Whole-organism clone tracing using single-cell sequencing

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.

Genetically engineered zebrafish as models of skeletal development and regeneration

Zebrafish (Danio rerio) are aquatic vertebrates with significant homology to their terrestrial counterparts. While zebrafish have a centuries-long track record in developmental and regenerative biology, their utility has grown exponentially with the onset of modern genetics. This is exemplified in studies focused on skeletal development and repair. Herein, the numerous contributions of zebrafish to our understanding of the basic science of cartilage, bone, tendon/ligament, and other skeletal tissues are described, with a particular focus on applications to development and regeneration. We summarize the genetic strengths that have made the zebrafish a powerful model to understand skeletal biology. We also highlight the large body of existing tools and techniques available to understand skeletal development and repair in the zebrafish and introduce emerging methods that will aid in novel discoveries in skeletal biology. Finally, we review the unique contributions of zebrafish to our understanding of regeneration and highlight diverse routes of repair in different contexts of injury. We conclude that zebrafish will continue to fill a niche of increasing breadth and depth in the study of basic cellular mechanisms of skeletal biology.

Updated Perspectives on Direct Vascular Cellular Reprogramming and Their Potential Applications in Tissue Engineered Vascular Grafts

Cardiovascular disease is a globally prevalent disease with far-reaching medical and socio-economic consequences. Although improvements in treatment pathways and revascularisation therapies have slowed disease progression, contemporary management fails to modulate the underlying atherosclerotic process and sustainably replace damaged arterial tissue. Direct cellular reprogramming is a rapidly evolving and innovative tissue regenerative approach that holds promise to restore functional vasculature and restore blood perfusion. The approach utilises cell plasticity to directly convert somatic cells to another cell fate without a pluripotent stage. In this narrative literature review, we comprehensively analyse and compare direct reprogramming protocols to generate endothelial cells, vascular smooth muscle cells and vascular progenitors. Specifically, we carefully examine the reprogramming factors, their molecular mechanisms, conversion efficacies and therapeutic benefits for each induced vascular cell. Attention is given to the application of these novel approaches with tissue engineered vascular grafts as a therapeutic and disease-modelling platform for cardiovascular diseases. We conclude with a discussion on the ethics of direct reprogramming, its current challenges, and future perspectives.

A Device for Isolation of Selected Single Adherent Cells

In recent years, extensive research has been focused on the field of single cell analysis. The isolation of single cells is the first step in this type of research. However, the techniques used for direct isolation and acquisition of single adherent cells are limited. Here, we present a method of obtaining selected single adherent cells using a separation device. Compared with other single cell isolation methods, this method has the advantages of simple operation, low cost, minimal cell damage, and preservation of cell morphology. Our methodology is, therefore, suitable for the collection of selected single adherent cells.

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.

TiDeTree: a Bayesian phylogenetic framework to estimate single-cell trees and population dynamic parameters from genetic lineage tracing data

The development of organisms and tissues is dictated by an elaborate balance between cell division, apoptosis and differentiation: the cell population dynamics. To quantify these dynamics, we propose a phylodynamic inference approach based on single-cell lineage recorder data. We developed a Bayesian phylogenetic framework-time-scaled developmental trees (TiDeTree)-that uses lineage recorder data to estimate time-scaled single-cell trees. By implementing TiDeTree within BEAST 2, we enable joint inference of the time-scaled trees and the cell population dynamics. We validated TiDeTree using simulations and showed that performance further improves when including multiple independent sources of information into the inference, such as frequencies of editing outcomes or experimental replicates. We benchmarked TiDeTree against state-of-the-art methods and show comparable performance in terms of tree topology, plus direct assessment of uncertainty and co-estimation of additional parameters. To demonstrate TiDeTree's use in practice, we analysed a public dataset containing lineage data from approximately 100 stem cell colonies. We estimated a time-scaled phylogeny for each colony; as well as the cell division and apoptosis rates underlying the growth dynamics of all colonies. We envision that TiDeTree will find broad application in the analysis of single-cell lineage tracing data, which will improve our understanding of cellular processes during development.

