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The bone marrow constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular and spatial organization remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular, cellular and spatial composition of distinct bone marrow niches. This allowed us to transcriptionally profile all major bone-marrow-resident cell types, determine their localization and clarify sources of pro-haematopoietic factors. Our data demonstrate that Cxcl12-abundant-reticular (CAR) cell subsets (Adipo-CAR and Osteo-CAR) differentially localize to sinusoidal and arteriolar surfaces, act locally as ‘professional cytokine-secreting cells’ and thereby establish peri-vascular micro-niches. Importantly, the three-dimensional bone-marrow organization can be accurately inferred from single-cell transcriptome data using the RNA-Magnet algorithm described here. Together, our study reveals the cellular and spatial organization of bone marrow niches and offers a systematic approach to dissect the complex organization of whole organs.Baccin, Al-Sabah, Velten et al. use single-cell and spatially resolved transcriptomics to map the cellular, molecular and spatial organization of the endosteal, sinusoidal and arteriolar bone marrow niches.

Cancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with it the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells. Leukaemic stem cells drive acute myeloid leukaemia (AML) progression and relapse but they are incompletely characterized. Here, the authors combine single-cell transcriptomics and clonal tracking using nuclear and mitochondrial somatic variants to distinguish healthy, pre-leukaemic and leukaemic stem cells in AML.

Blood formation is believed to occur through stepwise progression of haematopoietic stem cells (HSCs) following a tree-like hierarchy of oligo-, bi- and unipotent progenitors. However, this model is based on the analysis of predefined flow-sorted cell populations. Here we integrated flow cytometric, transcriptomic and functional data at single-cell resolution to quantitatively map early differentiation of human HSCs towards lineage commitment. During homeostasis, individual HSCs gradually acquire lineage biases along multiple directions without passing through discrete hierarchically organized progenitor populations. Instead, unilineage-restricted cells emerge directly from a ‘continuum of low-primed undifferentiated haematopoietic stem and progenitor cells’ (CLOUD-HSPCs). Distinct gene expression modules operate in a combinatorial manner to control stemness, early lineage priming and the subsequent progression into all major branches of haematopoiesis. These data reveal a continuous landscape of human steady-state haematopoiesis downstream of HSCs and provide a basis for the understanding of haematopoietic malignancies. Velten et al.  use single-cell transcriptomics and functional data to map the early lineage commitment of human haematopoietic stem cells as a continuous process of cells passing through transitory states rather than demarcating discrete progenitors.

Single-cell genomics technology has transformed our understanding of complex cellular systems. However, excessive cost and a lack of strategies for the purification of newly identified cell types impede their functional characterization and large-scale profiling. Here, we have generated high-content single-cell proteo-genomic reference maps of human blood and bone marrow that quantitatively link the expression of up to 197 surface markers to cellular identities and biological processes across all main hematopoietic cell types in healthy aging and leukemia. These reference maps enable the automatic design of cost-effective high-throughput cytometry schemes that outperform state-of-the-art approaches, accurately reflect complex topologies of cellular systems and permit the purification of precisely defined cell states. The systematic integration of cytometry and proteo-genomic data enables the functional capacities of precisely mapped cell states to be measured at the single-cell level. Our study serves as an accessible resource and paves the way for a data-driven era in cytometry. Haas, Velten and colleagues use single-cell multiomics of human blood and bone marrow to generate a reference map allowing the quantitative linking of cytometry and proteo-genomic information.

Single-cell DNA methylation profiling currently suffers from excessive noise and/or limited cellular throughput. We developed scTAM-seq, a targeted bisulfite-free method for profiling up to 650 CpGs in up to 10,000 cells per experiment, with a dropout rate as low as 7%. We demonstrate that scTAM-seq can resolve DNA methylation dynamics across B-cell differentiation in blood and bone marrow, identifying intermediate differentiation states that were previously masked. scTAM-seq additionally queries surface-protein expression, thus enabling integration of single-cell DNA methylation information with cell atlas data. In summary, scTAM-seq is a high-throughput, high-confidence method for analyzing DNA methylation at single-CpG resolution across thousands of single cells.

The 5′-untranslated region (5′-UTR) of mRNAs contains elements that affect expression, yet the rules by which these regions exert their effect are poorly understood. Here, we studied the impact of 5′-UTR sequences on protein levels in yeast, by constructing a large-scale library of mutants that differ only in the 10 bp preceding the translational start site of a fluorescent reporter. Using a high-throughput sequencing strategy, we obtained highly accurate measurements of protein abundance for over 2,000 unique sequence variants. The resulting pool spanned an approximately sevenfold range of protein levels, demonstrating the powerful consequences of sequence manipulations of even 1-10 nucleotides immediately upstream of the start codon. We devised computational models that predicted over 70% of the measured expression variability in held-out sequence variants. Notably, a combined model of the most prominent features successfully explained protein abundance in an additional, independently constructed library, whose nucleotide composition differed greatly from the library used to parameterize the model. Our analysis reveals the dominant contribution of the start codon context at positions −3 to −1, mRNA secondary structure, and out-of-frame upstream AUGs (uAUGs) to phenotypic diversity, thereby advancing our understanding of how protein levels are modulated by 5′-UTR sequences, and paving the way toward predictably tuning protein expression through manipulations of 5′-UTRs.

The induction of central T cell tolerance in the thymus depends on the presentation of peripheral self-epitopes by medullary thymic epithelial cells (mTECs). This promiscuous gene expression (pGE) drives mTEC transcriptomic diversity, with non-canonical transcript initiation, alternative splicing, and expression of endogenous retroelements (EREs) representing important but incompletely understood contributors. Here we map the expression of genome-wide transcripts in immature and mature human mTECs using high-throughput 5’ cap and RNA sequencing. Both mTEC populations show high splicing entropy, potentially driven by the expression of peripheral splicing factors. During mTEC maturation, rates of global transcript mis-initiation increase and EREs enriched in long terminal repeat retrotransposons are up-regulated, the latter often found in proximity to differentially expressed genes. As a resource, we provide an interactive public interface for exploring mTEC transcriptomic diversity. Our findings therefore help construct a map of transcriptomic diversity in the healthy human thymus and may ultimately facilitate the identification of those epitopes which contribute to autoimmunity and immune recognition of tumor antigens. The thymus generates all T cells, including those that underly autoimmune diseases. Here, using deep sequencing, the authors profile human medullary thymic epithelial cells and establish a web portal to query their transcriptome, which may serve as a tool to help identify the drivers of autoimmunity.

Efficient preparation of high-quality sequencing libraries that well represent the biological sample is a key step for using next-generation sequencing in research. Tn5 enables fast, robust, and highly efficient processing of limited input material while scaling to the parallel processing of hundreds of samples. Here, we present a robust Tn5 transposase purification strategy based on an N-terminal His6-Sumo3 tag. We demonstrate that libraries prepared with our in-house Tn5 are of the same quality as those processed with a commercially available kit (Nextera XT), while they dramatically reduce the cost of large-scale experiments. We introduce improved purification strategies for two versions of the Tn5 enzyme. The first version carries the previously reported point mutations E54K and L372P, and stably produces libraries of constant fragment size distribution, even if the Tn5-to-input molecule ratio varies. The second Tn5 construct carries an additional point mutation (R27S) in the DNA-binding domain. This construct allows for adjustment of the fragment size distribution based on enzyme concentration during tagmentation, a feature that opens new opportunities for use of Tn5 in customized experimental designs. We demonstrate the versatility of our Tn5 enzymes in different experimental settings, including a novel single-cell polyadenylation site mapping protocol as well as ultralow input DNA sequencing.

Cancer stem cells are essential for initiation and therapy resistance of many cancers, including acute myeloid leukemias (AML). Here, we apply functional genomic profiling to diverse human leukemias, including high-risk MLL- and NUP98-rearranged specimens, using label tracing in vivo. Human leukemia propagation is mediated by a rare quiescent label-retaining cell (LRC) population undetectable by current immunophenotypic markers. AML quiescence is reversible, preserving genetic clonal competition and epigenetic inheritance. LRC quiescence is defined by distinct promoter-centered chromatin and gene expression dynamics controlled by an AP-1/ETS transcription factor network, where JUN is necessary and sufficient for LRC quiescence and associated with persistence and chemotherapy resistance in diverse patients. This enables prospective isolation and manipulation of immunophenotypically-varied leukemia stem cells, establishing the functions of epigenetic plasticity in leukemia development and therapy resistance. These findings offer insights into leukemia stem cell quiescence and the design of therapeutic strategies for their clinical identification and control. Acute myeloid leukemia (AML) arise from mutations of stem and progenitor cells. Here, authors identify a quiescent, label-retaining cell population in AML patient specimens that have tumor-initiation capacity and unique epigenetic and transcriptional properties that can be functionally altered by expression of transcription factors such as JUN.

Understanding the molecular and cellular processes involved in lung epithelial regeneration may fuel the development of therapeutic approaches for lung diseases. We combine mouse models allowing diphtheria toxin-mediated damage of specific epithelial cell types and parallel GFP-labeling of functionally dividing cells with single-cell transcriptomics to characterize the regeneration of the distal lung. We uncover cell types, including Krt13 + basal and Krt15 + club cells, detect an intermediate cell state between basal and goblet cells, reveal goblet cells as actively dividing progenitor cells, and provide evidence that adventitial fibroblasts act as supporting cells in epithelial regeneration. We also show that diphtheria toxin-expressing cells can persist in the lung, express specific inflammatory factors, and transcriptionally resemble a previously undescribed population in the lungs of COVID-19 patients. Our study provides a comprehensive single-cell atlas of the distal lung that characterizes early transcriptional and cellular responses to concise epithelial injury, encompassing proliferation, differentiation, and cell-to-cell interactions. This study uses single-cell transcriptomics to examine how lung cells respond to targeted damage. The authors employ genetically modified mouse models and cell sorting to enrich for rare, actively dividing cells, revealing cell types/states and alternative differentiation paths.