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The blastocyst (the early mammalian embryo) forms all embryonic and extra-embryonic tissues, including the placenta. It consists of a spherical thin-walled layer, known as the trophectoderm, that surrounds a fluid-filled cavity sheltering the embryonic cells 1 . From mouse blastocysts, it is possible to derive both trophoblast 2 and embryonic stem-cell lines 3 , which are in vitro analogues of the trophectoderm and embryonic compartments, respectively. Here we report that trophoblast and embryonic stem cells cooperate in vitro to form structures that morphologically and transcriptionally resemble embryonic day 3.5 blastocysts, termed blastoids. Like blastocysts, blastoids form from inductive signals that originate from the inner embryonic cells and drive the development of the outer trophectoderm. The nature and function of these signals have been largely unexplored. Genetically and physically uncoupling the embryonic and trophectoderm compartments, along with single-cell transcriptomics, reveals the extensive inventory of embryonic inductions. We specifically show that the embryonic cells maintain trophoblast proliferation and self-renewal, while fine-tuning trophoblast epithelial morphogenesis in part via a BMP4/Nodal–KLF6 axis. Although blastoids do not support the development of bona fide embryos, we demonstrate that embryonic inductions are crucial to form a trophectoderm state that robustly implants and triggers decidualization in utero. Thus, at this stage, the nascent embryo fuels trophectoderm development and implantation. Trophoblast and embryonic stem cells interact in vitro to form structures that resemble early blastocysts, and the embryo provides signals that drive early trophectoderm development and implantation.

MicroRNAs (miRNAs) repress the expression of many genes in metazoans by accelerating messenger RNA degradation and inhibiting translation, thereby reducing the level of protein. However, miRNAs only slightly reduce the mean expression of most targeted proteins, leading to speculation about their role in the variability, or noise, of protein expression. We used mathematical modeling and single-cell reporter assays to show that miRNAs, in conjunction with increased transcription, decrease protein expression noise for lowly expressed genes but increase noise for highly expressed genes. Genes that are regulated by multiple miRNAs show more-pronounced noise reduction. We estimate that hundreds of (lowly expressed) genes in mouse embryonic stem cells have reduced noise due to substantial miRNA regulation. Our findings suggest that miRNAs confer precision to protein expression and thus offer plausible explanations for the commonly observed combinatorial targeting of endogenous genes by multiple miRNAs, as well as the preferential targeting of lowly expressed genes.

During puberty, the mouse mammary gland develops into a highly branched epithelial network. Owing to the absence of exclusive stem cell markers, the location, multiplicity, dynamics and fate of mammary stem cells (MaSCs), which drive branching morphogenesis, are unknown. Here we show that morphogenesis is driven by proliferative terminal end buds that terminate or bifurcate with near equal probability, in a stochastic and time-invariant manner, leading to a heterogeneous epithelial network. We show that the majority of terminal end bud cells function as highly proliferative, lineage-committed MaSCs that are heterogeneous in their expression profile and short-term contribution to ductal extension. Yet, through cell rearrangements during terminal end bud bifurcation, each MaSC is able to contribute actively to long-term growth. Our study shows that the behaviour of MaSCs is not directly linked to a single expression profile. Instead, morphogenesis relies upon lineage-restricted heterogeneous MaSC populations that function as single equipotent pools in the long term. The formation of the branched epithelial network of the mouse mammary gland during puberty is driven by a heterogeneous population of stem cells at the terminal end buds of the epithelium. Dynamics of mammary stem cells Mammary stem cells drive branching morphogenesis in breast tissue, but their location, dynamics and fate remained unknown. Here, a multidisciplinary approach using lineage tracing, single-cell analysis, mathematical modelling and organ reconstruction defines the characteristics of mammary-gland morphogenesis. The results suggest that lineage-restricted heterogeneous stem cells modulate their proliferation behaviour through cell rearrangements every time branching and elongation of the terminal-end bud occurs.

