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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.

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.

Variation among RNA transcript isoforms can be generated from alternative start and polyadenylation sites, and results in RNAs and proteins with different properties being generated from the same genomic sequence; here a new method termed transcript isoform sequencing is described in yeast, and the method allows a fuller exploration of transcriptome diversity across the compact yeast genome. Yeast transcription variants quantified The expression of eukaryotic genomes is a complicated matter, a long way from the old picture of a series of distinct protein-coding genes separated by less-important tracts of DNA. Lars Steinmetz and colleagues have used a novel technique termed TIF-Seq to demonstrate that the yeast genome containing around 6,000 protein-coding genes produces more than 1.88 million unique transcript isoforms (TIFs), defined as unique combinations of start (5′) and end (3′) RNA sequences. This work demonstrates that the complexity of overlapping transcript isoforms has been greatly underestimated previously. Transcript function is determined by sequence elements arranged on an individual RNA molecule. Variation in transcripts can affect messenger RNA stability, localization and translation 1 , or produce truncated proteins that differ in localization 2 or function 3 . Given the existence of overlapping, variable transcript isoforms, determining the functional impact of the transcriptome requires identification of full-length transcripts, rather than just the genomic regions that are transcribed 4 , 5 . Here, by jointly determining both transcript ends for millions of RNA molecules, we reveal an extensive layer of isoform diversity previously hidden among overlapping RNA molecules. Variation in transcript boundaries seems to be the rule rather than the exception, even within a single population of yeast cells. Over 26 major transcript isoforms per protein-coding gene were expressed in yeast. Hundreds of short coding RNAs and truncated versions of proteins are concomitantly encoded by alternative transcript isoforms, increasing protein diversity. In addition, approximately 70% of genes express alternative isoforms that vary in post-transcriptional regulatory elements, and tandem genes frequently produce overlapping or even bicistronic transcripts. This extensive transcript diversity is generated by a relatively simple eukaryotic genome with limited splicing, and within a genetically homogeneous population of cells. Our findings have implications for genome compaction, evolution and phenotypic diversity between single cells. These data also indicate that isoform diversity as well as RNA abundance should be considered when assessing the functional repertoire of genomes.

Genome editing holds promise for correcting pathogenic mutations. However, it is difficult to determine off-target effects of editing due to single-nucleotide polymorphism in individuals. Here we developed a method named GOTI (genome-wide off-target analysis by two-cell embryo injection) to detect off-target mutations by editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or base editors. Comparison of the whole-genome sequences of progeny cells of edited and nonedited blastomeres at embryonic day 14.5 showed that off-target single-nucleotide variants (SNVs) were rare in embryos edited by CRISPR-Cas9 or adenine base editor, with a frequency close to the spontaneous mutation rate. By contrast, cytosine base editing induced SNVs at more than 20-fold higher frequencies, requiring a solution to address its fidelity.

In order to obtain a systems‐level understanding of a complex biological system, detailed proteome information is essential. Despite great progress in proteomics technologies, thorough interrogation of the proteome from quantity‐limited biological samples is hampered by inefficiencies during processing. To address these challenges, here we introduce a novel protocol using paramagnetic beads, termed Single‐Pot Solid‐Phase‐enhanced Sample Preparation (SP3). SP3 provides a rapid and unbiased means of proteomic sample preparation in a single tube that facilitates ultrasensitive analysis by outperforming existing protocols in terms of efficiency, scalability, speed, throughput, and flexibility. To illustrate these benefits, characterization of 1,000 HeLa cells and single Drosophila embryos is used to establish that SP3 provides an enhanced platform for profiling proteomes derived from sub‐microgram amounts of material. These data present a first view of developmental stage‐specific proteome dynamics in Drosophila at a single‐embryo resolution, permitting characterization of inter‐individual expression variation. Together, the findings of this work position SP3 as a superior protocol that facilitates exciting new directions in multiple areas of proteomics ranging from developmental biology to clinical applications. Synopsis A new proteomic sample preparation protocol allows fast, efficient and ultra‐sensitive analyses. The method is illustrated by profiling proteomes from sub‐microgram amounts of material, including the first proteome screen of Drosophila development at a single‐embryo resolution. A novel protocol using paramagnetic beads, termed Single‐Pot Solid‐Phase‐enhanced Sample Preparation (SP3) is presented. SP3 enables protein and peptide enrichment, cleanup, digestion, chemical isotope labeling and fractionation in a single tube, without limitations arising from reagent compatibility. SP3 allows unmatched ultra‐sensitive proteome profiling from sub‐microgram amounts of material, as low as 1,000 HeLa cells or a single fly embryo. The first quantitative analysis of early Drosophila development at a single‐embryo resolution reveals dynamic trends in the developmental proteome. Graphical Abstract A new proteomic sample preparation protocol allows fast, efficient and ultra‐sensitive analyses. The method is illustrated by profiling proteomes from sub‐microgram amounts of material, including the first proteome screen of Drosophila development at a single‐embryo resolution.

Microscopy and fluorescence‐activated cell sorting (FACS) are two of the most important tools for single‐cell phenotyping in basic and biomedical research. Microscopy provides high‐resolution snapshots of cell morphology and the inner workings of cells, while FACS isolates thousands of cells per second using simple parameters, such as the intensity of fluorescent protein labels. Recent technologies are now combining both methods to enable the fast isolation of cells with microscopic phenotypes of interest, thereby bridging a long‐standing gap in the life sciences. In this Commentary, we discuss the technical advancements made by image‐enabled cell sorting and highlight novel experimental strategies in functional genomics and single‐cell research. Graphical Abstract This Commentary discusses the technical advancements made by image‐enabled cell sorting and highlights novel experimental strategies in functional genomics and single‐cell research.

The development of the nervous system involves a coordinated succession of events including the migration of GABAergic (γ-aminobutyric-acid-releasing) neurons from ventral to dorsal forebrain and their integration into cortical circuits. However, these interregional interactions have not yet been modelled with human cells. Here we generate three-dimensional spheroids from human pluripotent stem cells that resemble either the dorsal or ventral forebrain and contain cortical glutamatergic or GABAergic neurons. These subdomain-specific forebrain spheroids can be assembled in vitro to recapitulate the saltatory migration of interneurons observed in the fetal forebrain. Using this system, we find that in Timothy syndrome—a neurodevelopmental disorder that is caused by mutations in the Ca V 1.2 calcium channel—interneurons display abnormal migratory saltations. We also show that after migration, interneurons functionally integrate with glutamatergic neurons to form a microphysiological system. We anticipate that this approach will be useful for studying neural development and disease, and for deriving spheroids that resemble other brain regions to assemble circuits in vitro . Human pluripotent stem cells were used to develop dorsal and ventral forebrain 3D spheroids, which can be assembled to study interneuron migration and to derive a functionally integrated forebrain system with cortical interneurons and glutamatergic neurons. Modelling forebrains in a dish GABAergic neurons play important roles in brain function and are implicated in numerous psychiatric disorders. They migrate long distances from the ventral to the dorsal forebrain before integrating to cortical circuits. In vitro modelling of GABAergic neuronal differentiation during this interaction would allow us to investigate the cause of human brain disorders associated with defects in neuronal migration, but this has so far been difficult. Sergiu Paşca and colleagues have developed an approach for generating neural three-dimensional spheroids resembling either the ventral or dorsal forebrain. They show that assembling the two types of spheroids separately in vitro allows the saltatory migration of human interneurons into the cortex, as seen in human development, and the formation of functional synapses with the dorsally derived cortical glutamatergic neurons. In this context, they find that interneurons from Timothy syndrome patients exhibit perturbation in migration patterns. Elsewhere in this issue, Paola Arlotta and colleagues carried out single cell expression analysis on cells from human brain organoids to investigate the nature of cells generated by these three-dimensional models.

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 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.

Meiotic recombination has a central role in the evolution of sexually reproducing organisms. The two recombination outcomes, crossover and non-crossover, increase genetic diversity, but have the potential to homogenize alleles by gene conversion. Whereas crossover rates vary considerably across the genome, non-crossovers and gene conversions have only been identified in a handful of loci. To examine recombination genome wide and at high spatial resolution, we generated maps of crossovers, crossover-associated gene conversion and non-crossover gene conversion using dense genetic marker data collected from all four products of fifty-six yeast (Saccharomyces cerevisiae) meioses. Our maps reveal differences in the distributions of crossovers and non-crossovers, showing more regions where either crossovers or non-crossovers are favoured than expected by chance. Furthermore, we detect evidence for interference between crossovers and non-crossovers, a phenomenon previously only known to occur between crossovers. Up to 1% of the genome of each meiotic product is subject to gene conversion in a single meiosis, with detectable bias towards GC nucleotides. To our knowledge the maps represent the first high-resolution, genome-wide characterization of the multiple outcomes of recombination in any organism. In addition, because non-crossover hotspots create holes of reduced linkage within haplotype blocks, our results stress the need to incorporate non-crossovers into genetic linkage analysis.