Molecular recording of mammalian embryogenesis

The transcriptional portraits of the neural crest at the individual cell level

Since the discovery of this cell population by His in 1850, the neural crest has been under intense study for its important role during vertebrate development. Much has been learned about the function and regulation of neural crest cell differentiation, and as a result, the neural crest has become a key model system for stem cell biology in general. The experiments performed in embryology, genetics, and cell biology in the last 150 years in the neural crest field has given rise to several big questions that have been debated intensely for many years: "How does positional information impact developmental potential? Are neural crest cells individually multipotent or a mixed population of committed progenitors? What are the key factors that regulate the acquisition of stem cell identity, and how does a stem cell decide to differentiate towards one cell fate versus another?" Recently, a marriage between single cell multi-omics, statistical modeling, and developmental biology has shed a substantial amount of light on these questions, and has paved a clear path for future researchers in the field.

Systematic reconstruction of cellular trajectories across mouse embryogenesis

Mammalian embryogenesis is characterized by rapid cellular proliferation and diversification. Within a few weeks, a single-cell zygote gives rise to millions of cells expressing a panoply of molecular programs. Although intensively studied, a comprehensive delineation of the major cellular trajectories that comprise mammalian development in vivo remains elusive. Here, we set out to integrate several single-cell RNA-sequencing (scRNA-seq) datasets that collectively span mouse gastrulation and organogenesis, supplemented with new profiling of ~150,000 nuclei from approximately embryonic day 8.5 (E8.5) embryos staged in one-somite increments. Overall, we define cell states at each of 19 successive stages spanning E3.5 to E13.5 and heuristically connect them to their pseudoancestors and pseudodescendants. Although constructed through automated procedures, the resulting directed acyclic graph (TOME (trajectories of mammalian embryogenesis)) is largely consistent with our contemporary understanding of mammalian development. We leverage TOME to systematically nominate transcription factors (TFs) as candidate regulators of each cell type's specification, as well as 'cell-type homologs' across vertebrate evolution.

Clonal relations in the mouse brain revealed by single-cell and spatial transcriptomics

The mammalian brain contains many specialized cells that develop from a thin sheet of neuroepithelial progenitor cells. Single-cell transcriptomics revealed hundreds of molecularly diverse cell types in the nervous system, but the lineage relationships between mature cell types and progenitor cells are not well understood. Here we show in vivo barcoding of early progenitors to simultaneously profile cell phenotypes and clonal relations in the mouse brain using single-cell and spatial transcriptomics. By reconstructing thousands of clones, we discovered fate-restricted progenitor cells in the mouse hippocampal neuroepithelium and show that microglia are derived from few primitive myeloid precursors that massively expand to generate widely dispersed progeny. We combined spatial transcriptomics with clonal barcoding and disentangled migration patterns of clonally related cells in densely labeled tissue sections. Our approach enables high-throughput dense reconstruction of cell phenotypes and clonal relations at the single-cell and tissue level in individual animals and provides an integrated approach for understanding tissue architecture.

Ratz et al. present an easy-to-use method to barcode progenitor cells, enabling profiling of cell phenotypes and clonal relations using single-cell and spatial transcriptomics, providing an integrated approach for understanding brain architecture.

Mapping transcriptomic vector fields of single cells

Single-cell (sc)-RNA-seq, together with RNA-velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo, that infers absolute RNA velocity, reconstructs continuous vector-field functions that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo’s power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically-labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1–GATA1 circuit. Leveraging the Least-Action-Path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo thus represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Temporal modelling using single-cell transcriptomics

Methods for profiling genes at the single-cell level have revolutionized our ability to study several biological processes and systems including development, differentiation, response programmes and disease progression. In many of these studies, cells are profiled over time in order to infer dynamic changes in cell states and types, sets of expressed genes, active pathways and key regulators. However, time-series single-cell RNA sequencing (scRNA-seq) also raises several new analysis and modelling issues. These issues range from determining when and how deep to profile cells, linking cells within and between time points, learning continuous trajectories, and integrating bulk and single-cell data for reconstructing models of dynamic networks. In this Review, we discuss several approaches for the analysis and modelling of time-series scRNA-seq, highlighting their steps, key assumptions, and the types of data and biological questions they are most appropriate for.

Single-cell delineation of lineage and genetic identity in the mouse brain

During neurogenesis, mitotic progenitor cells lining the ventricles of the embryonic mouse brain undergo their final rounds of cell division, giving rise to a wide spectrum of postmitotic neurons and glia^1,2. The link between developmental lineage and cell-type diversity remains an open question. Here we used massively parallel tagging of progenitors to track clonal relationships and transcriptomic signatures during mouse forebrain development. We quantified clonal divergence and convergence across all major cell classes postnatally, and found diverse types of GABAergic neuron that share a common lineage. Divergence of GABAergic clones occurred during embryogenesis upon cell-cycle exit, suggesting that differentiation into subtypes is initiated as a lineage-dependent process at the progenitor cell level.

Distinctive aspects of the placental epigenome and theories as to how they arise

The placenta has a methylome dramatically unlike that of any somatic cell type. Among other distinctions, it features low global DNA methylation, extensive “partially methylated domains” packed in dense heterochromatin and methylation of hundreds of CpG islands important in somatic development. These features attract interest in part because a substantial fraction of human cancers feature the exact same phenomena, suggesting parallels between epigenome formation in placentation and cancer. Placenta also features an expanded set of imprinted genes, some of which come about by distinctive developmental pathways. Recent discoveries, some from far outside the placental field, shed new light on how the unusual placental epigenetic state may arise. Nonetheless, key questions remain unresolved.

