Molecular recording of mammalian embryogenesis

Temporal recording of mammalian development and precancer

Key to understanding many biological phenomena is knowing the temporal ordering of cellular events, which often require continuous direct observations [1, 2]. An alternative solution involves the utilization of irreversible genetic changes, such as naturally occurring mutations, to create indelible markers that enables retrospective temporal ordering [3-8]. Using NSC-seq, a newly designed and validated multi-purpose single-cell CRISPR platform, we developed a molecular clock approach to record the timing of cellular events and clonality in vivo , while incorporating assigned cell state and lineage information. Using this approach, we uncovered precise timing of tissue-specific cell expansion during murine embryonic development and identified new intestinal epithelial progenitor states by their unique genetic histories. NSC-seq analysis of murine adenomas and single-cell multi-omic profiling of human precancers as part of the Human Tumor Atlas Network (HTAN), including 116 scRNA-seq datasets and clonal analysis of 418 human polyps, demonstrated the occurrence of polyancestral initiation in 15-30% of colonic precancers, revealing their origins from multiple normal founders. Thus, our multimodal framework augments existing single-cell analyses and lays the foundation for in vivo multimodal recording, enabling the tracking of lineage and temporal events during development and tumorigenesis.

LinRace: cell division history reconstruction of single cells using paired lineage barcode and gene expression data

Lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes in single cells, which allows for inference of cell lineage and cell types at the whole organism level. While most state-of-the-art methods for lineage reconstruction utilize only the lineage barcode data, methods that incorporate gene expressions are emerging. Effectively incorporating the gene expression data requires a reasonable model of how gene expression data changes along generations of divisions. Here, we present LinRace (Lineage Reconstruction with asymmetric cell division model), which integrates lineage barcode and gene expression data using asymmetric cell division model and infers cell lineages and ancestral cell states using Neighbor-Joining and maximum-likelihood heuristics. On both simulated and real data, LinRace outputs more accurate cell division trees than existing methods. With inferred ancestral states, LinRace can also show how a progenitor cell generates a large population of cells with various functionalities.

ConvexML: Scalable and accurate inference of single-cell chronograms from CRISPR/Cas9 lineage tracing data

CRISPR/Cas9 gene editing technology has enabled lineage tracing for thousands of cells in vivo. However, most of the analysis of CRISPR/Cas9 lineage tracing data has so far been limited to the reconstruction of single-cell tree topologies, which depict lineage relationships between cells, but not the amount of time that has passed between ancestral cell states and the present. Time-resolved trees, known as chronograms, would allow one to study the evolutionary dynamics of cell populations at an unprecedented level of resolution. Indeed, time-resolved trees would reveal the timing of events on the tree, the relative fitness of subclones, and the dynamics underlying phenotypic changes in the cell population - among other important applications. In this work, we introduce the first scalable and accurate method to refine any given single-cell tree topology into a single-cell chronogram by estimating its branch lengths. To do this, we leverage a statistical model of CRISPR/Cas9 cutting with missing data, paired with a conservative version of maximum parsimony that reconstructs only the ancestral states that we are confident about. As part of our method, we propose a novel approach to represent and handle missing data - specifically, double-resection events - which greatly simplifies and speeds up branch length estimation without compromising quality. All this leads to a convex maximum likelihood estimation (MLE) problem that can be readily solved in seconds with off-the-shelf convex optimization solvers. To stabilize estimates in low-information regimes, we propose a simple penalized version of MLE using a minimum branch length and pseudocounts. We benchmark our method using simulations and show that it performs well on several tasks, outperforming more naive baselines. Our method, which we name 'ConvexML', is available through the cassiopeia open source Python package.

Range of chromatin accessibility configurations are permissive of GABAergic fate acquisition in developing mouse brain

In recent single-cell -omics studies, both the differential activity of transcription factors regulating cell fate determination and differential genome activation have been tested for utility as descriptors of cell types. Naturally, genome accessibility and gene expression are interlinked. To understand the variability in genomic feature activation in the GABAergic neurons of different spatial origins, we have mapped accessible chromatin regions and mRNA expression in single cells derived from the developing mouse central nervous system (CNS). We first defined a reference set of open chromatin regions for scATAC-seq read quantitation across samples, allowing comparison of chromatin accessibility between brain regions and cell types directly. Second, we integrated the scATAC-seq and scRNA-seq data to form a unified resource of transcriptome and chromatin accessibility landscape for the cell types in di- and telencephalon, midbrain and anterior hindbrain of E14.5 mouse embryo. Importantly, we implemented resolution optimization at the clustering, and automatized the cell typing step. We show high level of concordance between the cell clustering based on the chromatin accessibility and the transcriptome in analyzed neuronal lineages, indicating that both genome and transcriptome features can be used for cell type definition. Hierarchical clustering by the similarity in accessible chromatin reveals that the genomic feature activation correlates with neurotransmitter phenotype, selector gene expression, cell differentiation stage and neuromere origins.

A mouse model with high clonal barcode diversity for joint lineage, transcriptomic, and epigenomic profiling in single cells

Cellular lineage histories and their molecular states encode fundamental principles of tissue development and homeostasis. Current lineage-recording mouse models have insufficient barcode diversity and single-cell lineage coverage for profiling tissues composed of millions of cells. Here, we developed DARLIN, an inducible Cas9 barcoding mouse line that utilizes terminal deoxynucleotidyl transferase (TdT) and 30 CRISPR target sites. DARLIN is inducible, generates massive lineage barcodes across tissues, and enables the detection of edited barcodes in ∼70% of profiled single cells. Using DARLIN, we examined fate bias within developing hematopoietic stem cells (HSCs) and revealed unique features of HSC migration. Additionally, we established a protocol for joint transcriptomic and epigenomic single-cell measurements with DARLIN and found that cellular clonal memory is associated with genome-wide DNA methylation rather than gene expression or chromatin accessibility. DARLIN will enable the high-resolution study of lineage relationships and their molecular signatures in diverse tissues and physiological contexts.

