in molecular profiling provide descriptive datasets of complex differentiation landscapes including the haematopoietic system, but the molecular mechanisms defining progenitor states and lineage choice remain ill-defined. Here, we employed a cellular model of murine multipotent haematopoietic progenitors (Hoxb8-FL) to knock out 39 transcription factors (TFs) followed by RNA-Seq analysis, to functionally define a regulatory network of 16,992 regulator/target gene links. Focussed analysis of the subnetworks regulated by the B-lymphoid TF Ebf1 and T-lymphoid TF Gata3 revealed a surprising role in common activation of an early myeloid programme. Moreover, Gata3-mediated repression of Pax5 emerges as a mechanism to prevent precocious B-lymphoid differentiation, while Hox-mediated activation of Meis1 suppresses myeloid differentiation. To aid interpretation of large transcriptomics datasets, we also report a new method that visualises likely transitions that a progenitor will undergo following regulatory network perturbations. Taken together, this study reveals how molecular network wiring helps to establish a multipotent progenitor state, with experimental approaches and analysis tools applicable to dissecting a broad range of both normal and perturbed cellular differentiation landscapes.

The stem/progenitor landscape is reshaped in a mouse model of essential thrombocythemia and causes excess megakaryocyte production

Frameshift mutations in CALR (calreticulin) are associated with essential thrombocythemia (ET), but the stages at and mechanisms by which mutant CALR drives transformation remain incompletely defined. Here, we use single-cell approaches to examine the hematopoietic stem/progenitor cell landscape in a mouse model of mutant CALR-driven ET. We identify a trajectory linking hematopoietic stem cells (HSCs) with megakaryocytes and prospectively identify a previously unknown intermediate population that is overrepresented in the disease state. We also show that mutant CALR drives transformation primarily from the earliest stem cell compartment, with some contribution from megakaryocyte progenitors. Last, relative to wild-type HSCs, mutant CALR HSCs show increases in JAK-STAT signaling, the unfolded protein response, cell cycle, and a previously undescribed up-regulation of cholesterol biosynthesis. Overall, we have identified a novel megakaryocyte-biased cell population that is increased in a mouse model of ET and described transcriptomic changes linking CALR mutations to increased HSC proliferation and megakaryopoiesis.

How Relevant Are Bone Marrow-Derived Mast Cells (BMMCs) as Models for Tissue Mast Cells? A Comparative Transcriptome Analysis of BMMCs and Peritoneal Mast Cells

Bone marrow-derived mast cells (BMMCs) are often used as a model system for studies of the role of MCs in health and disease. These cells are relatively easy to obtain from total bone marrow cells by culturing under the influence of IL-3 or stem cell factor (SCF). After 3 to 4 weeks in culture, a nearly homogenous cell population of toluidine blue-positive cells are often obtained. However, the question is how relevant equivalents these cells are to normal tissue MCs. By comparing the total transcriptome of purified peritoneal MCs with BMMCs, here we obtained a comparative view of these cells. We found several important transcripts that were expressed at very high levels in peritoneal MCs, but were almost totally absent from the BMMCs, including the major chymotryptic granule protease Mcpt4, the neurotrophin receptor Gfra2, the substance P receptor Mrgprb2, the metalloprotease Adamts9 and the complement factor 2 (C2). In addition, there were a number of other molecules that were expressed at much higher levels in peritoneal MCs than in BMMCs, including the transcription factors Myb and Meis2, the MilR1 (Allergin), Hdc (Histidine decarboxylase), Tarm1 and the IL-3 receptor alpha chain. We also found many transcripts that were highly expressed in BMMCs but were absent or expressed at low levels in the peritoneal MCs. However, there were also numerous MC-related transcripts that were expressed at similar levels in the two populations of cells, but almost absent in peritoneal macrophages and B cells. These results reveal that the transcriptome of BMMCs shows many similarities, but also many differences to that of tissue MCs. BMMCs can thereby serve as suitable models in many settings concerning the biology of MCs, but our findings also emphasize that great care should be taken when extrapolating findings from BMMCs to the in vivo function of tissue-resident MCs.

Single-cell lineage tracing unveils a role for TCF15 in haematopoiesis

Bone marrow transplantation therapy relies on the life-long regenerative capacity of haematopoietic stem cells (HSCs)^1,2. HSCs present a complex variety of regenerative behaviours at the clonal level, but the mechanisms underlying this diversity are still undetermined^3–11. Recent advances in single cell RNA sequencing (scRNAseq) have revealed transcriptional differences amongst HSCs, providing a possible explanation for their functional heterogeneity^12–17. However, the destructive nature of sequencing assays prevents simultaneous observation of stem cell state and function. To solve this challenge, we implemented expressible lentiviral barcoding, which enabled simultaneous analysis of lineages and transcriptomes from single adult HSCs and their clonal trajectories during long-term bone marrow reconstitution. Differential gene expression analysis between clones with distinct behaviour unveiled an intrinsic molecular signature that characterizes functional long-term repopulating HSCs. Probing this signature through in vivo CRISPR screening, we found the transcription factor Tcf15 to be required, and sufficient, to drive HSC quiescence and long-term self-renewal. In situ, Tcf15 expression labels the most primitive subset of true multipotent HSCs. In conclusion, our work elucidates clone-intrinsic molecular programs associated with functional stem cell heterogeneity, and identifies a mechanism for the maintenance of the self-renewing haematopoietic stem cell state.