Integration of spatial and single-cell transcriptomic data elucidates mouse organogenesis

Molecular profiling of single cells has advanced our knowledge of the molecular basis of development. However, current approaches mostly rely on dissociating cells from tissues, thereby losing the crucial spatial context of regulatory processes. Here, we apply an image-based single-cell transcriptomics method, sequential fluorescence in situ hybridization (seqFISH), to detect mRNAs for 387 target genes in tissue sections of mouse embryos at the 8-12 somite stage. By integrating spatial context and multiplexed transcriptional measurements with two single-cell transcriptome atlases, we characterize cell types across the embryo and demonstrate that spatially resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary (MHB) and the developing gut tube. We uncover axes of cell differentiation that are not apparent from single-cell RNA-sequencing (scRNA-seq) data, such as early dorsal-ventral separation of esophageal and tracheal progenitor populations in the gut tube. Our method provides an approach for studying cell fate decisions in complex tissues and development.

Differentiation and Expansion of Human Extra-Embryonic Endoderm Cell Lines from Naïve Pluripotent Stem Cells

In human, endoderm is induced in two waves, with the first being the extra-embryonic primitive endoderm (PrE), otherwise known as hypoblast, induced during blastocyst development, and the second being gastrulation-stage definitive endoderm (DE). The PrE gives rise to the primary and secondary yolk sac, and has supportive functions during pregnancy for nutrient provision, with descendants of this extra-embryonic lineage also playing a role in embryonic patterning. As in DE specification, we recently found that PrE could be induced in vitro by Wnt and Nodal-related signaling, but that the critical difference was in the pluripotent starting point for differentiation. Thus, blastocyst-like naïve human pluripotent stem cells retain the unique capacity to differentiate into PrE cultures, a cell type resembling the pre-implantation hypoblast. The PrE cells could then be expanded as stable naïve extra-embryonic endoderm (nEnd) cell lines, capable of indefinite self-renewal. Here, we describe detailed protocols to differentiate naïve pluripotent stem cells into PrE and then expand the cultures as nEnd, including descriptions of morphology, passaging technique, and troubleshooting.

Primate gastrulation and early organogenesis at single-cell resolution

Our understanding of human early development is severely hampered by limited access to embryonic tissues. Due to their close evolutionary relationship with humans, nonhuman primates are often used as surrogates to understand human development but currently suffer from a lack of in vivo datasets, especially from gastrulation to early organogenesis during which the major embryonic cell types are dynamically specified. To fill this gap, we collected six Carnegie stage 8-11 cynomolgus monkey (Macaca fascicularis) embryos and performed in-depth transcriptomic analyses of 56,636 single cells. Our analyses show transcriptomic features of major perigastrulation cell types, which help shed light on morphogenetic events including primitive streak development, somitogenesis, gut tube formation, neural tube patterning and neural crest differentiation in primates. In addition, comparative analyses with mouse embryos and human embryoids uncovered conserved and divergent features of perigastrulation development across species-for example, species-specific dependency on Hippo signalling during presomitic mesoderm differentiation-and provide an initial assessment of relevant stem cell models of human early organogenesis. This comprehensive single-cell transcriptome atlas not only fills the knowledge gap in the nonhuman primate research field but also serves as an invaluable resource for understanding human embryogenesis and developmental disorders.

Lineage recording in human cerebral organoids

Induced pluripotent stem cell (iPSC)-derived organoids provide models to study human organ development. Single-cell transcriptomics enable highly resolved descriptions of cell states within these systems; however, approaches are needed to directly measure lineage relationships. Here we establish iTracer, a lineage recorder that combines reporter barcodes with inducible CRISPR-Cas9 scarring and is compatible with single-cell and spatial transcriptomics. We apply iTracer to explore clonality and lineage dynamics during cerebral organoid development and identify a time window of fate restriction as well as variation in neurogenic dynamics between progenitor neuron families. We also establish long-term four-dimensional light-sheet microscopy for spatial lineage recording in cerebral organoids and confirm regional clonality in the developing neuroepithelium. We incorporate gene perturbation (iTracer-perturb) and assess the effect of mosaic TSC2 mutations on cerebral organoid development. Our data shed light on how lineages and fates are established during cerebral organoid formation. More broadly, our techniques can be adapted in any iPSC-derived culture system to dissect lineage alterations during normal or perturbed development.

Dissecting the Complexity of Early Heart Progenitor Cells

Early heart development depends on the coordinated participation of heterogeneous cell sources. As pioneer work from Adriana C. Gittenberger-de Groot demonstrated, characterizing these distinct cell sources helps us to understand congenital heart defects. Despite decades of research on the segregation of lineages that form the primitive heart tube, we are far from understanding its full complexity. Currently, single-cell approaches are providing an unprecedented level of detail on cellular heterogeneity, offering new opportunities to decipher its functional role. In this review, we will focus on three key aspects of early heart morphogenesis: First, the segregation of myocardial and endocardial lineages, which yields an early lineage diversification in cardiac development; second, the signaling cues driving differentiation in these progenitor cells; and third, the transcriptional heterogeneity of cardiomyocyte progenitors of the primitive heart tube. Finally, we discuss how single-cell transcriptomics and epigenomics, together with live imaging and functional analyses, will likely transform the way we delve into the complexity of cardiac development and its links with congenital defects.