Mastering the use of cellular barcoding to explore cancer heterogeneity

Tumours are often composed of a multitude of malignant clones that are genomically unique, and only a few of them may have the ability to escape cancer therapy and grow as symptomatic lesions. As a result, tumours with a large degree of genomic diversity have a higher chance of leading to patient death. However, clonal fate can be driven by non-genomic features. In this context, new technologies are emerging not only to track the spatiotemporal fate of individual cells and their progeny but also to study their molecular features using various omics analysis. In particular, the recent development of cellular barcoding facilitates the labelling of tens to millions of cancer clones and enables the identification of the complex mechanisms associated with clonal fate in different microenvironments and in response to therapy. In this Review, we highlight the recent discoveries made using lentiviral-based cellular barcoding techniques, namely genetic and optical barcoding. We also emphasize the strengths and limitations of each of these technologies and discuss some of the key concepts that must be taken into consideration when one is designing barcoding experiments. Finally, we suggest new directions to further improve the use of these technologies in cancer research.

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.

Recent advances in understanding cell types during human gastrulation

Gastrulation is a fundamental process during embryonic development, conserved across all multicellular animals [1]. In the majority of metazoans, gastrulation is characterised by large scale morphogenetic remodeling, leading to the conversion of an early pluripotent embryonic cell layer into the three primary 'germ layers': an outer ectoderm, inner endoderm and intervening mesoderm layer. The morphogenesis of these three layers of cells is closely coordinated with cellular diversification, laying the foundation for the generation of the hundreds of distinct specialized cell types in the animal body. The process of gastrulation has for a long time attracted tremendous attention in a broad range of experimental systems ranging from sponges to mice. In humans the process of gastrulation starts approximately 14 days after fertilization and continues for slightly over a week. However our understanding of this important process, as it pertains to human, is limited. Donations of human fetal material at these early stages are exceptionally rare, making it nearly impossible to study human gastrulation directly. Therefore, our understanding of human gastrulation is predominantly derived from animal models such as the mouse [2,3] and from studies of limited collections of fixed whole samples and histological sections of human gastrulae [4-7], some of which date back to over a century ago. More recently we have been gaining valuable molecular insights into human gastrulation using in vitro models of hESCs [8-12] and increasingly, in vitro cultured human and non-human primate embryos [13-16]. However, while methods have been developed to culture human embryos into this stage (and probably beyond), current ethical standards prohibit the culture of human embryos past 14 days again limiting our ability to experimentally probe human gastrulation. This review discusses recent molecular insights from the study of a rare CS 7 human gastrula obtained as a live sample and raises several questions arising from this recent study that it will be interesting to address in the future using emerging models of human gastrulation.

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.

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.

Origin and function of activated fibroblast states during zebrafish heart regeneration

The adult zebrafish heart has a high capacity for regeneration following injury. However, the composition of the regenerative niche has remained largely elusive. Here, we dissected the diversity of activated cell states in the regenerating zebrafish heart based on single-cell transcriptomics and spatiotemporal analysis. We observed the emergence of several transient cell states with fibroblast characteristics following injury, and we outlined the proregenerative function of collagen-12-expressing fibroblasts. To understand the cascade of events leading to heart regeneration, we determined the origin of these cell states by high-throughput lineage tracing. We found that activated fibroblasts were derived from two separate sources: the epicardium and the endocardium. Mechanistically, we determined Wnt signalling as a regulator of the endocardial fibroblast response. In summary, our work identifies specialized activated fibroblast cell states that contribute to heart regeneration, thereby opening up possible approaches to modulating the regenerative capacity of the vertebrate heart.

Single-cell RNA sequencing and spatiotemporal analysis of the regenerating zebrafish heart identify transient proregenerative fibroblast-like cells that are derived from the epicardium and the endocardium. Wnt signalling regulates the endocardial fibroblast response.

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/ .

Hematopoietic Stem and Progenitor Cells (HSPCs) and Hematopoietic Microenvironment: Molecular and Bioinformatic Studies of the Zebrafish Models

Hematopoietic stem cells (HSCs) reside in a specialized microenvironment in a peculiar anatomic location which regulates the maintenance of stem cells and controls its functions. Recent scientific progress in experimental technologies have enabled the specific detection of epigenetic factors responsible for the maintenance and quiescence of the hematopoietic niche, which has improved our knowledge of regulatory mechanisms. The aberrant role of RNA-binding proteins and their impact on the disruption of stem cell biology have been reported by a number of recent studies. Despite recent modernization in hematopoietic microenvironment research avenues, our comprehension of the signaling mechanisms and interactive pathways responsible for integration of the hematopoietic niche is still limited. In the past few decades, zebrafish usage with regards to exploratory studies of the hematopoietic niche has expanded our knowledge for deeper understanding of novel cellular interactions. This review provides an update on the functional roles of different genetic and epigenetic factors and molecular signaling events at different sections of the hematopoietic microenvironment. The explorations of different molecular approaches and interventions of latest web-based tools being used are also outlined. This will help us to get more mechanistic insights and develop therapeutic options for the malignancies.

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.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

Developmental dynamics of two bipotent thymic epithelial progenitor types

T cell development in the thymus is essential for cellular immunity and depends on the organotypic thymic epithelial microenvironment. In comparison with other organs, the size and cellular composition of the thymus are unusually dynamic, as exemplified by rapid growth and high T cell output during early stages of development, followed by a gradual loss of functional thymic epithelial cells and diminished naive T cell production with age1-10. Single-cell RNA sequencing (scRNA-seq) has uncovered an unexpected heterogeneity of cell types in the thymic epithelium of young and aged adult mice11-18; however, the identities and developmental dynamics of putative pre- and postnatal epithelial progenitors have remained unresolved1,12,16,17,19-27. Here we combine scRNA-seq and a new CRISPR-Cas9-based cellular barcoding system in mice to determine qualitative and quantitative changes in the thymic epithelium over time. This dual approach enabled us to identify two principal progenitor populations: an early bipotent progenitor type biased towards cortical epithelium and a postnatal bipotent progenitor population biased towards medullary epithelium. We further demonstrate that continuous autocrine provision of Fgf7 leads to sustained expansion of thymic microenvironments without exhausting the epithelial progenitor pools, suggesting a strategy to modulate the extent of thymopoietic activity.

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.

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.

Single cell lineage reconstruction using distance-based algorithms and the R package, DCLEAR

Background

DCLEAR is an R package used for single cell lineage reconstruction. The advances of CRISPR-based gene editing technologies have enabled the prediction of cell lineage trees based on observed edited barcodes from each cell. However, the performance of existing reconstruction methods of cell lineage trees was not accessed until recently. In response to this problem, the Allen Institute hosted the Cell Lineage Reconstruction Dream Challenge in 2020 to crowdsource relevant knowledge from across the world. Our team won sub-challenges 2 and 3 in the challenge competition.

Results

The DCLEAR package contained the R codes, which was submitted in response to sub-challenges 2 and 3. Our method consists of two steps: (1) distance matrix estimation and (2) the tree reconstruction from the distance matrix. We proposed two novel methods for distance matrix estimation as outlined in the DCLEAR package. Using our method, we find that two of the more sophisticated distance methods display a substantially improved level of performance compared to the traditional Hamming distance method. DCLEAR is open source and freely available from R CRAN and from under the GNU General Public License, version 3.

Conclusions

DCLEAR is a powerful resource for single cell lineage reconstruction.

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.

Characterization of Pipefish Immune Cell Populations Through Single-Cell Transcriptomics

Teleost adaptive immune systems have evolved with more flexibility than previously assumed. A particularly enigmatic system to address immune system modifications in the evolutionary past is represented by the Syngnathids, the family of pipefishes, seahorses and seadragons. These small fishes with their unique male pregnancy have lost the spleen as an important immune organ as well as a functional major histocompatibility class II (MHC II) pathway. How these evolutionary changes have impacted immune cell population dynamics have up to this point remained unexplored. Here, we present the first immune cell repertoire characterization of a syngnathid fish (Syngnathus typhle) using single-cell transcriptomics. Gene expression profiles of individual cells extracted from blood and head-kidney clustered in twelve putative cell populations with eight belonging to those with immune function. Upregulated cell marker genes identified in humans and teleosts were used to define cell clusters. While the suggested loss of CD4+ T-cells accompanied the loss of the MHC II pathway was supported, the upregulation of specific subtype markers within the T-cell cluster indicates subpopulations of regulatory T-cells (il2rb) and cytotoxic T-cells (gzma). Utilizing single-cell RNA sequencing this report is the first to characterize immune cell populations in syngnathids and provides a valuable foundation for future cellular classification and experimental work within the lineage.

Engineering Brain Organoids: Toward Mature Neural Circuitry with an Intact Cytoarchitecture

The emergence of brain organoids as a model system has been a tremendously exciting development in the field of neuroscience. Brain organoids are a gateway to exploring the intricacies of human-specific neurogenesis that have so far eluded the neuroscience community. Regardless, current culture methods have a long way to go in terms of accuracy and reproducibility. To perfectly mimic the human brain, we need to recapitulate the complex in vivo context of the human fetal brain and achieve mature neural circuitry with an intact cytoarchitecture. In this review, we explore the major challenges facing the current brain organoid systems, potential technical breakthroughs to advance brain organoid techniques up to levels similar to an in vivo human developing brain, and the future prospects of this technology.

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.

Temporal signaling, population control, and information processing through chromatin-mediated gene regulation

Chromatin regulation is a key pathway cells use to regulate gene expression in response to temporal stimuli, and is becoming widely used as a platform for synthetic biology applications. Here, we build a mathematical framework for analyzing the response of genetic circuits containing chromatin regulators to temporal signals in mammalian cell populations. Chromatin regulators can silence genes in an all-or-none fashion at the single-cell level, with individual cells stochastically transitioning between active, reversibly silent, and irreversibly silent gene states at constant rates over time. We integrate this mode of regulation with classical gene regulatory motifs, such as autoregulatory and incoherent feedforward loops, to determine the types of responses achievable with duration-dependent signaling. We demonstrate that repressive regulators without long-term epigenetic memory can filter out high frequency noise, and as part of an autoregulatory loop can precisely tune the fraction of cells in a population that expresses a gene of interest. Additionally, we find that repressive regulators with epigenetic memory can sum up and encode the total duration of their recruitment in the fraction of cells irreversibly silenced and, when included in a feed forward loop, enable perfect adaptation. Last, we use an information theoretic approach to show that all-or-none stochastic silencing can be used by populations to transmit information reliably and with high fidelity even in very simple genetic circuits. Altogether, we show that chromatin-mediated gene control enables a repertoire of complex cell population responses to temporal signals and can transmit higher information levels than previously measured in gene regulation.

Re-building limbs, one cell at a time

New techniques for visualizing and interrogating single cells hold the key to unlocking the underlying mechanisms of salamander limb regeneration.

Spatial components of molecular tissue biology

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics.

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.

RNA-Seq of Single Fish Cells - Seeking Out the Leukocytes Mediating Immunity in Teleost Fishes

The immune system is a complex and sophisticated biological system, spanning multiple levels of complexity, from the molecular level to that of tissue. Our current understanding of its function and complexity, of the heterogeneity of leukocytes, is a result of decades of concentrated efforts to delineate cellular markers using conventional methods of antibody screening and antigen identification. In mammalian models, this led to in-depth understanding of individual leukocyte subsets, their phenotypes, and their roles in health and disease. The field was further propelled forward by the development of single-cell (sc) RNA-seq technologies, offering an even broader and more integrated view of how cells work together to generate a particular response. Consequently, the adoption of scRNA-seq revealed the unexpected plasticity and heterogeneity of leukocyte populations and shifted several long-standing paradigms of immunology. This review article highlights the unprecedented opportunities offered by scRNA-seq technology to unveil the individual contributions of leukocyte subsets and their crosstalk in generating the overall immune responses in bony fishes. Single-cell transcriptomics allow identifying unseen relationships, and formulating novel hypotheses tailored for teleost species, without the need to rely on the limited number of fish-specific antibodies and pre-selected markers. Several recent studies on single-cell transcriptomes of fish have already identified previously unnoticed expression signatures and provided astonishing insights into the diversity of teleost leukocytes and the evolution of vertebrate immunity. Without a doubt, scRNA-seq in tandem with bioinformatics tools and state-of-the-art methods, will facilitate studying the teleost immune system by not only defining key markers, but also teaching us about lymphoid tissue organization, development/differentiation, cell-cell interactions, antigen receptor repertoires, states of health and disease, all across time and space in fishes. These advances will invite more researchers to develop the tools necessary to explore the immunology of fishes, which remain non-conventional animal models from which we have much to learn.

Single-cell-resolved dynamics of chromatin architecture delineate cell and regulatory states in zebrafish embryos

DNA accessibility of cis-regulatory elements (CREs) dictates transcriptional activity and drives cell differentiation during development. While many genes regulating embryonic development have been identified, the underlying CRE dynamics controlling their expression remain largely uncharacterized. To address this, we produced a multimodal resource and genomic regulatory map for the zebrafish community, which integrates single-cell combinatorial indexing assay for transposase-accessible chromatin with high-throughput sequencing (sci-ATAC-seq) with bulk histone PTMs and Hi-C data to achieve a genome-wide classification of the regulatory architecture determining transcriptional activity in the 24-h post-fertilization (hpf) embryo. We characterized the genome-wide chromatin architecture at bulk and single-cell resolution, applying sci-ATAC-seq on whole 24-hpf stage zebrafish embryos, generating accessibility profiles for ∼23,000 single nuclei. We developed a genome segmentation method, ScregSeg (single-cell regulatory landscape segmentation), for defining regulatory programs, and candidate CREs, specific to one or more cell types. We integrated the ScregSeg output with bulk measurements for histone post-translational modifications and 3D genome organization and identified new regulatory principles between chromatin modalities prevalent during zebrafish development. Sci-ATAC-seq profiling of npas4l/cloche mutant embryos identified novel cellular roles for this hematovascular transcriptional master regulator and suggests an intricate mechanism regulating its expression. Our work defines regulatory architecture and principles in the zebrafish embryo and establishes a resource of cell-type-specific genome-wide regulatory annotations and candidate CREs, providing a valuable open resource for genomics, developmental, molecular, and computational biology.

Towards Tabula Gallus

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

From Cell States to Cell Fates: How Cell Proliferation and Neuronal Differentiation Are Coordinated During Embryonic Development

The central nervous system (CNS) exhibits an extraordinary diversity of neurons, with the right cell types and proportions at the appropriate sites. Thus, to produce brains with specific size and cell composition, the rates of proliferation and differentiation must be tightly coordinated and balanced during development. Early on, proliferation dominates; later on, the growth rate almost ceases as more cells differentiate and exit the cell cycle. Generation of cell diversity and morphogenesis takes place concomitantly. In the vertebrate brain, this results in dramatic changes in the position of progenitor cells and their neuronal derivatives, whereas in the spinal cord morphogenetic changes are not so important because the structure mainly grows by increasing its volume. Morphogenesis is under control of specific genetic programs that coordinately unfold over time; however, little is known about how they operate and impact in the pools of progenitor cells in the CNS. Thus, the spatiotemporal coordination of these processes is fundamental for generating functional neuronal networks. Some key aims in developmental neurobiology are to determine how cell diversity arises from pluripotent progenitor cells, and how the progenitor potential changes upon time. In this review, we will share our view on how the advance of new technologies provides novel data that challenge some of the current hypothesis. We will cover some of the latest studies on cell lineage tracing and clonal analyses addressing the role of distinct progenitor cell division modes in balancing the rate of proliferation and differentiation during brain morphogenesis. We will discuss different hypothesis proposed to explain how progenitor cell diversity is generated and how they challenged prevailing concepts and raised new questions.

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.

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.

Evolving features of human cortical development and the emerging roles of non-coding RNAs in neural progenitor cell diversity and function

The human cerebral cortex is a uniquely complex structure encompassing an unparalleled diversity of neuronal types and subtypes. These arise during development through a series of evolutionary conserved processes, such as progenitor cell proliferation, migration and differentiation, incorporating human-associated adaptations including a protracted neurogenesis and the emergence of novel highly heterogeneous progenitor populations. Disentangling the unique features of human cortical development involves elucidation of the intricate developmental cell transitions orchestrated by progressive molecular events. Crucially, developmental timing controls the fine balance between cell cycle progression/exit and the neurogenic competence of precursor cells, which undergo morphological transitions coupled to transcriptome-defined temporal states. Recent advances in bulk and single-cell transcriptomic technologies suggest that alongside protein-coding genes, non-coding RNAs exert important regulatory roles in these processes. Interestingly, a considerable number of novel long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have appeared in human and non-human primates suggesting an evolutionary role in shaping cortical development. Here, we present an overview of human cortical development and highlight the marked diversification and complexity of human neuronal progenitors. We further discuss how lncRNAs and miRNAs constitute critical components of the extended epigenetic regulatory network defining intermediate states of progenitors and controlling cell cycle dynamics and fate choices with spatiotemporal precision, during human neurodevelopment.

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.

Direct neuronal reprogramming: Fast forward from new concepts toward therapeutic approaches

Differentiated cells have long been considered fixed in their identity. However, about 20 years ago, the first direct conversion of glial cells into neurons in vitro opened the field of "direct neuronal reprogramming." Since then, neuronal reprogramming has achieved the generation of fully functional, mature neurons with remarkable efficiency, even in diseased brain environments. Beyond their clinical implications, these discoveries provided basic insights into crucial mechanisms underlying conversion of specific cell types into neurons and maintenance of neuronal identity. Here we discuss such principles, including the importance of the starter cell for shaping the outcome of neuronal reprogramming. We further highlight technical concerns for in vivo reprogramming and propose a code of conduct to avoid artifacts and pitfalls. We end by pointing out next challenges for development of less invasive cell replacement therapies for humans.

High throughput screening of novel AAV capsids identifies variants for transduction of adult NSCs within the subventricular zone

The adult mammalian brain entails a reservoir of neural stem cells (NSCs) generating glial cells and neurons. However, NSCs become increasingly quiescent with age, which hampers their regenerative capacity. New means are therefore required to genetically modify adult NSCs for re-enabling endogenous brain repair. Recombinant adeno-associated viruses (AAVs) are ideal gene-therapy vectors due to an excellent safety profile and high transduction efficiency. We thus conducted a high-throughput screening of 177 intraventricularly injected barcoded AAV variants profiled by RNA sequencing. Quantification of barcoded AAV mRNAs identified two synthetic capsids, peptide-modified derivative of wild-type AAV9 (AAV9_A2) and peptide-modified derivative of wild-type AAV1 (AAV1_P5), both of which transduce active and quiescent NSCs. Further optimization of AAV1_P5 by judicious selection of the promoter and dose of injected viral genomes enabled labeling of 30%–60% of the NSC compartment, which was validated by fluorescence-activated cell sorting (FACS) analyses and single-cell RNA sequencing. Importantly, transduced NSCs readily produced neurons. The present study identifies AAV variants with a high regional tropism toward the ventricular-subventricular zone (v-SVZ) with high efficiency in targeting adult NSCs, thereby paving the way for preclinical testing of regenerative gene therapy.

Evolution of metastasis: new tools and insights

Metastasis is an evolutionary process occurring across multiple organs and timescales. Due to its continuous and dynamic nature, this multifaceted process has been challenging to investigate and remains incompletely understood, in part due to the lack of tools capable of probing genomic evolution at high enough resolution. However, technological advances in genetic sequencing and editing have provided new and powerful methods to refine our understanding of the complex series of events that lead to metastatic dissemination. In this review, we summarize the latest genetic and lineage-tracing approaches developed to unravel the genetic evolution of metastasis. The findings that have emerged have enhanced our comprehension of the mechanistic trajectories and timescales of metastasis and could provide new strategies for therapy.

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.

Cloning and Embryo Splitting in Mammalians: Brief History, Methods, and Achievements

Embryo splitting is one of the newest developed methods in reproductive biotechnology. In this method, after splitting embryos in 2-, 4-, and even 8-cell stages, every single blastomere can be developed separately, but the embryos are genetically identical. Embryo splitting, as an approach in reproductive cloning, is extensively employed in reproductive medicine studies, such as investigating human diseases, treating sterility, embryo donation, and gene therapy. In the present study, cloning in mammalians and cloning approaches are briefly reviewed. In addition, embryo splitting and the methods commonly used in embryo splitting and recent achievements in this field, as well as the applications of embryo splitting into livestock species, primate animals, and humans, are outlined. Finally, a perspective of embryo splitting is provided as the conclusion.

Resistance to inflammation underlies enhanced fitness in clonal hematopoiesis

[Figure: see text].

Advanced Technologies for Local Neural Circuits in the Cerebral Cortex

The neural network in the brain can be viewed as an integrated system assembled from a large number of local neural circuits specialized for particular brain functions. Activities of neurons in local neural circuits are thought to be organized both spatially and temporally under the rules optimized for their roles in information processing. It is well perceived that different areas of the mammalian neocortex have specific cognitive functions and distinct computational properties. However, the organizational principles of the local neural circuits in different cortical regions have not yet been clarified. Therefore, new research principles and related neuro-technologies that enable efficient and precise recording of large-scale neuronal activities and synaptic connections are necessary. Innovative technologies for structural analysis, including tissue clearing and expansion microscopy, have enabled super resolution imaging of the neural circuits containing thousands of neurons at a single synapse resolution. The imaging resolution and volume achieved by new technologies are beyond the limits of conventional light or electron microscopic methods. Progress in genome editing and related technologies has made it possible to label and manipulate specific cell types and discriminate activities of multiple cell types. These technologies will provide a breakthrough for multiscale analysis of the structure and function of local neural circuits. This review summarizes the basic concepts and practical applications of the emerging technologies and new insight into local neural circuits obtained by these technologies.

Characterization of the Zebrafish Cell Landscape at Single-Cell Resolution

Zebrafish have been found to be a premier model organism in biological and regeneration research. However, the comprehensive cell compositions and molecular dynamics during tissue regeneration in zebrafish remain poorly understood. Here, we utilized Microwell-seq to analyze more than 250,000 single cells covering major zebrafish cell types and constructed a systematic zebrafish cell landscape. We revealed single-cell compositions for 18 zebrafish tissue types covering both embryo and adult stages. Single-cell mapping of caudal fin regeneration revealed a unique characteristic of blastema population and key genetic regulation involved in zebrafish tissue repair. Overall, our single-cell datasets demonstrate the utility of zebrafish cell landscape resources in various fields of biological research.

Defining cell types and lineage in the Drosophila midgut using single cell transcriptomics

The Drosophila midgut has emerged in recent years as a model system to study stem cell renewal and differentiation and tissue homeostasis. Histological, genetic and gene expression studies have provided a wealth of information on gut cell types, regionalization, genes and pathways involved in cell proliferation and differentiation, stem cell renewal, and responses to changes in environmental factors such as the microbiota and nutrients. Here, we review the contribution of single cell transcriptomic methods to our understanding of gut cell type diversity, lineage and behavior.

Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states

Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics.

Strategies for genetic manipulation of adult stem cell-derived organoids

Organoid technology allows the expansion of primary epithelial cells from normal and diseased tissues, providing a unique model for human (patho)biology. In a three-dimensional environment, adult stem cells self-organize and differentiate to gain tissue-specific features. Accessibility to genetic manipulation enables the investigation of the molecular mechanisms underlying cell fate regulation, cell differentiation and cell interactions. In recent years, powerful methodologies using lentiviral transgenesis, CRISPR/Cas9 gene editing, and single-cell readouts have been developed to study gene function and carry out genetic screens in organoids. However, the multicellularity and dynamic nature of stem cell-derived organoids also present challenges for genetic experimentation. In this review, we focus on adult gastrointestinal organoids and summarize the state-of-the-art protocols for successful transgenesis. We provide an outlook on emerging genetic techniques that could further increase the applicability of organoids and enhance the potential of organoid-based techniques to deepen our understanding of gene function in tissue biology.

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.