Emerging single-cell tools are primed to reveal functional and molecular heterogeneity in malignant hematopoietic stem cells

PURPOSE OF REVIEW

The recent emergence of single-cell technologies has permitted unprecedented insight into the molecular drivers of fate choice in blood stem and progenitor cells. This review gives a broad overview of current efforts to understand the molecular regulators of malignant hematopoietic stem cells (HSCs) at the single-cell level.

RECENT FINDINGS

The large-scale adoption of single-cell approaches has allowed extensive description of the transcriptional profiles and functional properties of single HSCs. These techniques are now beginning to be applied to malignant HSCs isolated directly from patients or from mouse models of malignancy. However, these studies have generally struggled to pinpoint the functional regulators of malignant characteristics, since malignant HSCs often differ in more than one property when compared with normal HSCs. Moreover, both normal and malignant populations are complicated by HSC heterogeneity.

SUMMARY

Despite the existence of single-cell gene expression profiling tools, relatively few publications have emerged. Here, we review these studies from recent years with a specific focus on those undertaking single-cell measurements in malignant stem and progenitor cells. We anticipate this to be the tip of the iceberg, expecting the next 2-3 years to produce datasets that will facilitate a much broader understanding of malignant HSCs.

Selective LXR agonist DMHCA corrects retinal and bone marrow dysfunction in type 2 diabetes

In diabetic dyslipidemia, cholesterol accumulates in the plasma membrane, decreasing fluidity and thereby suppressing the ability of cells to transduce ligand-activated signaling pathways. Liver X receptors (LXRs) make up the main cellular mechanism by which intracellular cholesterol is regulated and play important roles in inflammation and disease pathogenesis. N, N-dimethyl-3β-hydroxy-cholenamide (DMHCA), a selective LXR agonist, specifically activates the cholesterol efflux arm of the LXR pathway without stimulating triglyceride synthesis. In this study, we use a multisystem approach to understand the effects and molecular mechanisms of DMHCA treatment in type 2 diabetic (db/db) mice and human circulating angiogenic cells (CACs), which are hematopoietic progenitor cells with vascular reparative capacity. We found that DMHCA is sufficient to correct retinal and BM dysfunction in diabetes, thereby restoring retinal structure, function, and cholesterol homeostasis; rejuvenating membrane fluidity in CACs; hampering systemic inflammation; and correcting BM pathology. Using single-cell RNA sequencing on lineage-sca1+c-Kit+ (LSK) hematopoietic stem cells (HSCs) from untreated and DMHCA-treated diabetic mice, we provide potentially novel insights into hematopoiesis and reveal DMHCA's mechanism of action in correcting diabetic HSCs by reducing myeloidosis and increasing CACs and erythrocyte progenitors. Taken together, these findings demonstrate the beneficial effects of DMHCA treatment on diabetes-induced retinal and BM pathology.

A Novel GATA2 Protein Reporter Mouse Reveals Hematopoietic Progenitor Cell Types

The transcription factor (TF) GATA2 plays a key role in organ development and cell fate control in the central nervous, urogenital, respiratory, and reproductive systems, and in primitive and definitive hematopoiesis. Here, we generate a knockin protein reporter mouse line expressing a GATA2VENUS fusion from the endogenous Gata2 genomic locus, with correct expression and localization of GATA2VENUS in different organs. GATA2VENUS expression is heterogeneous in different hematopoietic stem and progenitor cell populations (HSPCs), identifies functionally distinct subsets, and suggests a novel monocyte and mast cell lineage bifurcation point. GATA2 levels further correlate with proliferation and lineage outcome of hematopoietic progenitors. The GATA2VENUS mouse line improves the identification of specific live cell types during embryonic and adult development and will be crucial for analyzing GATA2 protein dynamics in TF networks.

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A novel GATA2VENUS fusion mouse line to report GATA2 protein expression

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VENUS fusion does not alter GATA2 expression or disturb development or homeostasis

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GATA2 expression identifies functionally distinct HSPC subpopulations

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GATA2 expression unveils an earlier monocyte-mast cell lineage bifurcation point

Advancing Stem Cell Research through Multimodal Single-Cell Analysis

Technological advances play a key role in furthering our understanding of stem cell biology, and advancing the prospects of regenerative therapies. Highly parallelized methods, developed in the last decade, can profile DNA, RNA, or proteins in thousands of cells and even capture data across two or more modalities (multiomics). This allows unbiased and precise definition of molecular cell states, thus allowing classification of cell types, tracking of differentiation trajectories, and discovery of underlying mechanisms. Despite being based on destructive techniques, novel experimental and bioinformatic approaches enable embedding and extraction of temporal information, which is essential for deconvolution of complex data and establishing cause and effect relationships. Here, we provide an overview of recent studies pertinent to stem cell biology, followed by an outlook on how further advances in single-cell molecular profiling and computational analysis have the potential to shape the future of both basic and translational research.