Single-Cell Sequencing to Unveil the Mystery of Embryonic Development

Embryonic development is a fundamental physiological process that can provide tremendous insights into stem cell biology and regenerative medicine. In this process, cell fate decision is highly heterogeneous and dynamic, and investigations at the single-cell level can greatly facilitate the understanding of the molecular roadmap of embryonic development. Rapid advances in the technology of single-cell sequencing offer a perfectly useful tool to fulfill this purpose. Despite its great promise, single-cell sequencing is highly interdisciplinary, and successful applications in specific biological contexts require a general understanding of its diversity as well as the advantage versus limitations for each of its variants. Here, the technological principles of single-cell sequencing are consolidated and its applications in the study of embryonic development are summarized. First, the technology basics are presented and the available tools for each step including cell isolation, library construction, sequencing, and data analysis are discussed. Then, the works that employed single-cell sequencing are reviewed to investigate the specific processes of embryonic development, including preimplantation, peri-implantation, gastrulation, and organogenesis. Further, insights are provided on existing challenges and future research directions.

How a cell decides its own fate: a single-cell view of molecular mechanisms and dynamics of cell-type specification

On its path from a fertilized egg to one of the many cell types in a multicellular organism, a cell turns the blank canvas of its early embryonic state into a molecular profile fine-tuned to achieve a vital organismal function. This remarkable transformation emerges from the interplay between dynamically changing external signals, the cell's internal, variable state, and tremendously complex molecular machinery; we are only beginning to understand. Recently developed single-cell omics techniques have started to provide an unprecedented, comprehensive view of the molecular changes during cell-type specification and promise to reveal the underlying gene regulatory mechanism. The exponentially increasing amount of quantitative molecular data being created at the moment is slated to inform predictive, mathematical models. Such models can suggest novel ways to manipulate cell types experimentally, which has important biomedical applications. This review is meant to give the reader a starting point to participate in this exciting phase of molecular developmental biology. We first introduce some of the principal molecular players involved in cell-type specification and discuss the important organizing ability of biomolecular condensates, which has been discovered recently. We then review some of the most important single-cell omics methods and relevant findings they produced. We devote special attention to the dynamics of the molecular changes and discuss methods to measure them, most importantly lineage tracing. Finally, we introduce a conceptual framework that connects all molecular agents in a mathematical model and helps us make sense of the experimental data.

Mapping single-cell-resolution cell phylogeny reveals cell population dynamics during organ development

Mapping the cell phylogeny of a complex multicellular organism relies on somatic mutations accumulated from zygote to adult. Available cell barcoding methods can record about three mutations per barcode, enabling only low-resolution mapping of the cell phylogeny of complex organisms. Here we developed SMALT, a substitution mutation-aided lineage-tracing system that outperforms the available cell barcoding methods in mapping cell phylogeny. We applied SMALT to Drosophila melanogaster and obtained on average more than 20 mutations on a three-kilobase-pair barcoding sequence in early-adult cells. Using the barcoding mutations, we obtained high-quality cell phylogenetic trees, each comprising several thousand internal nodes with 84-93% median bootstrap support. The obtained cell phylogenies enabled a population genetic analysis that estimates the longitudinal dynamics of the number of actively dividing parental cells (Np) in each organ through development. The Np dynamics revealed the trajectory of cell births and provided insight into the balance of symmetric and asymmetric cell division.

Endoderm and mesoderm derivatives in embryonic stem cell differentiation and their use in developmental toxicity testing

Embryonic stem cell differentiation models have increasingly been applied in non-animal test systems for developmental toxicity. After the initial focus on cardiac differentiation, attention has also included an array of neuro-ectodermal differentiation routes. Alternative differentiation routes in the mesodermal and endodermal germ lines have received less attention. This review provides an inventory of achievements in the latter areas of embryonic stem cell differentiation, with a view to possibilities for their use in non-animal test systems in developmental toxicology. This includes murine and human stem cell differentiation models, and also gains information from the field of stem cell use in regenerative medicine. Endodermal stem cell derivatives produced in vitro include hepatocytes, pancreatic cells, lung epithelium, and intestinal epithelium, and mesodermal derivatives include cardiac muscle, osteogenic, vascular and hemopoietic cells. This inventory provides an overview of studies on the different cell types together with biomarkers and culture conditions that stimulate these differentiation routes from embryonic stem cells. These models may be used to expand the spectrum of embryonic stem cell based new approach methodologies in non-animal developmental toxicity testing.

Spatial Organization of Chromatin: Emergence of Chromatin Structure During Development

Nuclei are central hubs for information processing in eukaryotic cells. The need to fit large genomes into small nuclei imposes severe restrictions on genome organization and the mechanisms that drive genome-wide regulatory processes. How a disordered polymer such as chromatin, which has vast heterogeneity in its DNA and histone modification profiles, folds into discernibly consistent patterns is a fundamental question in biology. Outstanding questions include how genomes are spatially and temporally organized to regulate cellular processes with high precision and whether genome organization is causally linked to transcription regulation. The advent of next-generation sequencing, super-resolution imaging, multiplexed fluorescent in situ hybridization, and single-molecule imaging in individual living cells has caused a resurgence in efforts to understand the spatiotemporal organization of the genome. In this review, we discuss structural and mechanistic properties of genome organization at different length scales and examine changes in higher-order chromatin organization during important developmental transitions.