The developmental role of histone H3K9 methylation (H3K9me), which typifies heterochromatin, remains unclear. In Caenorhabditis elegans , loss of H3K9me leads to a highly divergent upregulation of genes with tissue and developmental-stage specificity. During development H3K9me is lost from differentiated cell type-specific genes and gained at genes expressed in earlier developmental stages or other tissues. The continuous deposition of H3K9me2 by the SETDB1 homolog MET-2 after terminal differentiation is necessary to maintain repression. In differentiated tissues, H3K9me ensures silencing by restricting the activity of a defined set of transcription factors at promoters and enhancers. Increased chromatin accessibility following the loss of H3K9me is neither sufficient nor necessary to drive transcription. Increased ATAC-seq signal and gene expression correlate at a subset of loci positioned away from the nuclear envelope, while derepressed genes at the nuclear periphery remain poorly accessible despite being transcribed. In conclusion, H3K9me deposition can confer tissue-specific gene expression and maintain the integrity of terminally differentiated muscle by restricting transcription factor activity. Gasser and colleagues report that H3K9me2 and H3K9me3 repress lineage-specific and germline genes by restricting the activity of a subset of transcription factors in terminally differentiated Caenorhabditis elegans tissues.

While the heart regenerates poorly in mammals, efficient heart regeneration occurs in zebrafish. Studies in zebrafish have resulted in a model in which preexisting cardiomyocytes dedifferentiate and reinitiate proliferation to replace the lost myocardium. To identify which processes occur in proliferating cardiomyocytes we have used a single-cell RNA-sequencing approach. We uncovered that proliferating border zone cardiomyocytes have very distinct transcriptomes compared to the nonproliferating remote cardiomyocytes and that they resemble embryonic cardiomyocytes. Moreover, these cells have reduced expression of mitochondrial genes and reduced mitochondrial activity, while glycolysis gene expression and glucose uptake are increased, indicative for metabolic reprogramming. Furthermore, we find that the metabolic reprogramming of border zone cardiomyocytes is induced by Nrg1/ErbB2 signaling and is important for their proliferation. This mechanism is conserved in murine hearts in which cardiomyocyte proliferation is induced by activating ErbB2 signaling. Together these results demonstrate that glycolysis regulates cardiomyocyte proliferation during heart regeneration. Heart attacks are a common cause of death in the Western world. During a heart attack, oxygen levels in the affected part of the heart decrease, which causes heart muscle cells to die. In humans the dead cells are replaced by a permanent scar that stabilizes the injury but does not completely heal it. As a result, individuals have a lower quality of life after a heart attack and are more likely to die from a subsequent attack. Unlike humans, zebrafish are able to regenerate their hearts after injury: heart muscle cells close to a wound divide to produce new cells that slowly replace the scar tissue and restore normal function to the area. It remains unclear, however, what stimulates the heart muscle cells of zebrafish to start dividing. To address this question, Honkoop, de Bakker et al. used a technique called single-cell sequencing to study heart muscle cells in wounded zebrafish hearts. The experiments identified a group of heart muscle cells close to the site of the wound that multiplied to repair the damage. This group of cells had altered their metabolism compared to other heart muscle cells so that they relied on a pathway called glycolysis to produce the energy and building blocks they needed to proliferate. Blocking glycolysis impaired the ability of the heart muscle cells to divide, indicating that this switch is necessary for the heart to regenerate. Further experiments showed that a signaling cascade, which includes the molecules Nrg1 and ErbB2, induces heart muscle cells in both zebrafish and mouse hearts to switch to glycolysis and undergo division. These findings indicate that activating glycolysis in heart muscle cells may help to stimulate the heart to regenerate after a heart attack or other injury. The next step following on from this work is to develop methods to activate glycolysis and promote cell division in injured hearts.