The Source and Dynamics of Adult Hematopoiesis: Insights from Lineage Tracing

The generation of all blood cell lineages (hematopoiesis) is sustained throughout the entire life span of adult mammals. Studies using cell transplantation identified the self-renewing, multipotent hematopoietic stem cells (HSCs) as the source of hematopoiesis in adoptive hosts and delineated a hierarchy of HSC-derived progenitors that ultimately yield mature blood cells. However, much less is known about adult hematopoiesis as it occurs in native hosts, i.e., without transplantation. Here we review recent advances in our understanding of native hematopoiesis, focusing in particular on the application of genetic lineage tracing in mice. The emerging evidence has established HSCs as the major source of native hematopoiesis, helped to define the kinetics of HSC differentiation, and begun exploring native hematopoiesis in stress conditions such as aging and inflammation. Major outstanding questions about native hematopoiesis still remain, such as its clonal composition, the nature of lineage commitment, and the dynamics of the process in humans.

m6A Modification Prevents Formation of Endogenous Double-Stranded RNAs and Deleterious Innate Immune Responses during Hematopoietic Development

N6-methyladenosine (m6A) is the most abundant RNA modification, but little is known about its role in mammalian hematopoietic development. Here, we show that conditional deletion of the m6A writer METTL3 in murine fetal liver resulted in hematopoietic failure and perinatal lethality. Loss of METTL3 and m6A activated an aberrant innate immune response, mediated by the formation of endogenous double-stranded RNAs (dsRNAs). The aberrantly formed dsRNAs were long, highly m6A modified in their native state, characterized by low folding energies, and predominantly protein coding. We identified coinciding activation of pattern recognition receptor pathways normally tasked with the detection of foreign dsRNAs. Disruption of the aberrant immune response via abrogation of downstream Mavs or Rnasel signaling partially rescued the observed hematopoietic defects in METTL3-deficient cells in vitro and in vivo. Our results suggest that m6A modification protects against endogenous dsRNA formation and a deleterious innate immune response during mammalian hematopoietic development.

Nascent transcript and single-cell RNA-seq analysis defines the mechanism of action of the LSD1 inhibitor INCB059872 in myeloid leukemia

Drugs targeting chromatin-modifying enzymes have entered clinical trials for myeloid malignancies, including INCB059872, a selective irreversible inhibitor of Lysine-Specific Demethylase 1 (LSD1). While initial studies of LSD1 inhibitors suggested these compounds may be used to induce differentiation of acute myeloid leukemia (AML), the mechanisms underlying this effect and dose-limiting toxicities are not well understood. Here, we used precision nuclear run-on sequencing (PRO-seq) and ChIP-seq in AML cell lines to probe for the earliest regulatory events associated with INCB059872 treatment. The changes in nascent transcription could be traced back to a loss of CoREST activity and activation of GFI1-regulated genes. INCB059872 is in phase I clinical trials, and we evaluated a pre-treatment bone marrow sample of a patient who showed a clinical response to INCB059872 while being treated with azacitidine. We used single-cell RNA-sequencing (scRNA-seq) to show that INCB059872 caused a shift in gene expression that was again associated with GFI1/GFI1B regulation. Finally, we treated mice with INCB059872 and performed scRNA-seq of lineage-negative bone marrow cells, which showed that INCB059872 triggered accumulation of megakaryocyte early progenitor cells with gene expression hallmarks of stem cells. Accumulation of these stem/progenitor cells may contribute to the thrombocytopenia observed in patients treated with LSD1 inhibitors.

Sterile α-motif domain requirement for cellular signaling and survival

Hundreds of sterile α-motif (SAM) domains have predicted structural similarities and are reported to bind proteins, lipids, or RNAs. However, the majority of these domains have not been analyzed functionally. Previously, we demonstrated that a SAM domain-containing protein, SAMD14, promotes SCF/proto-oncogene c-Kit (c-Kit) signaling, erythroid progenitor function, and erythrocyte regeneration. Deletion of a Samd14 enhancer (Samd14-Enh), occupied by GATA2 and SCL/TAL1 transcription factors, reduces SAMD14 expression in bone marrow and spleen and is lethal in a hemolytic anemia mouse model. To rigorously establish whether Samd14-Enh deletion reduces anemia-dependent c-Kit signaling by lowering SAMD14 levels, we developed a genetic rescue assay in murine Samd14-Enh-/- primary erythroid precursor cells. SAMD14 expression at endogenous levels rescued c-Kit signaling. The conserved SAM domain was required for SAMD14 to increase colony-forming activity, c-Kit signaling, and progenitor survival. To elucidate the molecular determinants of SAM domain function in SAMD14, we substituted its SAM domain with distinct SAM domains predicted to be structurally similar. The chimeras were less effective than SAMD14 itself in rescuing signaling, survival, and colony-forming activities. Thus, the SAMD14 SAM domain has attributes that are distinct from other SAM domains and underlie SAMD14 function as a regulator of cellular signaling and erythrocyte regeneration.