Decoding and recoding plant development

The development of multicellular organisms has been studied for centuries, yet many critical events and mechanisms of regulation remain challenging to observe directly. Early research focused on detailed observational and comparative studies. Molecular biology has generated insights into regulatory mechanisms, but only for a limited number of species. Now, synthetic biology is bringing these two approaches together, and by adding the possibility of sculpting novel morphologies, opening another path to understanding biology. Here, we review a variety of recently invented techniques that use CRISPR/Cas9 and phage integrases to trace the differentiation of cells over various timescales, as well as to decode the molecular states of cells in high spatiotemporal resolution. Most of these tools have been implemented in animals. The time is ripe for plant biologists to adopt and expand these approaches. Here, we describe how these tools could be used to monitor development in diverse plant species, as well as how they could guide efforts to recode programs of interest.

Lineage-specific control of convergent differentiation by a Forkhead repressor

During convergent differentiation, multiple developmental lineages produce a highly similar or identical cell type. However, few molecular players that drive convergent differentiation are known. Here, we show that the C. elegans Forkhead transcription factor UNC-130 is required in only one of three convergent lineages that produce the same glial cell type. UNC-130 acts transiently as a repressor in progenitors and newly-born terminal cells to allow the proper specification of cells related by lineage rather than by cell type or function. Specification defects correlate with UNC-130:DNA binding, and UNC-130 can be functionally replaced by its human homolog, the neural crest lineage determinant FoxD3. We propose that, in contrast to terminal selectors that activate cell type-specific transcriptional programs in terminally differentiating cells, UNC-130 acts early and specifically in one convergent lineage to produce a cell type that also arises from molecularly distinct progenitors in other lineages.

Cellular origins and lineage relationships of the intestinal epithelium

Knowledge of the development and hierarchical organization of tissues is key to understanding how they are perturbed in injury and disease, as well as how they may be therapeutically manipulated to restore homeostasis. The rapidly regenerating intestinal epithelium harbors diverse cell types and their lineage relationships have been studied using numerous approaches, from classical label-retaining and genetic lineage tracing methods to novel transcriptome-based annotations. Here, we describe the developmental trajectories that dictate differentiation and lineage specification in the intestinal epithelium. We focus on the most recent single-cell RNA-sequencing (scRNA-seq)-based strategies for understanding intestinal epithelial cell lineage relationships, underscoring how they have refined our view of the development of this tissue and highlighting their advantages and limitations. We emphasize how these technologies have been applied to understand the dynamics of intestinal epithelial cells in homeostatic and injury-induced regeneration models.

Determining lineage relationships in kidney development and disease

The lineage relationships of cells provide information about the origins of component cell types during development and repair as well as the source of aberrant cells during disease. Genetic approaches to lineage tracing applied in the mouse have revealed much about how the mammalian kidney forms, including the identification of key progenitors for the nephrons and stromal compartments. Inducible Cre systems have also facilitated lineage tracing studies in the postnatal animal that illustrate the changes in cellular fate that can occur during kidney injury. With the advent of single-cell transcriptional profiling and trajectory analyses, predictions of cellular relationships across development are now being made in model systems, such as the mouse, as well as in human fetal kidney. Importantly, these approaches provide predictions of lineage relationships rather than definitive evidence. Although genetic approaches to the study of lineage have not previously been possible in a human setting, the application of CRISPR-Cas9 gene editing of pluripotent stem cells is beginning to teach us about human lineage relationships.

A new era in functional genomics screens

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

Diversity of developing peripheral glia revealed by single-cell RNA sequencing

The peripheral nervous system responds to a wide variety of sensory stimuli, a process that requires great neuronal diversity. These diverse neurons are closely associated with glial cells originating from the neural crest. However, the molecular nature and diversity among peripheral glia are not understood. Here, we used single-cell RNA sequencing to profile developing and mature glia from somatosensory dorsal root ganglia and auditory spiral ganglia. We found that glial precursors (GPs) in these two systems differ in their transcriptional profiles. Despite their unique features, somatosensory and auditory GPs undergo convergent differentiation to generate molecularly uniform myelinating and non-myelinating Schwann cells. By contrast, somatosensory and auditory satellite glial cells retain system-specific features. Lastly, we identified a glial signature gene set, providing new insights into commonalities among glia across the nervous system. This survey of gene expression in peripheral glia constitutes a resource for understanding functions of glia across different sensory modalities.

Applications of high-resolution clone tracking technologies in cancer

Tumors are comprised of dynamic, heterogenous cell populations characterized by numerous genetic and non-genetic alterations that accumulate and change with disease progression and treatment. Retrospective analyses of tumor evolution have relied on the measurement of genetic markers (such as copy number variants) to infer clonal dynamics. However, these approaches neglect the critical contributions of non-genetic drivers of disease. Techniques that harness the power of prospective clone tracking via heritable barcode tags provide an alternative strategy. In this review, we discuss methods for high-resolution, quantitative clone tracking, including recent advancements to pair barcode-specific functionality with scRNA-seq, clonal cell isolation, and in situ hybridization and imaging. We discuss these approaches in the context of cancer cell heterogeneity and treatment resistance.

Applications of Single-Cell DNA Sequencing

Over the past decade, genomic analyses of single cells-the fundamental units of life-have become possible. Single-cell DNA sequencing has shed light on biological questions that were previously inaccessible across diverse fields of research, including somatic mutagenesis, organismal development, genome function, and microbiology. Single-cell DNA sequencing also promises significant future biomedical and clinical impact, spanning oncology, fertility, and beyond. While single-cell approaches that profile RNA and protein have greatly expanded our understanding of cellular diversity, many fundamental questions in biology and important biomedical applications require analysis of the DNA of single cells. Here, we review the applications and biological questions for which single-cell DNA sequencing is uniquely suited or required. We include a discussion of the fields that will be impacted by single-cell DNA sequencing as the technology continues to advance.

In vivo Pooled Screening: A Scalable Tool to Study the Complexity of Aging and Age-Related Disease

Biological aging, and the diseases of aging, occur in a complex in vivo environment, driven by multiple interacting processes. A convergence of recently developed technologies has enabled in vivo pooled screening: direct administration of a library of different perturbations to a living animal, with a subsequent readout that distinguishes the identity of each perturbation and its effect on individual cells within the animal. Such screens hold promise for efficiently applying functional genomics to aging processes in the full richness of the in vivo setting. In this review, we describe the technologies behind in vivo pooled screening, including a range of options for delivery, perturbation and readout methods, and outline their potential application to aging and age-related disease. We then suggest how in vivo pooled screening, together with emerging innovations in each of its technological underpinnings, could be extended to shed light on key open questions in aging biology, including the mechanisms and limits of epigenetic reprogramming and identifying cellular mediators of systemic signals in aging.

Lineages of embryonic stem cells show non-Markovian state transitions

Pluripotent embryonic stem cells (ESCs) constitute the cell types of the adult vertebrate through a series of developmental state transitions. These states can be defined by expression levels of marker genes, such as Nanog and Sox2. In culture, ESCs reversibly transition between states. However, whether ESCs retain memory of their previous states or transition in a memoryless (Markovian) process remains relatively unknown. Here, we show some highly dynamic lineages of ESCs do not exhibit the Markovian property: their previous states and kin relations influence future choices. Unexpectedly, the distribution of lineages across their composition between states is constant over time, contrasting with the predictions of a Markov model. Additionally, highly dynamic ESC lineages show skewed cell fate distributions after retinoic acid differentiation. Together, these data suggest ESC lineage is an important variable governing future cell states, with implications for stem cell function and development.

Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees

The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.

LineageOT is a unified framework for lineage tracing and trajectory inference

Understanding the genetic and epigenetic programs that control differentiation during development is a fundamental challenge, with broad impacts across biology and medicine. Measurement technologies like single-cell RNA-sequencing and CRISPR-based lineage tracing have opened new windows on these processes, through computational trajectory inference and lineage reconstruction. While these two mathematical problems are deeply related, methods for trajectory inference are not typically designed to leverage information from lineage tracing and vice versa. Here, we present LineageOT, a unified framework for lineage tracing and trajectory inference. Specifically, we leverage mathematical tools from graphical models and optimal transport to reconstruct developmental trajectories from time courses with snapshots of both cell states and lineages. We find that lineage data helps disentangle complex state transitions with increased accuracy using fewer measured time points. Moreover, integrating lineage tracing with trajectory inference in this way could enable accurate reconstruction of developmental pathways that are impossible to recover with state-based methods alone.

Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states

The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ∼380,000 CRISPR target sites and reconstruct dissemination of ∼28,000 single cells across multiple metastatic sites. We find that cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations.

Synthetic gene circuits as tools for drug discovery

Within mammalian systems, there exists enormous opportunity to use synthetic gene circuits to enhance phenotype-based drug discovery, to map the molecular origins of disease, and to validate therapeutics in complex cellular systems. While drug discovery has relied on marker staining and high-content imaging in cell-based assays, synthetic gene circuits expand the potential for precision and speed. Here we present a vision of how circuits can improve the speed and accuracy of drug discovery by enhancing the efficiency of hit triage, capturing disease-relevant dynamics in cell-based assays, and simplifying validation and readouts from organoids and microphysiological systems (MPS). By tracking events and cellular states across multiple length and time scales, circuits will transform how we decipher the causal link between molecular events and phenotypes to improve the selectivity and sensitivity of cell-based assays.

p53 convergently activates Dux/DUX4 in embryonic stem cells and in facioscapulohumeral muscular dystrophy cell models

In mammalian embryos, proper zygotic genome activation (ZGA) underlies totipotent development. Double homeobox (DUX)-family factors participate in ZGA, and mouse Dux is required for forming cultured two-cell (2C)-like cells. Remarkably, in mouse embryonic stem cells, Dux is activated by the tumor suppressor p53, and Dux expression promotes differentiation into expanded-fate cell types. Long-read sequencing and assembly of the mouse Dux locus reveals its complex chromatin regulation including putative positive and negative feedback loops. We show that the p53-DUX/DUX4 regulatory axis is conserved in humans. Furthermore, we demonstrate that cells derived from patients with facioscapulohumeral muscular dystrophy (FSHD) activate human DUX4 during p53 signaling via a p53-binding site in a primate-specific subtelomeric long terminal repeat (LTR)10C element. In summary, our work shows that p53 activation convergently evolved to couple p53 to Dux/DUX4 activation in embryonic stem cells, embryos and cells from patients with FSHD, potentially uniting the developmental and disease regulation of DUX-family factors and identifying evidence-based therapeutic opportunities for FSHD.

Identification of Intercellular Crosstalk between Decidual Cells and Niche Cells in Mice

Decidualization is a crucial step for human reproduction, which is a prerequisite for embryo implantation, placentation and pregnancy maintenance. Despite rapid advances over recent years, the molecular mechanism underlying decidualization remains poorly understood. Here, we used the mouse as an animal model and generated a single-cell transcriptomic atlas of a mouse uterus during decidualization. By analyzing the undecidualized inter-implantation site of the uterus as a control, we were able to identify global gene expression changes associated with decidualization in each cell type. Additionally, we identified intercellular crosstalk between decidual cells and niche cells, including immune cells, endothelial cells and trophoblast cells. Our data provide a valuable resource for deciphering the molecular mechanism underlying decidualization.

Highly conserved and cis-acting lncRNAs produced from paralogous regions in the center of HOXA and HOXB clusters in the endoderm lineage

Long noncoding RNAs (lncRNAs) have been shown to play important roles in gene regulatory networks acting in early development. There has been rapid turnover of lncRNA loci during vertebrate evolution, with few human lncRNAs conserved beyond mammals. The sequences of these rare deeply conserved lncRNAs are typically not similar to each other. Here, we characterize HOXA-AS3 and HOXB-AS3, lncRNAs produced from the central regions of the HOXA and HOXB clusters. Sequence-similar orthologs of both lncRNAs are found in multiple vertebrate species and there is evident sequence similarity between their promoters, suggesting that the production of these lncRNAs predates the duplication of the HOX clusters at the root of the vertebrate lineage. This conservation extends to similar expression patterns of the two lncRNAs, in particular in cells transiently arising during early development or in the adult colon. Functionally, the RNA products of HOXA-AS3 and HOXB-AS3 regulate the expression of their overlapping HOX5-7 genes both in HT-29 cells and during differentiation of human embryonic stem cells. Beyond production of paralogous protein-coding and microRNA genes, the regulatory program in the HOX clusters therefore also relies on paralogous lncRNAs acting in restricted spatial and temporal windows of embryonic development and cell differentiation.

Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-cell molecular tools have been developed at an incredible pace over the last five years as sequencing costs continue to drop and numerous molecular assays have been coupled to sequencing readouts. This rapid period of technological development has facilitated the delineation of individual molecular characteristics including the genome, transcriptome, epigenome, and proteome of individual cells, leading to an unprecedented resolution of the molecular networks governing complex biological systems. The immense power of single-cell molecular screens has been particularly highlighted through work in systems where cellular heterogeneity is a key feature, such as stem cell biology, immunology, and tumor cell biology. Single-cell-omics technologies have already contributed to the identification of novel disease biomarkers, cellular subsets, therapeutic targets and diagnostics, many of which would have been undetectable by bulk sequencing approaches. More recently, efforts to integrate single-cell multi-omics with single cell functional output and/or physical location have been challenging but have led to substantial advances. Perhaps most excitingly, there are emerging opportunities to reach beyond the description of static cellular states with recent advances in modulation of cells through CRISPR technology, in particular with the development of base editors which greatly raises the prospect of cell and gene therapies. In this review, we provide a brief overview of emerging single-cell technologies and discuss current developments in integrating single-cell molecular screens and performing single-cell multi-omics for clinical applications. We also discuss how single-cell molecular assays can be usefully combined with functional data to unpick the mechanism of cellular decision-making. Finally, we reflect upon the introduction of spatial transcriptomics and proteomics, its complementary role with single-cell RNA sequencing (scRNA-seq) and potential application in cellular and gene therapy.

Statistical mechanics meets single-cell biology

Single-cell omics is transforming our understanding of cell biology and disease, yet the systems-level analysis and interpretation of single-cell data faces many challenges. In this Perspective, we describe the impact that fundamental concepts from statistical mechanics, notably entropy, stochastic processes and critical phenomena, are having on single-cell data analysis. We further advocate the need for more bottom-up modelling of single-cell data and to embrace a statistical mechanics analysis paradigm to help attain a deeper understanding of single-cell systems biology.

Endothelial ontogeny and the establishment of vascular heterogeneity

The establishment of distinct cellular identities was pivotal during the evolution of Metazoa, enabling the emergence of an array of specialized tissues with different functions. In most animals including vertebrates, cell specialization occurs in response to a combination of intrinsic (e.g., cellular ontogeny) and extrinsic (e.g., local environment) factors that drive the acquisition of unique characteristics at the single-cell level. The first functional organ system to form in vertebrates is the cardiovascular system, which is lined by a network of endothelial cells whose organ-specific characteristics have long been recognized. Recent genetic analyses at the single-cell level have revealed that heterogeneity exists not only at the organ level but also between neighboring endothelial cells. Thus, how endothelial heterogeneity is established has become a key question in vascular biology. Drawing upon evidence from multiple organ systems, here we will discuss the role that lineage history may play in establishing endothelial heterogeneity.

Prostate cancer cell heterogeneity and plasticity: Insights from studies of genetically-engineered mouse models

Although prostate adenocarcinoma lacks distinguishable histopathological subtypes, prostate cancer displays significant inter- and intratumor heterogeneity at the molecular level and with respect to disease prognosis and treatment response. In principle, understanding the basis for prostate cancer heterogeneity can help distinguish aggressive from indolent disease, and help overcome castration-resistance in advanced prostate cancer. In this review, we will discuss recent advances in understanding the cell types of origin, putative cancer stem cells, and tumor plasticity in prostate cancer, focusing on insights from studies of genetically engineered mouse models (GEMMs). We will also outline future directions for investigating tumor heterogeneity using mouse models of prostate cancer.

A single-cell-resolution fate map of endoderm reveals demarcation of pancreatic progenitors by cell cycle

A progenitor cell could generate a certain type or multiple types of descendant cells during embryonic development. To make all the descendant cell types and developmental trajectories of every single progenitor cell clear remains an ultimate goal in developmental biology. Characterizations of descendant cells produced by each uncommitted progenitor for a full germ layer represent a big step toward the goal. Here, we focus on early foregut endoderm, which generates foregut digestive organs, including the pancreas, liver, foregut, and ductal system, through distinct lineages. Using unbiased single-cell labeling techniques, we label every individual zebrafish foregut endodermal progenitor cell out of 216 cells to visibly trace the distribution and number of their descendant cells. Hence, single-cell-resolution fate and proliferation maps of early foregut endoderm are established, in which progenitor regions of each foregut digestive organ are precisely demarcated. The maps indicate that the pancreatic endocrine progenitors are featured by a cell cycle state with a long G1 phase. Manipulating durations of the G1 phase modulates pancreatic progenitor populations. This study illustrates foregut endodermal progenitor cell fate at single-cell resolution, precisely demarcates different progenitor populations, and sheds light on mechanistic insights into pancreatic fate determination.

Lineage tracing and analog recording in mammalian cells by single-site DNA writing

Studying cellular and developmental processes in complex multicellular organisms can require the non-destructive observation of thousands to billions of cells deep within an animal. DNA recorders address the staggering difficulty of this task by converting transient cellular experiences into mutations at defined genomic sites that can be sequenced later in high throughput. However, existing recorders act primarily by erasing DNA. This is problematic because, in the limit of progressive erasure, no record remains. We present a DNA recorder called CHYRON (Cell History Recording by Ordered Insertion) that acts primarily by writing new DNA through the repeated insertion of random nucleotides at a single locus in temporal order. To achieve in vivo DNA writing, CHYRON combines Cas9, a homing guide RNA and the template-independent DNA polymerase terminal deoxynucleotidyl transferase. We successfully applied CHYRON as an evolving lineage tracer and as a recorder of user-selected cellular stimuli.

Piecemeal regulation of convergent neuronal lineages by bHLH transcription factors in Caenorhabditis elegans

Cells of the same type can be generated by distinct cellular lineages that originate in different parts of the developing embryo ('lineage convergence'). Several Caenorhabditis elegans neuron classes composed of left/right or radially symmetric class members display such lineage convergence. We show here that the C. elegans Atonal homolog lin-32 is differentially expressed in neuronal lineages that give rise to left/right or radially symmetric class members. Loss of lin-32 results in the selective loss of the expression of pan-neuronal markers and terminal selector-type transcription factors that confer neuron class-specific features. Another basic helix-loop-helix (bHLH) gene, the Achaete-Scute homolog hlh-14, is expressed in a mirror image pattern relative to lin-32 and is required to induce neuronal identity and terminal selector expression on the contralateral side of the animal. These findings demonstrate that distinct lineage histories converge via different bHLH factors at the level of induction of terminal selector identity determinants, which thus serve as integrators of distinct lineage histories. We also describe neuron-to-neuron identity transformations in lin-32 mutants, which we propose to also be the result of misregulation of terminal selector gene expression.

Defining the Emerging Blood System During Development at Single-Cell Resolution

Developmental hematopoiesis differs from adult and is far less described. In the developing embryo, waves of lineage-restricted blood precede the ultimate emergence of definitive hematopoietic stem cells (dHSCs) capable of maintaining hematopoiesis throughout life. During the last two decades, the advent of single-cell genomics has provided tools to circumvent previously impeding characteristics of embryonic hematopoiesis, such as cell heterogeneity and rare cell states, allowing for definition of lineage trajectories, cellular hierarchies, and cell-type specification. The field has rapidly advanced from microfluidic platforms and targeted gene expression analysis, to high throughput unbiased single-cell transcriptomic profiling, single-cell chromatin analysis, and cell tracing-offering a plethora of tools to resolve important questions within hematopoietic development. Here, we describe how these technologies have been implemented to address a wide range of aspects of embryonic hematopoiesis ranging from the gene regulatory network of dHSC formation via endothelial to hematopoietic transition (EHT) and how EHT can be recapitulated in vitro, to hematopoietic trajectories and cell fate decisions. Together, these studies have important relevance for regenerative medicine and for our understanding of genetic blood disorders and childhood leukemias.

CRISPR-Cas Tools and Their Application in Genetic Engineering of Human Stem Cells and Organoids

CRISPR-Cas technology has revolutionized biological research and holds great therapeutic potential. Here, we review CRISPR-Cas systems and their latest developments with an emphasis on application to human cells. We also discuss how different CRISPR-based strategies can be used to accomplish a particular genome engineering goal. We then review how different CRISPR tools have been used in genome engineering of human stem cells in vitro, covering both the pluripotent (iPSC/ESC) and somatic adult stem cell fields and, in particular, 3D organoid cultures. Finally, we discuss the progress and challenges associated with CRISPR-based genome editing of human stem cells for therapeutic use.

All models are wrong, but some are useful: Establishing standards for stem cell-based embryo models

Detailed studies of the embryo allow an increasingly mechanistic understanding of development, which has proved of profound relevance to human disease. The last decade has seen in vitro cultured stem cell-based models of embryo development flourish, which provide an alternative to the embryo for accessible experimentation. However, the usefulness of any stem cell-based embryo model will be determined by how accurately it reflects in vivo embryonic development, and/or the extent to which it facilitates new discoveries. Stringent benchmarking of embryo models is thus an important consideration for this growing field. Here we provide an overview of means to evaluate both the properties of stem cells, the building blocks of most embryo models, as well as the usefulness of current and future in vitro embryo models.

Hotspot identifies informative gene modules across modalities of single-cell genomics

Two fundamental aims that emerge when analyzing single-cell RNA-seq data are identifying which genes vary in an informative manner and determining how these genes organize into modules. Here, we propose a general approach to these problems, called "Hotspot," that operates directly on a given metric of cell-cell similarity, allowing for its integration with any method (linear or non-linear) for identifying the primary axes of transcriptional variation between cells. In addition, we show that when using multimodal data, Hotspot can be used to identify genes whose expression reflects alternative notions of similarity between cells, such as physical proximity in a tissue or clonal relatedness in a cell lineage tree. In this manner, we demonstrate that while Hotspot is capable of identifying genes that reflect nuanced transcriptional variability between T helper cells, it can also identify spatially dependent patterns of gene expression in the cerebellum as well as developmentally heritable expression programs during embryogenesis. Hotspot is implemented as an open-source Python package and is available for use at http://www.github.com/yoseflab/hotspot. A record of this paper's transparent peer review process is included in the supplemental information.

A single-embryo, single-cell time-resolved model for mouse gastrulation

Mouse embryonic development is a canonical model system for studying mammalian cell fate acquisition. Recently, single-cell atlases comprehensively charted embryonic transcriptional landscapes, yet inference of the coordinated dynamics of cells over such atlases remains challenging. Here, we introduce a temporal model for mouse gastrulation, consisting of data from 153 individually sampled embryos spanning 36 h of molecular diversification. Using algorithms and precise timing, we infer differentiation flows and lineage specification dynamics over the embryonic transcriptional manifold. Rapid transcriptional bifurcations characterize the commitment of early specialized node and blood cells. However, for most lineages, we observe combinatorial multi-furcation dynamics rather than hierarchical transcriptional transitions. In the mesoderm, dozens of transcription factors combinatorially regulate multifurcations, as we exemplify using time-matched chimeric embryos of Foxc1/Foxc2 mutants. Our study rejects the notion of differentiation being governed by a series of binary choices, providing an alternative quantitative model for cell fate acquisition.

Single-cell profiling for advancing birth defects research and prevention

Cellular analysis of developmental processes and toxicities has traditionally entailed bulk methods (e.g., transcriptomics) that lack single cell resolution or tissue localization methods (e.g., immunostaining) that allow only a few genes to be monitored in each experiment. Recent technological advances have enabled interrogation of genomic function at the single-cell level, providing new opportunities to unravel developmental pathways and processes with unprecedented resolution. Here, we review emerging technologies of single-cell RNA-sequencing (scRNA-seq) to globally characterize the gene expression sets of different cell types and how different cell types emerge from earlier cell states in development. Cell atlases of experimental embryology and human embryogenesis at single-cell resolution will provide an encyclopedia of genes that define key stages from gastrulation to organogenesis. This technology, combined with computational models to discover key organizational principles, was recognized by Science magazine as the "Breakthrough of the year" for 2018 due to transformative potential on the way we study how human cells mature over a lifetime, how tissues regenerate, and how cells change in diseases (e.g., patient-derived organoids to screen disease-specific targets and design precision therapy). Profiling transcriptomes at the single-cell level can fulfill the need for greater detail in the molecular progression of all cell lineages, from pluripotency to adulthood and how cell-cell signaling pathways control progression at every step. Translational opportunities emerge for elucidating pathogenesis of genetic birth defects with cellular precision and improvements for predictive toxicology of chemical teratogenesis.

Imaging cell lineage with a synthetic digital recording system

During multicellular development, spatial position and lineage history play powerful roles in controlling cell fate decisions. Using a serine integrase-based recording system, we engineered cells to record lineage information in a format that can be read out in situ. The system, termed integrase-editable memory by engineered mutagenesis with optical in situ readout (intMEMOIR), allowed in situ reconstruction of lineage relationships in cultured mouse cells and flies. intMEMOIR uses an array of independent three-state genetic memory elements that can recombine stochastically and irreversibly, allowing up to 59,049 distinct digital states. It reconstructed lineage trees in stem cells and enabled simultaneous analysis of single-cell clonal history, spatial position, and gene expression in Drosophila brain sections. These results establish a foundation for microscopy-readable lineage recording and analysis in diverse systems.

Lineage barcoding in mice with homing CRISPR

Classic approaches to mapping the developmental history of cells in vivo have relied on techniques that require complex interventions and often capture only a single trajectory or moment in time. We have previously described a developmental barcoding system to address these issues using synthetically induced mutations to record information about each cell's lineage in its genome. This system uses MARC1 mouse lines, which have multiple homing guide RNAs that each generate hundreds of mutant alleles and combine to produce an exponential diversity of barcodes. Here, we detail two MARC1 lines that are available from a public repository. We describe strategies for using MARC1 mice and experimental design considerations. We provide a protocol for barcode retrieval and sequencing as well as the analysis of the sequencing data. This protocol generates barcodes based on synthetically induced mutations in mice to enable lineage analysis.