Parallel Chondrogenesis and Osteogenesis Tissue Morphogenesis in Muscle Tissue via Combinations of TGF-β Supergene Family Members

OBJECTIVE

This study aimed to decipher the temporal and spatial signaling code for clinical cartilage and bone regeneration. We investigated the effects of continuous equal dosages of a single, dual, or triplicate growth factor combination of bone morphogenetic protein (BMP)-2, transforming growth factor (TGF)-β3, and/or BMP-7 on muscle tissue over a culturing period. The hypothesis was that specific growth factor combinations at specific time points direct tissue transformation toward endochondral bone or cartilage formation.

DESIGN

The harvested muscle tissues from F-344 adult male rats were cultured in 96-well plates maintained in a specific medium and cultured at specific conditions. And the multidimensional and multi-time point analyses were performed at both the genetic and protein levels.

RESULTS

The results insinuate that the application of growth factor stimulates a chaotic tissue response that does not follow a chronological signaling cascade. Both osteogenic and chondrogenic genes showed upregulation after induction, a similar result was also observed in the semiquantitative analysis after immunohistochemical staining against different antigens.

CONCLUSIONS

The study showed that multiple TGF-β superfamily proteins applied to tissue stimulate developmental tissue processes that do not follow current tissue formation rules. The findings contribute to the understanding of the chronological order of signals and expression patterns needed to achieve chondrogenesis, articular chondrogenesis, or osteogenesis, which is crucial for the development of treatments that can regrow bone and articular cartilage clinically.

A DNA Nanodevice-Based Platform with Diverse Capabilities

Social biotic colonies often perform intricate tasks by interindividual communication and cooperation. Inspired by these biotic behaviors, a DNA nanodevice community is proposed as a universal and scalable platform. The modular nanodevice as the infrastructure of platform contains a DNA origami triangular prism framework and a hairpin-swing arm machinery core. By coding and decoding a signal domain on the shuttled output strand in different nanodevices, an orthogonal inter-nanodevice communication network is established to connect multi-nanodevices into a functional platform. The nanodevice platform enables implementation of diverse tasks, including signal cascading and feedback, molecular input recording, distributed logic computing, and modeling of simulation for virus transmission. The nanodevice platform with powerful compatibility and programmability presents an elegant example of the combination of the distributed operation of multiple devices and the complicated interdevice communication network, and may become a new generation of intelligent DNA nanosystems.

Comprehensive spatiotemporal mapping of single-cell lineages in developing mouse brain by CRISPR-based barcoding

A fundamental interest in developmental neuroscience lies in the ability to map the complete single-cell lineages within the brain. To this end, we developed a CRISPR editing-based lineage-specific tracing (CREST) method for clonal tracing in Cre mice. We then used two complementary strategies based on CREST to map single-cell lineages in developing mouse ventral midbrain (vMB). By applying snapshotting CREST (snapCREST), we constructed a spatiotemporal lineage landscape of developing vMB and identified six progenitor archetypes that could represent the principal clonal fates of individual vMB progenitors and three distinct clonal lineages in the floor plate that specified glutamatergic, dopaminergic or both neurons. We further created pandaCREST (progenitor and derivative associating CREST) to associate the transcriptomes of progenitor cells in vivo with their differentiation potentials. We identified multiple origins of dopaminergic neurons and demonstrated that a transcriptome-defined progenitor type comprises heterogeneous progenitors, each with distinct clonal fates and molecular signatures. Therefore, the CREST method and strategies allow comprehensive single-cell lineage analysis that could offer new insights into the molecular programs underlying neural specification.

Spatiotemporal transcriptomic maps of whole mouse embryos at the onset of organogenesis

Spatiotemporal orchestration of gene expression is required for proper embryonic development. The use of single-cell technologies has begun to provide improved resolution of early regulatory dynamics, including detailed molecular definitions of most cell states during mouse embryogenesis. Here we used Slide-seq to build spatial transcriptomic maps of complete embryonic day (E) 8.5 and E9.0, and partial E9.5 embryos. To support their utility, we developed sc3D, a tool for reconstructing and exploring three-dimensional 'virtual embryos', which enables the quantitative investigation of regionalized gene expression patterns. Our measurements along the main embryonic axes of the developing neural tube revealed several previously unannotated genes with distinct spatial patterns. We also characterized the conflicting transcriptional identity of 'ectopic' neural tubes that emerge in Tbx6 mutant embryos. Taken together, we present an experimental and computational framework for the spatiotemporal investigation of whole embryonic structures and mutant phenotypes.

Cellular barcoding: From developmental tracing to anti-tumor drug discovery

Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.

Lineage motifs: developmental modules for control of cell type proportions

In multicellular organisms, cell types must be produced and maintained in appropriate proportions. One way this is achieved is through committed progenitor cells that produce specific sets of descendant cell types. However, cell fate commitment is probabilistic in most contexts, making it difficult to infer progenitor states and understand how they establish overall cell type proportions. Here, we introduce Lineage Motif Analysis (LMA), a method that recursively identifies statistically overrepresented patterns of cell fates on lineage trees as potential signatures of committed progenitor states. Applying LMA to published datasets reveals spatial and temporal organization of cell fate commitment in zebrafish and rat retina and early mouse embryo development. Comparative analysis of vertebrate species suggests that lineage motifs facilitate adaptive evolutionary variation of retinal cell type proportions. LMA thus provides insight into complex developmental processes by decomposing them into simpler underlying modules.

Best Practices in Designing, Sequencing, and Identifying Random DNA Barcodes

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way.

Synthetic developmental biology: New tools to deconstruct and rebuild developmental systems

Technological advances have driven many recent advances in developmental biology. Light sheet imaging can reveal single-cell dynamics in living three-dimensional tissues, whereas single-cell genomic methods open the door to a complete catalogue of cell types and gene expression states. An equally powerful but complementary set of approaches are also becoming available to define development processes from the bottom up. These synthetic approaches aim to reconstruct the minimal developmental patterns, signaling processes, and gene networks that produce the basic set of developmental operations: spatial polarization, morphogen interpretation, tissue movement, and cellular memory. In this review we discuss recent approaches at the intersection of synthetic biology and development, including synthetic circuits to deliver and record signaling stimuli and synthetic reconstitution of pattern formation on multicellular scales.

A single cell transcriptomic fingerprint of stressed premature, imbalanced differentiation of embryonic stem cells

Cultured naïve pluripotent ESC differentiate into first lineage, XEN or second lineage, formative pluripotency. Hyperosmotic stress (sorbitol), like retinoic acid, decreases naive pluripotency and increases XEN in two ESC lines, as reported by bulk and scRNAseq, analyzed by UMAP. Sorbitol overrides pluripotency in two ESC lines as reported by bulk and scRNAseq, analyzed by UMAP. UMAP analyzed the effects of 5 stimuli - three stressed (200-300mM sorbitol with leukemia inhibitory factor +LIF) and two unstressed (+LIF, normal stemness-NS and -LIF, normal differentiation-ND). Sorbitol and RA decrease naive pluripotency and increase subpopulations of 2-cell embryo-like and XEN sub-lineages; primitive, parietal, and visceral endoderm (VE). Between the naïve pluripotency and primitive endoderm clusters is a stress-induced cluster with transient intermediate cells with higher LIF receptor signaling, with increased Stat3, Klf4, and Tbx3 expression. Sorbitol, like RA, also suppresses formative pluripotency, increasing lineage imbalance. Although bulk RNAseq and gene ontology group analyses suggest that stress induces head organizer and placental markers, scRNAseq reveals few cells. But VE and placental markers/cells were in adjacent clusters, like recent reports. UMAPs show that dose-dependent stress overrides stemness to force premature lineage imbalance. Hyperosmotic stress induces lineage imbalance, and other toxicological stresses, like drugs with RA, may cause lineage imbalance, resulting in miscarriages or birth defects.

Toward a systems-level probing of tumor clonality

Cancer has been described as a genetic disease that clonally evolves in the face of selective pressures imposed by cell-intrinsic and extrinsic factors. Although classical models based on genetic data predominantly propose Darwinian mechanisms of cancer evolution, recent single-cell profiling of cancers has described unprecedented heterogeneity in tumors providing support for alternative models of branched and neutral evolution through both genetic and non-genetic mechanisms. Emerging evidence points to a complex interplay between genetic, non-genetic, and extrinsic environmental factors in shaping the evolution of tumors. In this perspective, we briefly discuss the role of cell-intrinsic and extrinsic factors that shape clonal behaviors during tumor progression, metastasis, and drug resistance. Taking examples of pre-malignant states associated with hematological malignancies and esophageal cancer, we discuss recent paradigms of tumor evolution and prospective approaches to further enhance our understanding of this spatiotemporally regulated process.

LinRace: single cell lineage reconstruction using paired lineage barcode and gene expression data

Understanding how single cells divide and differentiate into different cell types in developed organs is one of the major tasks of developmental and stem cell biology. Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes in single cells, which allows for the reconstruction of the cell division tree, and even the detection of cell types and differentiation trajectories at the whole organism level. While most state-of-the-art methods for lineage reconstruction utilize only the lineage barcode data, methods that incorporate gene expression data are emerging, aiming to improve the accuracy of lineage reconstruction. However, effectively incorporating the gene expression data requires a reasonable model on how gene expression data changes along generations of divisions. Here, we present LinRace (Lineage Reconstruction with asymmetric cell division model), a method that integrates the lineage barcode and gene expression data using the asymmetric cell division model and infers cell lineage under a framework combining Neighbor Joining and maximum-likelihood heuristics. On both simulated and real data, LinRace outputs more accurate cell division trees than existing methods. Moreover, LinRace can output the cell states (cell types) of ancestral cells, which is rarely performed with existing lineage reconstruction methods. The information on ancestral cells can be used to analyze how a progenitor cell generates a large population of cells with various functionalities. LinRace is available at: https://github.com/ZhangLabGT/LinRace.

CRISPR for neuroscientists

Genome engineering technologies provide an entry point into understanding and controlling the function of genetic elements in health and disease. The discovery and development of the microbial defense system CRISPR-Cas yielded a treasure trove of genome engineering technologies and revolutionized the biomedical sciences. Comprising diverse RNA-guided enzymes and effector proteins that evolved or were engineered to manipulate nucleic acids and cellular processes, the CRISPR toolbox provides precise control over biology. Virtually all biological systems are amenable to genome engineering-from cancer cells to the brains of model organisms to human patients-galvanizing research and innovation and giving rise to fundamental insights into health and powerful strategies for detecting and correcting disease. In the field of neuroscience, these tools are being leveraged across a wide range of applications, including engineering traditional and non-traditional transgenic animal models, modeling disease, testing genomic therapies, unbiased screening, programming cell states, and recording cellular lineages and other biological processes. In this primer, we describe the development and applications of CRISPR technologies while highlighting outstanding limitations and opportunities.

Recording of cellular physiological histories along optically readable self-assembling protein chains

Observing cellular physiological histories is key to understanding normal and disease-related processes. Here we describe expression recording islands-a fully genetically encoded approach that enables both continual digital recording of biological information within cells and subsequent high-throughput readout in fixed cells. The information is stored in growing intracellular protein chains made of self-assembling subunits, human-designed filament-forming proteins bearing different epitope tags that each correspond to a different cellular state or function (for example, gene expression downstream of neural activity or pharmacological exposure), allowing the physiological history to be read out along the ordered subunits of protein chains with conventional optical microscopy. We use expression recording islands to record gene expression timecourse downstream of specific pharmacological and physiological stimuli in cultured neurons and in living mouse brain, with a time resolution of a fraction of a day, over periods of days to weeks.

Single-cell analysis of bidirectional reprogramming between early embryonic states reveals mechanisms of differential lineage plasticities

Two distinct fates, pluripotent epiblast (EPI) and primitive (extra-embryonic) endoderm (PrE), arise from common progenitor cells, the inner cell mass (ICM), in mammalian embryos. To study how these sister identities are forged, we leveraged embryonic (ES) and eXtraembryonic ENdoderm (XEN) stem cells - in vitro counterparts of the EPI and PrE. Bidirectional reprogramming between ES and XEN coupled with single-cell RNA and ATAC-seq analyses uncovered distinct rates, efficiencies and trajectories of state conversions, identifying drivers and roadblocks of reciprocal conversions. While GATA4-mediated ES-to-iXEN conversion was rapid and nearly deterministic, OCT4, KLF4 and SOX2-induced XEN-to-iPS reprogramming progressed with diminished efficiency and kinetics. The dominant PrE transcriptional program, safeguarded by Gata4, and globally elevated chromatin accessibility of EPI underscored the differential plasticities of the two states. Mapping in vitro trajectories to embryos revealed reprogramming in either direction tracked along, and toggled between, EPI and PrE in vivo states without transitioning through the ICM.

Targeting the metastatic niche: Single-cell lineage tracing in prime time

Identification of actionable drug targets remains a rate-limiting step of, and one of the most prominent barriers to successful drug development for metastatic cancers. CRISPR-Cas9, a tool for making targeted genomic edits, has given rise to various novel applications that have greatly accelerated discovery in developmental biology. Recent work has coupled a CRISPR-Cas9-based lineage tracing platform with single-cell transcriptomics in the unexplored context of cancer metastasis. In this perspective, we briefly reflect on the development of these distinct technological advances and the process by which they have become integrated. We also highlight the importance of single-cell lineage tracing in oncology drug development and suggest the profound capacity of a high-resolution, computational approach to reshape cancer drug discovery by enabling identification of novel metastasis-specific drug targets and mechanisms of resistance.

Functional profiling of the Toxoplasma genome during acute mouse infection

Within a host, pathogens encounter a diverse and changing landscape of cell types, nutrients, and immune responses. Examining host-pathogen interactions in animal models can therefore reveal aspects of infection absent from cell culture. We use CRISPR-based screens to functionally profile the entire genome of the model apicomplexan parasite Toxoplasma gondii during mouse infection. Barcoded gRNAs were used to track mutant parasite lineages, enabling detection of bottlenecks and mapping of population structures. We uncovered over 300 genes that modulate parasite fitness in mice with previously unknown roles in infection. These candidates span multiple axes of host-parasite interaction, including determinants of tropism, host organelle remodeling, and metabolic rewiring. We mechanistically characterized three novel candidates, including GTP cyclohydrolase I, against which a small-molecule inhibitor could be repurposed as an antiparasitic compound. This compound exhibited antiparasitic activity against T. gondii and Plasmodium falciparum, the most lethal agent of malaria. Taken together, we present the first complete survey of an apicomplexan genome during infection of an animal host, and point to novel interfaces of host-parasite interaction that may offer new avenues for treatment.

Single-Cell Molecular Barcoding to Decode Multimodal Information Defining Cell States

Single-cell research has provided a breakthrough in biology to understand heterogeneous cell groups, such as tissues and organs, in development and disease. Molecular barcoding and subsequent sequencing technology insert a singlecell barcode into isolated single cells, allowing separation cell by cell. Given that multimodal information from a cell defines precise cellular states, recent technical advances in methods focus on simultaneously extracting multimodal data recorded in different biological materials (DNA, RNA, protein, etc.). This review summarizes recently developed singlecell multiomics approaches regarding genome, epigenome, and protein profiles with the transcriptome. In particular, we focus on how to anchor or tag molecules from a cell, improve throughputs with sample multiplexing, and record lineages, and we further discuss the future developments of the technology.

BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity

Cell plasticity is a core biological process underlying a myriad of molecular and cellular events taking place throughout organismal development and evolution. It has been postulated that cellular systems thrive to balance the organization of meta-stable states underlying this phenomenon, thereby maintaining a degree of populational homeostasis compatible with an ever-changing environment and, thus, life. Notably, albeit circumstantial evidence has been gathered in favour of the latter conceptual framework, a direct observation of meta-state dynamics and the biological consequences of such a process in generating non-genetic clonal diversity and divergent phenotypic output remains largely unexplored. To fill this void, here we develop a lineage-tracing technology termed Barcode decay Lineage Tracing-Seq. BdLT-Seq is based on episome-encoded molecular identifiers that, supported by the dynamic decay of the tracing information upon cell division, ascribe directionality to a cell lineage tree whilst directly coupling non-genetic molecular features to phenotypes in comparable genomic landscapes. We show that cell transcriptome states are both inherited, and dynamically reshaped following constrained rules encoded within the cell lineage in basal growth conditions, upon oncogene activation and throughout the process of reversible resistance to therapeutic cues thus adjusting phenotypic output leading to intra-clonal non-genetic diversity.

Cre recombinase microinjection for single-cell tracing and localised gene targeting

Tracing and manipulating cells in embryos are essential to understand development. Lipophilic dye microinjections, viral transfection and iontophoresis have been key to map the origin of the progenitor cells that form the different organs in the post-implantation mouse embryo. These techniques require advanced manipulation skills and only iontophoresis, a demanding approach of limited efficiency, has been used for single-cell labelling. Here, we perform lineage tracing and local gene ablation using cell-permeant Cre recombinase (TAT-Cre) microinjection. First, we map the fate of undifferentiated progenitors to the different heart chambers. Then, we achieve single-cell recombination by titrating the dose of TAT-Cre, which allows clonal analysis of nascent mesoderm progenitors. Finally, injecting TAT-Cre to Mycnflox/flox embryos in the primitive heart tube revealed that Mycn plays a cell-autonomous role in maintaining cardiomyocyte proliferation. This tool will help researchers identify the cell progenitors and gene networks involved in organ development, helping to understand the origin of congenital defects.

TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages

During development, regulatory factors appear in a precise order to determine cell fates over time. Consequently, to investigate complex tissue development, it is necessary to visualize and manipulate cell lineages with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here, we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labeling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation and inactivation of reporters and/or effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.

SPEED: Single-cell Pan-species atlas in the light of Ecology and Evolution for Development and Diseases

It is a challenge to efficiently integrate and present the tremendous amounts of single-cell data generated from multiple tissues of various species. Here, we create a new database named SPEED for single-cell pan-species atlas in the light of ecology and evolution for development and diseases (freely accessible at http://8.142.154.29 or http://speedatlas.net). SPEED is an online platform with 4 data modules, 7 function modules and 2 display modules. The 'Pan' module is applied for the interactive analysis of single cell sequencing datasets from 127 species, and the 'Evo', 'Devo', and 'Diz' modules provide comprehensive analysis of single-cell atlases on 18 evolution datasets, 28 development datasets, and 85 disease datasets. The 'C2C', 'G2G' and 'S2S' modules explore intercellular communications, genetic regulatory networks, and cross-species molecular evolution. The 'sSearch', 'sMarker', 'sUp', and 'sDown' modules allow users to retrieve specific data information, obtain common marker genes for cell types, freely upload, and download single-cell datasets, respectively. Two display modules ('HOME' and 'HELP') offer easier access to the SPEED database with informative statistics and detailed guidelines. All in all, SPEED is an integrated platform for single-cell RNA sequencing (scRNA-seq) and single-cell whole-genome sequencing (scWGS) datasets to assist the deep-mining and understanding of heterogeneity among cells, tissues, and species at multi-levels, angles, and orientations, as well as provide new insights into molecular mechanisms of biological development and pathogenesis.

Journey of the mouse primitive endoderm: from specification to maturation

The blastocyst is a conserved stage and distinct milestone in the development of the mammalian embryo. Blastocyst stage embryos comprise three cell lineages which arise through two sequential binary cell fate specification steps. In the first, extra-embryonic trophectoderm (TE) cells segregate from inner cell mass (ICM) cells. Subsequently, ICM cells acquire a pluripotent epiblast (Epi) or extra-embryonic primitive endoderm (PrE, also referred to as hypoblast) identity. In the mouse, nascent Epi and PrE cells emerge in a salt-and-pepper distribution in the early blastocyst and are subsequently sorted into adjacent tissue layers by the late blastocyst stage. Epi cells cluster at the interior of the ICM, while PrE cells are positioned on its surface interfacing the blastocyst cavity, where they display apicobasal polarity. As the embryo implants into the maternal uterus, cells at the periphery of the PrE epithelium, at the intersection with the TE, break away and migrate along the TE as they mature into parietal endoderm (ParE). PrE cells remaining in association with the Epi mature into visceral endoderm. In this review, we discuss our current understanding of the PrE from its specification to its maturation. This article is part of the theme issue 'Extraembryonic tissues: exploring concepts, definitions and functions across the animal kingdom'.

Quantitative fate mapping: A general framework for analyzing progenitor state dynamics via retrospective lineage barcoding

Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; whether these lineage barcodes capture the complex dynamics of progenitor states remains unclear. We introduce quantitative fate mapping, an approach to reconstruct the hierarchy, commitment times, population sizes, and commitment biases of intermediate progenitor states during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a general barcoding mutagenesis model. We validate these approaches using realistic in silico and in vitro barcoding experiments. We further establish criteria for the number of cells that must be analyzed for robust quantitative fate mapping and a progenitor state coverage statistic to assess the robustness. This work demonstrates how lineage barcodes, natural or synthetic, enable analyzing progenitor fate and dynamics long after embryonic development in any organism.

Single-cell RNA-sequencing analysis of early sea star development

Echinoderms represent a broad phylum with many tractable features to test evolutionary changes and constraints. Here, we present a single-cell RNA-sequencing analysis of early development in the sea star Patiria miniata, to complement the recent analysis of two sea urchin species. We identified 20 cell states across six developmental stages from 8 hpf to mid-gastrula stage, using the analysis of 25,703 cells. The clusters were assigned cell states based on known marker gene expression and by in situ RNA hybridization. We found that early (morula, 8-14 hpf) and late (blastula-to-mid-gastrula) cell states are transcriptionally distinct. Cells surrounding the blastopore undergo rapid cell state changes that include endomesoderm diversification. Of particular import to understanding germ cell specification is that we never see Nodal pathway members within Nanos/Vasa-positive cells in the region known to give rise to the primordial germ cells (PGCs). The results from this work contrast the results of PGC specification in the sea urchin, and the dataset presented here enables deeper comparative studies in tractable developmental models for testing a variety of developmental mechanisms.

Connecting past and present: single-cell lineage tracing

Central to the core principle of cell theory, depicting cells' history, state and fate is a fundamental goal in modern biology. By leveraging clonal analysis and single-cell RNA-seq technologies, single-cell lineage tracing provides new opportunities to interrogate both cell states and lineage histories. During the past few years, many strategies to achieve lineage tracing at single-cell resolution have been developed, and three of them (integration barcodes, polylox barcodes, and CRISPR barcodes) are noteworthy as they are amenable in experimentally tractable systems. Although the above strategies have been demonstrated in animal development and stem cell research, much care and effort are still required to implement these methods. Here we review the development of single-cell lineage tracing, major characteristics of the cell barcoding strategies, applications, as well as technical considerations and limitations, providing a guide to choose or improve the single-cell barcoding lineage tracing.

Cellular barcoding to decipher clonal dynamics in disease

Cellular barcodes are distinct DNA sequences that enable one to track specific cells across time or space. Recent advances in our ability to detect natural or synthetic cellular barcodes, paired with single-cell readouts of cell state, have markedly increased our knowledge of clonal dynamics and genealogies of the cells that compose a variety of tissues and organs. These advances hold promise to redefine our view of human disease. Here, we provide an overview of cellular barcoding approaches, discuss applications to gain new insights into disease mechanisms, and provide an outlook on future applications. We discuss unanticipated insights gained through barcoding in studies of cancer and blood cell production and describe how barcoding can be applied to a growing array of medical fields, particularly with the increasing recognition of clonal contributions in human diseases.

Organoid research on human early development and beyond

The organoid field has been developing rapidly during the last decade. Organoids for human pre-, peri- and post-implantation development have opened an avenue to study these biological processes in vitro, which have been hampered by lack of accessible research models for long term. The technologies of four fields, single cell omics sequencing, genome editing and lineage tracing, microfluidics and tissue engineering, have fueled the rapid development of the organoid field. In this review, we will discuss the organoid research on human early development as well as future directions of the organoid field combining with other powerful technologies.

Machine-learning-optimized Cas12a barcoding enables the recovery of single-cell lineages and transcriptional profiles

The development of CRISPR-based barcoding methods creates an exciting opportunity to understand cellular phylogenies. We present a compact, tunable, high-capacity Cas12a barcoding system called dual acting inverted site array (DAISY). We combined high-throughput screening and machine learning to predict and optimize the 60-bp DAISY barcode sequences. After optimization, top-performing barcodes had ∼10-fold increased capacity relative to the best random-screened designs and performed reliably across diverse cell types. DAISY barcode arrays generated ∼12 bits of entropy and ∼66,000 unique barcodes. Thus, DAISY barcodes-at a fraction of the size of Cas9 barcodes-achieved high-capacity barcoding. We coupled DAISY barcoding with single-cell RNA-seq to recover lineages and gene expression profiles from ∼47,000 human melanoma cells. A single DAISY barcode recovered up to ∼700 lineages from one parental cell. This analysis revealed heritable single-cell gene expression and potential epigenetic modulation of memory gene transcription. Overall, Cas12a DAISY barcoding is an efficient tool for investigating cell-state dynamics.

Post-gastrulation synthetic embryos generated ex utero from mouse naive ESCs

In vitro cultured stem cells with distinct developmental capacities can contribute to embryonic or extraembryonic tissues after microinjection into pre-implantation mammalian embryos. However, whether cultured stem cells can independently give rise to entire gastrulating embryo-like structures with embryonic and extraembryonic compartments remains unknown. Here, we adapt a recently established platform for prolonged ex utero growth of natural embryos to generate mouse post-gastrulation synthetic whole embryo models (sEmbryos), with both embryonic and extraembryonic compartments, starting solely from naive ESCs. This was achieved by co-aggregating non-transduced ESCs, with naive ESCs transiently expressing Cdx2 or Gata4 to promote their priming toward trophectoderm and primitive endoderm lineages, respectively. sEmbryos adequately accomplish gastrulation, advance through key developmental milestones, and develop organ progenitors within complex extraembryonic compartments similar to E8.5 stage mouse embryos. Our findings highlight the plastic potential of naive pluripotent cells to self-organize and functionally reconstitute and model the entire mammalian embryo beyond gastrulation.

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Advanced synthetic embryos (sEmbryos) self-assembled from ESCs in an ex utero setup

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Naive ESCs give rise to all embryonic and extraembryonic compartments in sEmbryos

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Post-gastrulation stem cell derived sEmbryos develop organ-specific progenitors

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Extraembryonic compartments adequately develop in post-gastrulation whole sEmbryos

The intrinsic and extrinsic effects of TET proteins during gastrulation

Mice deficient for all ten-eleven translocation (TET) genes exhibit early gastrulation lethality. However, separating cause and effect in such embryonic failure is challenging. To isolate cell-autonomous effects of TET loss, we used temporal single-cell atlases from embryos with partial or complete mutant contributions. Strikingly, when developing within a wild-type embryo, Tet-mutant cells retain near-complete differentiation potential, whereas embryos solely comprising mutant cells are defective in epiblast to ectoderm transition with degenerated mesoderm potential. We map de-repressions of early epiblast factors (e.g., Dppa4 and Gdf3) and failure to activate multiple signaling from nascent mesoderm (Lefty, FGF, and Notch) as likely cell-intrinsic drivers of TET loss phenotypes. We further suggest loss of enhancer demethylation as the underlying mechanism. Collectively, our work demonstrates an unbiased approach for defining intrinsic and extrinsic embryonic gene function based on temporal differentiation atlases and disentangles the intracellular effects of the demethylation machinery from its broader tissue-level ramifications.

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Chimeras with full or partial Tet deficiency are mapped over the course of gastrulation

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Tet-TKO cells disrupt signaling, leading to skewed whole-embryo mutant gastrulation

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Tet-TKO cells retain near-complete differentiation potential in a chimera context

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Loss of TET leads to pervasive hypermethylation and mildly perturbed gene expression

Molecular recorders to track cellular events

DNA tapes could be used to record dynamic molecular and cellular events in animals.

Specification of hematopoietic stem cells in mammalian embryos: a rare or frequent event?

Hematopoietic stem cells (HSCs) are the blood-forming stem cells thought to be responsible for supporting the blood system throughout life. Transplantability has long been the flagship assay used to define and characterize HSCs throughout ontogeny. However, it has recently become clear that many cells emerge during ontogeny that lack transplantability yet nevertheless are fated to ultimately contribute to the adult HSC pool. Here, we explore recent advances in understanding the numbers and kinetics of cells that emerge during development to support lifelong hematopoiesis; these advances are made possible by new technologies allowing interrogation of lifelong blood potential without embryo perturbation or transplantation. Illuminating the dynamics of these cells during normal development informs efforts to better understand the origins of hematologic disease and engineer HSCs from differentiating pluripotent stem cells.

Hijacking of transcriptional condensates by endogenous retroviruses

Most endogenous retroviruses (ERVs) in mammals are incapable of retrotransposition; therefore, why ERV derepression is associated with lethality during early development has been a mystery. Here, we report that rapid and selective degradation of the heterochromatin adapter protein TRIM28 triggers dissociation of transcriptional condensates from loci encoding super-enhancer (SE)-driven pluripotency genes and their association with transcribed ERV loci in murine embryonic stem cells. Knockdown of ERV RNAs or forced expression of SE-enriched transcription factors rescued condensate localization at SEs in TRIM28-degraded cells. In a biochemical reconstitution system, ERV RNA facilitated partitioning of RNA polymerase II and the Mediator coactivator into phase-separated droplets. In TRIM28 knockout mouse embryos, single-cell RNA-seq analysis revealed specific depletion of pluripotent lineages. We propose that coding and noncoding nascent RNAs, including those produced by retrotransposons, may facilitate ‘hijacking’ of transcriptional condensates in various developmental and disease contexts.

TRIM28 depletion in embryonic stem cells disconnects transcriptional condensates from super-enhancers, which is rescued by knockdown of endogenous retroviruses.

Single-cell technologies: a new lens into epigenetic regulation in development

The totipotent zygote gives rise to diverse cell types through a series of well-orchestrated regulatory mechanisms. Epigenetic modifiers play an essential, though still poorly understood, role in the transition from pluripotency towards organogenesis. However, recent advances in single-cell technologies have enabled an unprecedented, high-resolution dissection of this crucial developmental window, highlighting more cell-type-specific functions of these ubiquitous regulators. In this review, we discuss and contextualize several recent studies that explore epigenetic regulation during mouse embryogenesis, emphasizing the opportunities presented by single-cell technologies, in vivo perturbation approaches as well as advanced in vitro models to characterize dynamic developmental transitions.

Specification of the haematopoietic stem cell lineage: From blood-fated mesodermal angioblasts to haemogenic endothelium

Haematopoietic stem and progenitor cells emerge from specialized haemogenic endothelial cells in select vascular beds during embryonic development. Specification and commitment to the blood lineage, however, occur before endothelial cells are endowed with haemogenic competence, at the time of mesoderm patterning and production of endothelial cell progenitors (angioblasts). Whilst early blood cell fate specification has long been recognized, very little is known about the mechanisms that induce endothelial cell diversification and progressive acquisition of a blood identity by a subset of these cells. Here, we review the endothelial origin of the haematopoietic system and the complex developmental journey of blood-fated angioblasts. We discuss how recent technological advances will be instrumental to examine the diversity of the embryonic anatomical niches, signaling pathways and downstream epigenetic and transcriptional processes controlling endothelial cell heterogeneity and blood cell fate specification. Ultimately, this will give essential insights into the ontogeny of the cells giving rise to haematopoietic stem cells, that may aid in the development of novel strategies for their in vitro production for clinical purposes.

CoSpar identifies early cell fate biases from single-cell transcriptomic and lineage information

A goal of single-cell genome-wide profiling is to reconstruct dynamic transitions during cell differentiation, disease onset and drug response. Single-cell assays have recently been integrated with lineage tracing, a set of methods that identify cells of common ancestry to establish bona fide dynamic relationships between cell states. These integrated methods have revealed unappreciated cell dynamics, but their analysis faces recurrent challenges arising from noisy, dispersed lineage data. In this study, we developed coherent, sparse optimization (CoSpar) as a robust computational approach to infer cell dynamics from single-cell transcriptomics integrated with lineage tracing. Built on assumptions of coherence and sparsity of transition maps, CoSpar is robust to severe downsampling and dispersion of lineage data, which enables simpler experimental designs and requires less calibration. In datasets representing hematopoiesis, reprogramming and directed differentiation, CoSpar identifies early fate biases not previously detected, predicting transcription factors and receptors implicated in fate choice. Documentation and detailed examples for common experimental designs are available at https://cospar.readthedocs.io/ .

Toward the dissection of hematopoietic stem cell fates and their determinants

Hematopoietic stem cell (HSC) functions have long been difficult to study under physiological conditions. Recently, genetic in vivo approaches have been developed for lineage tracing of differentiating progeny emerging from HSC over time (output), and for high-resolution, endogenous barcoding to uncover the lineages that HSC contribute to (fate). Such fate measurements have in principle led to the recognition of three major fate groups of HSC: multilineage, myelo-erythroid-restricted, and inactive, that is, no or no known progeny, in addition to a minor group of megakaryocyte-restricted HSC. The most recent RNA-barcoding experiments have begun to directly link fate measurements with transcriptome reading in HSC clones and single HSC, which yielded insights into transcriptional signatures associated with fate patterns. Here, we discuss these findings in light of the structure of the hematopoietic differentiation hierarchy, and we provide an outlook on strategies to dissect molecular determinants of HSC fates.

Identification of the central intermediate in the extra-embryonic to embryonic endoderm transition through single-cell transcriptomics

High-resolution maps of embryonic development suggest that acquisition of cell identity is not limited to canonical germ layers but proceeds via alternative routes. Despite evidence that visceral organs are formed via embryonic and extra-embryonic trajectories, the production of organ-specific cell types in vitro focuses on the embryonic one. Here we resolve these differentiation routes using massively parallel single-cell RNA sequencing to generate datasets from FOXA2^Venus reporter mouse embryos and embryonic stem cell differentiation towards endoderm. To relate cell types in these datasets, we develop a single-parameter computational approach and identify an intermediate en route from extra-embryonic identity to embryonic endoderm, which we localize spatially in embryos at embryonic day 7.5. While there is little evidence for this cell type in embryonic stem cell differentiation, by following the extra-embryonic trajectory starting with naïve extra-embryonic endoderm stem cells we can generate embryonic gut spheroids. Exploiting developmental plasticity therefore offers alternatives to pluripotent cells and opens alternative avenues for in vitro differentiation.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

A New Generation of Lineage Tracing Dynamically Records Cell Fate Choices

Reconstructing the development of lineage relationships and cell fate mapping has been a fundamental problem in biology. Using advanced molecular biology and single-cell RNA sequencing, we have profiled transcriptomes at the single-cell level and mapped cell fates during development. Recently, CRISPR/Cas9 barcode editing for large-scale lineage tracing has been used to reconstruct the pseudotime trajectory of cells and improve lineage tracing accuracy. This review presents the progress of the latest CbLT (CRISPR-based Lineage Tracing) and discusses the current limitations and potential technical pitfalls in their application and other emerging concepts.

Interactive, integrated analysis of single-cell transcriptomic and phylogenetic data with PhyloVision

Recent advances in CRISPR-Cas9 engineering and single-cell assays have enabled the simultaneous measurement of single-cell transcriptomic and phylogenetic profiles. However, there are few computational tools enabling users to integrate and derive insight from a joint analysis of these two modalities. Here, we describe "PhyloVision": an open-source software for interactively exploring data from both modalities and for identifying and interpreting heritable gene modules whose concerted expression are associated with phylogenetic relationships. PhyloVision provides a feature-rich, interactive, and shareable web-based report for investigating these modules while also supporting several other data and meta-data exploration capabilities. We demonstrate the utility of PhyloVision using a published dataset of metastatic lung adenocarcinoma cells, whose phylogeny was resolved using a CRISPR-Cas9-based lineage-tracing system. Together, we anticipate that PhyloVision and the methods it implements will be a useful resource for scalable and intuitive data exploration for any assay that simultaneously measures cell state and lineage.

TedSim: temporal dynamics simulation of single-cell RNA sequencing data and cell division history

Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree and makes it possible to reconstruct ancestral cell types and trace the origin of each cell type. Meanwhile, trajectory inference methods are widely used to infer cell trajectories and pseudotime in a dynamic process using gene expression data of present-day cells. Here, we present TedSim (single-cell temporal dynamics simulator), which simulates the cell division events from the root cell to present-day cells, simultaneously generating two data modalities for each single cell: the lineage barcode and gene expression data. TedSim is a framework that connects the two problems: lineage tracing and trajectory inference. Using TedSim, we conducted analysis to show that (i) TedSim generates realistic gene expression and barcode data, as well as realistic relationships between these two data modalities; (ii) trajectory inference methods can recover the underlying cell state transition mechanism with balanced cell type compositions; and (iii) integrating gene expression and barcode data can provide more insights into the temporal dynamics in cell differentiation compared to using only one type of data, but better integration methods need to be developed.

Deep distributed computing to reconstruct extremely large lineage trees

Phylogeny estimation (the reconstruction of evolutionary trees) has recently been applied to CRISPR-based cell lineage tracing, allowing the developmental history of an individual tissue or organism to be inferred from a large number of mutated sequences in somatic cells. However, current computational methods are not able to construct phylogenetic trees from extremely large numbers of input sequences. Here, we present a deep distributed computing framework to comprehensively trace accurate large lineages (FRACTAL) that substantially enhances the scalability of current lineage estimation software tools. FRACTAL first reconstructs only an upstream lineage of the input sequences and recursively iterates the same produce for its downstream lineages using independent computing nodes. We demonstrate the utility of FRACTAL by reconstructing lineages from >235 million simulated sequences and from >16 million cells from a simulated experiment with a CRISPR system that accumulates mutations during cell proliferation. We also successfully applied FRACTAL to evolutionary tree reconstructions and to an experiment using error-prone PCR (EP-PCR) for large-scale sequence diversification.

Genetic mosaicism in the human brain: from lineage tracing to neuropsychiatric disorders

Genetic mosaicism is the result of the accumulation of somatic mutations in the human genome starting from the first postzygotic cell generation and continuing throughout the whole life of an individual. The rapid development of next-generation and single-cell sequencing technologies is now allowing the study of genetic mosaicism in normal tissues, revealing unprecedented insights into their clonal architecture and physiology. The somatic variant repertoire of an adult human neuron is the result of somatic mutations that accumulate in the brain by different mechanisms and at different rates during development and ageing. Non-pathogenic developmental mutations function as natural barcodes that once identified in deep bulk or single-cell sequencing can be used to retrospectively reconstruct human lineages. This approach has revealed novel insights into the clonal structure of the human brain, which is a mosaic of clones traceable to the early embryo that contribute differentially to the brain and distinct areas of the cortex. Some of the mutations happening during development, however, have a pathogenic effect and can contribute to some epileptic malformations of cortical development and autism spectrum disorder. In this Review, we discuss recent findings in the context of genetic mosaicism and their implications for brain development and disease.