Linker histone H1.2 and H1.4 affect the neutrophil lineage determination

Neutrophils are important innate immune cells that tackle invading pathogens with different effector mechanisms. They acquire this antimicrobial potential during their maturation in the bone marrow, where they differentiate from hematopoietic stem cells in a process called granulopoiesis. Mature neutrophils are terminally differentiated and short-lived with a high turnover rate. Here, we show a critical role for linker histone H1 on the differentiation and function of neutrophils using a genome-wide CRISPR/Cas9 screen in the human cell line PLB-985. We systematically disrupted expression of somatic H1 subtypes to show that individual H1 subtypes affect PLB-985 maturation in opposite ways. Loss of H1.2 and H1.4 induced an eosinophil-like transcriptional program, thereby negatively regulating the differentiation into the neutrophil lineage. Importantly, H1 subtypes also affect neutrophil differentiation and the eosinophil-directed bias of murine bone marrow stem cells, demonstrating an unexpected subtype-specific role for H1 in granulopoiesis.

TooManyCells identifies and visualizes relationships of single-cell clades

Identifying and visualizing transcriptionally similar cells is instrumental for accurate exploration of the cellular diversity revealed by single-cell transcriptomics. However, widely used clustering and visualization algorithms produce a fixed number of cell clusters. A fixed clustering 'resolution' hampers our ability to identify and visualize echelons of cell states. We developed TooManyCells, a suite of graph-based algorithms for efficient and unbiased identification and visualization of cell clades. TooManyCells introduces a visualization model built on a concept intentionally orthogonal to dimensionality-reduction methods. TooManyCells is also equipped with an efficient matrix-free divisive hierarchical spectral clustering different from prevalent single-resolution clustering methods. TooManyCells enables multiresolution and multifaceted exploration of single-cell clades. An advantage of this paradigm is the immediate detection of rare and common populations that outperforms popular clustering and visualization algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resistance acquisition in leukemic T cells.

Dissecting the early steps of MLL induced leukaemogenic transformation using a mouse model of AML

Leukaemogenic mutations commonly disrupt cellular differentiation and/or enhance proliferation, thus perturbing the regulatory programs that control self-renewal and differentiation of stem and progenitor cells. Translocations involving the Mll1 (Kmt2a) gene generate powerful oncogenic fusion proteins, predominantly affecting infant and paediatric AML and ALL patients. The early stages of leukaemogenic transformation are typically inaccessible from human patients and conventional mouse models. Here, we take advantage of cells conditionally blocked at the multipotent haematopoietic progenitor stage to develop a MLL-r model capturing early cellular and molecular consequences of MLL-ENL expression based on a clear clonal relationship between parental and leukaemic cells. Through a combination of scRNA-seq, ATAC-seq and genome-scale CRISPR-Cas9 screening, we identify pathways and genes likely to drive the early phases of leukaemogenesis. Finally, we demonstrate the broad utility of using matched parental and transformed cells for small molecule inhibitor studies by validating both previously known and other potential therapeutic targets.

Deciphering Cell Fate Decision by Integrated Single-Cell Sequencing Analysis

Cellular differentiation is a common underlying feature of all multicellular organisms through which naïve cells progressively become fate restricted and develop into mature cells with specialized functions. A comprehensive understanding of the regulatory mechanisms of cell fate choices during de- velopment, regeneration, homeostasis, and disease is a central goal of mod- ern biology. Ongoing rapid advances in single-cell biology are enabling the exploration of cell fate specification at unprecedented resolution. Here, we review single-cell RNA sequencing and sequencing of other modalities as methods to elucidate the molecular underpinnings of lineage specification. We specifically discuss how the computational tools available to reconstruct lineage trajectories, quantify cell fate bias, and perform dimensionality re- duction for data visualization are providing new mechanistic insights into the process of cell fate decision. Studying cellular differentiation using single- cell genomic tools is paving the way for a detailed understanding of cellular behavior in health and disease.

Theory of cell fate

Cell fate decisions are controlled by complex intracellular molecular regulatory networks. Studies increasingly reveal the scale of this complexity: not only do cell fate regulatory networks contain numerous positive and negative feedback loops, they also involve a range of different kinds of nonlinear protein-protein and protein-DNA interactions. This inherent complexity and nonlinearity makes cell fate decisions hard to understand using experiment and intuition alone. In this primer, we will outline how tools from mathematics can be used to understand cell fate dynamics. We will briefly introduce some notions from dynamical systems theory, and discuss how they offer a framework within which to build a rigorous understanding of what we mean by a cell "fate", and how cells change fate. We will also outline how modern experiments, particularly high-throughput single-cell experiments, are enabling us to test and explore the limits of these ideas, and build a better understanding of cellular identities. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Models of Systems Properties and Processes > Cellular Models.

Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma

Immune checkpoint blockade (ICB) of PD-1 and CTLA-4 to treat metastatic melanoma (MM) has variable therapeutic benefit. To explore this in peripheral samples, we characterized CD8⁺ T cell gene expression across a cohort of patients with MM receiving anti-PD-1 alone (sICB) or in combination with anti-CTLA-4 (cICB). Whereas CD8⁺ transcriptional responses to sICB and cICB involve a shared gene set, the magnitude of cICB response is over fourfold greater, with preferential induction of mitosis- and interferon-related genes. Early samples from patients with durable clinical benefit demonstrated overexpression of T cell receptor-encoding genes. By mapping T cell receptor clonality, we find that responding patients have more large clones (those occupying >0.5% of repertoire) post-treatment than non-responding patients or controls, and this correlates with effector memory T cell percentage. Single-cell RNA-sequencing of eight post-treatment samples demonstrates that large clones overexpress genes implicated in cytotoxicity and characteristic of effector memory T cells, including CCL4, GNLY and NKG7. The 6-month clinical response to ICB in patients with MM is associated with the large CD8⁺ T cell clone count 21 d after treatment and agnostic to clonal specificity, suggesting that post-ICB peripheral CD8⁺ clonality can provide information regarding long-term treatment response and, potentially, facilitate treatment stratification.

The contribution of microRNA-mediated regulation to short- and long-term gene expression predictability

MicroRNAs are a class of short, noncoding RNAs which are essential for the coordination and timing of cell differentiation and embryonic development. However, despite their guiding role in development, microRNAs are dysregulated in many pathologies, including nearly all cases of cancer. While both development and oncogenesis can be thought of as extremes of phenotypic plasticity, they characteristically manifest on much different time scales: one taking place over a matter of weeks, the other typically requiring decades. Because microRNAs are believed to support this plasticity, a critically important question is how microRNAs affect phenotypic stability on different time scales, and what dynamical characteristics shift the balance between these two roles. To address this question, we extend a well-established mathematical model of transcriptional gene regulation to include translational regulation by microRNAs, and examine their effects on both short- and long-term gene expression predictability. Our findings show that microRNAs greatly improve short-term predictability for earlier, developmental phenotypes while causing a small decrease in long-term predictability, and that these effects are difficult to separate. In addition to providing a theoretical explanation for this seemingly duplicitous behavior, we describe some of the properties which determine the cost-benefit balance between short-term stabilization and long-term destabilization.

Cell lineage and communication network inference via optimization for single-cell transcriptomics

The use of single-cell transcriptomics has become a major approach to delineate cell subpopulations and the transitions between them. While various computational tools using different mathematical methods have been developed to infer clusters, marker genes, and cell lineage, none yet integrate these within a mathematical framework to perform multiple tasks coherently. Such coherence is critical for the inference of cell–cell communication, a major remaining challenge. Here, we present similarity matrix-based optimization for single-cell data analysis (SoptSC), in which unsupervised clustering, pseudotemporal ordering, lineage inference, and marker gene identification are inferred via a structured cell-to-cell similarity matrix. SoptSC then predicts cell–cell communication networks, enabling reconstruction of complex cell lineages that include feedback or feedforward interactions. Application of SoptSC to early embryonic development, epidermal regeneration, and hematopoiesis demonstrates robust identification of subpopulations, lineage relationships, and pseudotime, and prediction of pathway-specific cell communication patterns regulating processes of development and differentiation.

Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets

Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and their function is compromised in many blood disorders. HSC research has benefitted from the recent development of single-cell molecular profiling technologies, where single-cell RNA sequencing (scRNA-seq) in particular has rapidly become an established method to profile HSCs and related hematopoietic populations. The classic definition of HSCs relies on transplantation assays, which have been used to validate HSC function for cell populations defined by flow cytometry. Flow cytometry information for single cells, however, is not available for many new high-throughput scRNA-seq methods, thus highlighting an urgent need for the establishment of alternative ways to pinpoint the likely HSCs within large scRNA-seq data sets. To address this, we tested a range of machine learning approaches and developed a tool, hscScore, to score single-cell transcriptomes from murine bone marrow based on their similarity to gene expression profiles of validated HSCs. We evaluated hscScore across scRNA-seq data from different laboratories, which allowed us to establish a robust method that functions across different technologies. To facilitate broad adoption of hscScore by the wider hematopoiesis community, we have made the trained model and example code freely available online. In summary, our method hscScore provides fast identification of mouse bone marrow HSCs from scRNA-seq measurements and represents a broadly useful tool for analysis of single-cell gene expression data.

Deciphering the differentiation trajectory from hematopoietic stem cells to mast cells

Hematopoietic stem cells differentiate into all types of blood cells, including peripheral tissue-resident mast cells. The early mast cell differentiation takes place in the bone marrow, after which the progenitor cells enter the circulation and mature once reaching their target organ. Early results from single-cell culture experiments and colony-forming assays have produced the classic hierarchical tree model of hematopoiesis. The introduction of high-throughput, single-cell RNA sequencing is now revolutionizing our understanding of the differentiation process, questioning the classic tree-based models. By integrating the results from early cell culture experiments with single-cell transcriptomics, we present a differentiation landscape model of hematopoiesis and discuss it with focus on mast cells. The review also describes how the hematologic neoplasm systemic mastocytosis can be used to model human hematopoiesis using naturally occurring cell barcoding by means of the common KIT D816V mutation.

BBKNN: fast batch alignment of single cell transcriptomes

MOTIVATION

Increasing numbers of large scale single cell RNA-Seq projects are leading to a data explosion, which can only be fully exploited through data integration. A number of methods have been developed to combine diverse datasets by removing technical batch effects, but most are computationally intensive. To overcome the challenge of enormous datasets, we have developed BBKNN, an extremely fast graph-based data integration algorithm. We illustrate the power of BBKNN on large scale mouse atlasing data, and favourably benchmark its run time against a number of competing methods.

AVAILABILITY AND IMPLEMENTATION

BBKNN is available at https://github.com/Teichlab/bbknn, along with documentation and multiple example notebooks, and can be installed from pip.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

BBKNN: fast batch alignment of single cell transcriptomes

Motivation

Increasing numbers of large scale single cell RNA-Seq projects are leading to a data explosion, which can only be fully exploited through data integration. A number of methods have been developed to combine diverse datasets by removing technical batch effects, but most are computationally intensive. To overcome the challenge of enormous datasets, we have developed BBKNN, an extremely fast graph-based data integration algorithm. We illustrate the power of BBKNN on large scale mouse atlasing data, and favourably benchmark its run time against a number of competing methods.

Availability and implementation

BBKNN is available at https://github.com/Teichlab/bbknn, along with documentation and multiple example notebooks, and can be installed from pip.

Supplementary information

Supplementary data are available at Bioinformatics online.

Single-cell landscape in mammary epithelium reveals bipotent-like cells associated with breast cancer risk and outcome

Adult stem-cells may serve as the cell-of-origin for cancer, yet their unbiased identification in single cell RNA sequencing data is challenging due to the high dropout rate. In the case of breast, the existence of a bipotent stem-like state is also controversial. Here we apply a marker-free algorithm to scRNA-Seq data from the human mammary epithelium, revealing a high-potency cell-state enriched for an independent mammary stem-cell expression module. We validate this stem-like state in independent scRNA-Seq data. Our algorithm further predicts that the stem-like state is bipotent, a prediction we are able to validate using FACS sorted bulk expression data. The bipotent stem-like state correlates with clinical outcome in basal breast cancer and is characterized by overexpression of YBX1 and ENO1, two modulators of basal breast cancer risk. This study illustrates the power of a marker-free computational framework to identify a novel bipotent stem-like state in the mammary epithelium.

Single cell analysis of the developing mouse kidney provides deeper insight into marker gene expression and ligand-receptor crosstalk

Recent advances in the generation of kidney organoids and the culture of primary nephron progenitors from mouse and human have been based on knowledge of the molecular basis of kidney development in mice. Although gene expression during kidney development has been intensely investigated, single cell profiling provides new opportunities to further subsect component cell types and the signalling networks at play. Here, we describe the generation and analysis of 6732 single cell transcriptomes from the fetal mouse kidney [embryonic day (E)18.5] and 7853 sorted nephron progenitor cells (E14.5). These datasets provide improved resolution of cell types and specific markers, including subdivision of the renal stroma and heterogeneity within the nephron progenitor population. Ligand-receptor interaction and pathway analysis reveals novel crosstalk between cellular compartments and associates new pathways with differentiation of nephron and ureteric epithelium cell types. We identify transcriptional congruence between the distal nephron and ureteric epithelium, showing that most markers previously used to identify ureteric epithelium are not specific. Together, this work improves our understanding of metanephric kidney development and provides a template to guide the regeneration of renal tissue.

Mast Cells and Their Progenitors in Allergic Asthma

Mast cells and their mediators have been implicated in the pathogenesis of asthma and allergy for decades. Allergic asthma is a complex chronic lung disease in which several different immune cells, genetic factors and environmental exposures influence the pathology. Mast cells are key players in the asthmatic response through secretion of a multitude of mediators with pro-inflammatory and airway-constrictive effects. Well-known mast cell mediators, such as histamine and bioactive lipids are responsible for many of the physiological effects observed in the acute phase of allergic reactions. The accumulation of mast cells at particular sites of the allergic lung is likely relevant to the asthma phenotype, severity and progression. Mast cells located in different compartments in the lung and airways have different characteristics and express different mediators. According to in vivo experiments in mice, lung mast cells develop from mast cell progenitors induced by inflammatory stimuli to migrate to the airways. Human mast cell progenitors have been identified in the blood circulation. A high frequency of circulating human mast cell progenitors may reflect ongoing pathological changes in the allergic lung. In allergic asthma, mast cells become activated mainly via IgE-mediated crosslinking of the high affinity receptor for IgE (FcεRI) with allergens. However, mast cells can also be activated by numerous other stimuli e.g. toll-like receptors and MAS-related G protein-coupled receptor X2. In this review, we summarize research with implications on the role and development of mast cells and their progenitors in allergic asthma and cover selected activation pathways and mast cell mediators that have been implicated in the pathogenesis. The review places an emphasis on describing mechanisms identified using in vivo mouse models and data obtained by analysis of clinical samples.

Characterization of cell fate probabilities in single-cell data with Palantir

Single-cell RNA sequencing studies of differentiating systems have raised fundamental questions regarding the discrete versus continuous nature of both differentiation and cell fate. Here we present Palantir, an algorithm that models trajectories of differentiating cells by treating cell fate as a probabilistic process and leverages entropy to measure cell plasticity along the trajectory. Palantir generates a high-resolution pseudo-time ordering of cells and, for each cell state, assigns a probability of differentiating into each terminal state. We apply our algorithm to human bone marrow single-cell RNA sequencing data and detect important landmarks of hematopoietic differentiation. Palantir's resolution enables the identification of key transcription factors that drive lineage fate choice and closely track when cells lose plasticity. We show that Palantir outperforms existing algorithms in identifying cell lineages and recapitulating gene expression trends during differentiation, is generalizable to diverse tissue types, and is well-suited to resolving less-studied differentiating systems.

New insights into hematopoietic differentiation landscapes from single-cell RNA sequencing

Single-cell transcriptomics has recently emerged as a powerful tool to analyze cellular heterogeneity, discover new cell types, and infer putative differentiation routes. The technique has been rapidly embraced by the hematopoiesis research community, and like other technologies before, single-cell molecular profiling is widely expected to make important contributions to our understanding of the hematopoietic hierarchy. Much of this new interpretation relies on inference of the transcriptomic landscape as a representation of existing cellular states and associated transitions among them. Here we review how this model allows, under certain assumptions, charting of time-resolved differentiation trajectories with unparalleled resolution and how the landscape of multipotent cells may be rather devoid of discrete structures, challenging our preconceptions about stem and progenitor cell types and their organization. Finally, we highlight how promising technological advances may convert static differentiation landscapes into a dynamic cell flux model and thus provide a more holistic understanding of normal hematopoiesis and blood disorders.

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and continuous cell transitions. Partition-based graph abstraction (PAGA) provides an interpretable graph-like map of the arising data manifold, based on estimating connectivity of manifold partitions ( https://github.com/theislab/paga ). PAGA maps preserve the global topology of data, allow analyzing data at different resolutions, and result in much higher computational efficiency of the typical exploratory data analysis workflow. We demonstrate the method by inferring structure-rich cell maps with consistent topology across four hematopoietic datasets, adult planaria and the zebrafish embryo and benchmark computational performance on one million neurons.

Frontline Science: Mast cells regulate neutrophil homeostasis by influencing macrophage clearance activity

The receptor tyrosine kinase cKit and its ligand stem cell factor are essential for mast cells (MC) development and survival. Strains with mutations affecting the Kit gene display a profound MC deficiency in all tissues and have been extensively used to investigate the role of MC in both physiologic and pathologic conditions. However, these mice present a variety of abnormalities in other immune cell populations that can affect the interpretation of MC-related responses. C57BL/6 Kit^W-sh are characterized by an aberrant extramedullary myelopoiesis and systemic neutrophilia. MC deficiency in Kit^W-sh mice can be selectively repaired by engraftment with in vitro-differentiated MC to validate MC-specific functions. Nevertheless, the impact of MC reconstitution on other immune populations has never been evaluated in detail. Here, we specifically investigated the neutrophil compartment in primary and secondary lymphoid organs of C57BL/6 Kit^W-sh mice before and after MC reconstitution. We found that, albeit not apparently affecting neutrophils phenotype or maturation, MC reconstitution of Kit^W-sh mice restored the number of neutrophils at a level similar to that of wild-type C57BL/6 mice. In vitro and ex vivo experiments indicated that MC can influence neutrophil clearance by increasing macrophages' phagocytic activity. Furthermore, the G-CSF/IL-17 axis was also influenced by the presence or absence of MC in Kit^W-sh mice. These data suggest that MC play a role in the control of neutrophil homeostasis and that this aspect should be taken into account in the interpretation of results obtained using Kit^W-sh mice.

Bloody Zebrafish: Novel Methods in Normal and Malignant Hematopoiesis

Hematopoiesis is an optimal system for studying stem cell maintenance and lineage differentiation under physiological and pathological conditions. In vertebrate organisms, billions of differentiated hematopoietic cells need to be continuously produced to replenish the blood cell pool. Disruptions in this process have immediate consequences for oxygen transport, responses against pathogens, maintenance of hemostasis and vascular integrity. Zebrafish is a widely used and well-established model for studying the hematopoietic system. Several new hematopoietic regulators were identified in genetic and chemical screens using the zebrafish model. Moreover, zebrafish enables in vivo imaging of hematopoietic stem cell generation and differentiation during embryogenesis, and adulthood. Finally, zebrafish has been used to model hematopoietic diseases. Recent technological advances in single-cell transcriptome analysis, epigenetic regulation, proteomics, metabolomics, and processing of large data sets promise to transform the current understanding of normal, abnormal, and malignant hematopoiesis. In this perspective, we discuss how the zebrafish model has proven beneficial for studying physiological and pathological hematopoiesis and how these novel technologies are transforming the field.

Kit ligand has a critical role in mouse yolk sac and aorta-gonad-mesonephros hematopoiesis

Few studies report on the in vivo requirement for hematopoietic niche factors in the mammalian embryo. Here, we comprehensively analyze the requirement for Kit ligand (Kitl) in the yolk sac and aorta-gonad-mesonephros (AGM) niche. In-depth analysis of loss-of-function and transgenic reporter mouse models show that Kitl-deficient embryos harbor decreased numbers of yolk sac erythro-myeloid progenitor (EMP) cells, resulting from a proliferation defect following their initial emergence. This EMP defect causes a dramatic decrease in fetal liver erythroid cells prior to the onset of hematopoietic stem cell (HSC)-derived erythropoiesis, and a reduction in tissue-resident macrophages. Pre-HSCs in the AGM require Kitl for survival and maturation, but not proliferation. Although Kitl is expressed widely in all embryonic hematopoietic niches, conditional deletion in endothelial cells recapitulates germline loss-of-function phenotypes in AGM and yolk sac, with phenotypic HSCs but not EMPs remaining dependent on endothelial Kitl upon migration to the fetal liver. In conclusion, our data establish Kitl as a critical regulator in the in vivoAGM and yolk sac endothelial niche.

The Human Cell Atlas bone marrow single-cell interactive web portal

The Human Cell Atlas (HCA) is expected to facilitate the creation of reference cell profiles, marker genes, and gene regulatory networks that will provide a deeper understanding of healthy and disease cell types from clinical biospecimens. The hematopoietic system includes dozens of distinct, transcriptionally coherent cell types, including intermediate transitional populations that have not been previously described at a molecular level. Using the first data release from the HCA bone marrow tissue project, we resolved common, rare, and potentially transitional cell populations from over 100,000 hematopoietic cells spanning 35 transcriptionally coherent groups across eight healthy donors using emerging new computational approaches. These data highlight novel mixed-lineage progenitor populations and putative trajectories governing granulocytic, monocytic, lymphoid, erythroid, megakaryocytic, and eosinophil specification. Our analyses suggest significant variation in cell-type composition and gene expression among donors, including biological processes affected by donor age. To enable broad exploration of these findings, we provide an interactive website to probe intra-cell and extra-cell population differences within and between donors and reference markers for cellular classification and cellular trajectories through associated progenitor states.

An Introduction to the Analysis of Single-Cell RNA-Sequencing Data

The recent development of single-cell RNA sequencing has deepened our understanding of the cell as a functional unit, providing new insights based on gene expression profiles of hundreds to hundreds of thousands of individual cells, and revealing new populations of cells with distinct gene expression profiles previously hidden within analyses of gene expression performed on bulk cell populations. However, appropriate analysis and utilization of the massive amounts of data generated from single-cell RNA sequencing experiments are challenging and require an understanding of the experimental and computational pathways taken between preparation of input cells and output of interpretable data. In this review, we will discuss the basic principles of these new technologies, focusing on concepts important in the analysis of single-cell RNA-sequencing data. Specifically, we summarize approaches to quality-control measures for determination of which single cells to include for further examination, methods of data normalization and scaling to overcome the relatively inefficient capture rate of mRNA from each cell, and clustering and visualization algorithms used for dimensional reduction of the data to a two-dimensional plot.

Hematopoietic Hierarchy - An Updated Roadmap

The classical roadmap of hematopoietic hierarchy has been proposed for nearly 20 years and has become a dogma of stem cell research for most types of adult stem cells, including hematopoietic stem cells (HSCs). However, with the development of new technologies such as omics approaches at single-cell resolution, recent studies in vitro and in vivo have suggested that heterogeneity is a common feature of HSCs and their progenies. While these findings broaden our understanding of hematopoiesis, they also challenge the well-accepted hematopoietic hierarchy roadmap. Here, we review recent advances in the hematopoiesis field and provide an updated view to incorporate these new findings as well as to reflect on the complexity of HSCs and their derivatives in development and adulthood.