Tracking the progeny of single cells is necessary for building lineage trees that recapitulate processes such as embryonic development and stem cell differentiation. In classical lineage tracing experiments, cells are fluorescently labelled to allow identification by microscopy of a limited number of cell clones. To track a larger number of clones in complex tissues, fluorescent proteins are now replaced by heritable DNA barcodes that are read using next-generation sequencing. In prospective lineage tracing, unique DNA barcodes are introduced into single cells through genetic manipulation (using, for example, Cre-mediated recombination or CRISPR–Cas9-mediated editing) and tracked over time. Alternatively, in retrospective lineage tracing, naturally occurring somatic mutations can be used as endogenous DNA barcodes. Finally, single-cell mRNA-sequencing datasets that capture different cell states within a developmental or differentiation trajectory can be used to recapitulate lineages. In this Review, we discuss methods for prospective or retrospective lineage tracing and demonstrate how trajectory reconstruction algorithms can be applied to single-cell mRNA-sequencing datasets to infer developmental or differentiation tracks. We discuss how these approaches are used to understand cell fate during embryogenesis, cell differentiation and tissue regeneration.

DNA methylation (5mC) is central to cellular identity. The global erasure of 5mC from the parental genomes during preimplantation mammalian development is critical to reset the methylome of gametes to the cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to 5mC erasure remains unclear. Here, we report a single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, allowing us to systematically probe the dynamics of global demethylation. When applied to mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity, with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome suggesting loss of maintenance methylation. Next, in preimplantation mouse embryos, we discovered that methylation maintenance is active till the 16-cell stage followed by passive demethylation in a fraction of cells within the early blastocyst at the 32-cell stage of development. Finally, human preimplantation embryos qualitatively show temporally delayed yet similar demethylation dynamics as mouse embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost-effective method to map the strand-specific genome-wide patterns of 5mC in single cells. Erasure of DNA methylation from the parental genomes is critical to reset the methylome of differentiated gametes to pluripotent cells in the blastocyst. Here, the authors present a high-throughput single-cell method that enables strand-specific quantification of DNA methylation and identify distinct modes of DNA demethylation dynamics during early mammalian development.

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression \"noise,'' has been suggested as a major source of this variability, and its physiological consequences have been topics of intense research for the last decade. Several recent studies have measured variability in protein and messenger RNA levels, and they have discovered strong connections between noise and gene regulation mechanisms. When integrated with discrete stochastic models, measurements of cell-to-cell variability provide a sensitive \"fingerprint\" with which to explore fundamental questions of gene regulation. In this review, we highlight several studies that used gene expression variability to develop a quantitative understanding of the mechanisms and dynamics of gene regulation.

Preserving spatial information in gene expression analyses is key for interpreting the single-cell tissue context (and even subcellular environments) of RNAs to achieve a more complete understanding of the underlying physiology. This Innovation article describes the emerging technologies of and biological insights from spatially resolved transcriptomics technologies, and how they set the stage for comprehensive investigations using complementary omic approaches. Considerable progress in sequencing technologies makes it now possible to study the genomic and transcriptomic landscape of single cells. However, to better understand the complexity of multicellular organisms, we must devise ways to perform high-throughput measurements while preserving spatial information about the tissue context or subcellular localization of analysed nucleic acids. In this Innovation article, we summarize pioneering technologies that enable spatially resolved transcriptomics and discuss how these methods have the potential to extend beyond transcriptomics to encompass spatially resolved genomics, proteomics and possibly other omic disciplines.

Method for combined genome and transcriptome sequencing from the same single cell shows that copy number variations influence cell-to-cell variability in gene expression levels. Single-cell genomics and single-cell transcriptomics have emerged as powerful tools to study the biology of single cells at a genome-wide scale. However, a major challenge is to sequence both genomic DNA and mRNA from the same cell, which would allow direct comparison of genomic variation and transcriptome heterogeneity. We describe a quasilinear amplification strategy to quantify genomic DNA and mRNA from the same cell without physically separating the nucleic acids before amplification. We show that the efficiency of our integrated approach is similar to existing methods for single-cell sequencing of either genomic DNA or mRNA. Further, we find that genes with high cell-to-cell variability in transcript numbers generally have lower genomic copy numbers, and vice versa, suggesting that copy number variations may drive variability in gene expression among individual cells. Applications of our integrated sequencing approach could range from gaining insights into cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissues.