Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo

Spatio-temporal mRNA tracking in the early zebrafish embryo

Early stages of embryogenesis depend on subcellular localization and transport of maternal mRNA. However, systematic analysis of these processes is hindered by a lack of spatio-temporal information in single-cell RNA sequencing. Here, we combine spatially-resolved transcriptomics and single-cell RNA labeling to perform a spatio-temporal analysis of the transcriptome during early zebrafish development. We measure spatial localization of mRNA molecules within the one-cell stage embryo, which allows us to identify a class of mRNAs that are specifically localized at an extraembryonic position, the vegetal pole. Furthermore, we establish a method for high-throughput single-cell RNA labeling in early zebrafish embryos, which enables us to follow the fate of individual maternal transcripts until gastrulation. This approach reveals that many localized transcripts are specifically transported to the primordial germ cells. Finally, we acquire spatial transcriptomes of two xenopus species and compare evolutionary conservation of localized genes as well as enriched sequence motifs.

The master transcription factor SOX2, mutated in anophthalmia/microphthalmia, is post-transcriptionally regulated by the conserved RNA-binding protein RBM24 in vertebrate eye development

Mutations in the key transcription factor, SOX2, alone account for 20% of anophthalmia (no eye) and microphthalmia (small eye) birth defects in humans-yet its regulation is not well understood, especially on the post-transcription level. We report the unprecedented finding that the conserved RNA-binding motif protein, RBM24, positively controls Sox2 mRNA stability and is necessary for optimal SOX2 mRNA and protein levels in development, perturbation of which causes ocular defects, including microphthalmia and anophthalmia. RNA immunoprecipitation assay indicates that RBM24 protein interacts with Sox2 mRNA in mouse embryonic eye tissue. and electrophoretic mobility shift assay shows that RBM24 directly binds to the Sox2 mRNA 3'UTR, which is dependent on AU-rich elements (ARE) present in the Sox2 mRNA 3'UTR. Further, we demonstrate that Sox2 3'UTR AREs are necessary for RBM24-based elevation of Sox2 mRNA half-life. We find that this novel RBM24-Sox2 regulatory module is essential for early eye development in vertebrates. We show that Rbm24-targeted deletion using a constitutive CMV-driven Cre in mouse, and rbm24a-CRISPR/Cas9-targeted mutation or morpholino knockdown in zebrafish, results in Sox2 downregulation and causes the developmental defects anophthalmia or microphthalmia, similar to human SOX2-deficiency defects. We further show that Rbm24 deficiency leads to apoptotic defects in mouse ocular tissue and downregulation of eye development markers Lhx2, Pax6, Jag1, E-cadherin and gamma-crystallins. These data highlight the exquisite specificity that conserved RNA-binding proteins like RBM24 mediate in the post-transcriptional control of key transcription factors, namely, SOX2, associated with organogenesis and human developmental defects.

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

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

The many faces of cancer evolution

Cancer cells acquire genotypic and phenotypic changes over the course of the disease. A minority of these changes enhance cell fitness, allowing a tumor to evolve and overcome environmental constraints and treatment. Cancer evolution is driven by diverse processes governed by different rules, such as discrete and irreversible genetic variants and continuous and reversible plastic reprogramming. In this perspective, we explore the role of cell plasticity in tumor evolution through specific examples. We discuss epigenetic and transcriptional reprogramming in "disease progression" of solid tumors, through the lens of the epithelial-to-mesenchymal transition, and "treatment resistance", in the context endocrine therapy in hormone-driven cancers. These examples offer a paradigm of the features and challenges of cell plastic evolution, and we investigate how recent technological advances can address these challenges. Cancer evolution is a multi-faceted process, whose understanding and harnessing will require an equally diverse prism of perspectives and approaches.

A comprehensive survey of developmental programs reveals a dearth of tree-like lineage graphs and ubiquitous regeneration

Background

Multicellular organisms are characterized by a wide diversity of forms and complexity despite a restricted set of key molecules and mechanisms at the base of organismal development. Development combines three basic processes—asymmetric cell division, signaling, and gene regulation—in a multitude of ways to create this overwhelming diversity of multicellular life forms. Here, we use a generative model to test the limits to which such processes can be combined to generate multiple differentiation paths during development, and attempt to chart the diversity of multicellular organisms generated.

Results

We sample millions of biologically feasible developmental schemes, allowing us to comment on the statistical properties of cell differentiation trajectories they produce. We characterize model-generated “organisms” using the graph topology of their cell type lineage maps. Remarkably, tree-type lineage differentiation maps are the rarest in our data. Additionally, a majority of the “organisms” generated by our model appear to be endowed with the ability to regenerate using pluripotent cells.

Conclusions

Our results indicate that, in contrast to common views, cell type lineage graphs are unlikely to be tree-like. Instead, they are more likely to be directed acyclic graphs, with multiple lineages converging on the same terminal cell type. Furthermore, the high incidence of pluripotent cells in model-generated organisms stands in line with the long-standing hypothesis that whole body regeneration is an epiphenomenon of development. We discuss experimentally testable predictions of our model and some ways to adapt the generative framework to test additional hypotheses about general features of development.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12915-021-01013-4).

CloneSeq: A highly sensitive analysis platform for the characterization of 3D-cultured single-cell-derived clones

Single-cell assays have revealed the importance of heterogeneity in many biological systems. However, limited sensitivity is a major hurdle for uncovering cellular variation. To overcome it, we developed CloneSeq, combining clonal expansion inside 3D hydrogel spheres and droplet-based RNA sequencing (RNA-seq). We show that clonal cells maintain similar transcriptional profiles and cell states. CloneSeq of lung cancer cells revealed cancer-specific subpopulations, including cancer stem-like cells, that were not revealed by scRNA-seq. Clonal expansion within 3D soft microenvironments supported cellular stemness of embryonic stem cells (ESCs) even without pluripotent media, and it improved epigenetic reprogramming efficiency of mouse embryonic fibroblasts. CloneSeq of ESCs revealed that the differentiation decision is made early during Oct4 downregulation and is maintained during early clonal expansion. Together, we show CloneSeq can be adapted to different biological systems to discover rare subpopulations by leveraging the enhanced sensitivity within clones.

Mapping single-cell atlases throughout Metazoa unravels cell type evolution

Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs. Previously, we introduced the self-assembling manifold (SAM) algorithm to robustly reconstruct manifolds from single-cell data (Tarashansky et al., 2019). Here, we build on SAM to map cell atlas manifolds across species. This new method, SAMap, identifies homologous cell types with shared expression programs across distant species within phyla, even in complex examples where homologous tissues emerge from distinct germ layers. SAMap also finds many genes with more similar expression to their paralogs than their orthologs, suggesting paralog substitution may be more common in evolution than previously appreciated. Lastly, comparing species across animal phyla, spanning sponge to mouse, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.

Single-cell transcriptomics of human embryos identifies multiple sympathoblast lineages with potential implications for neuroblastoma origin

Characterization of the progression of cellular states during human embryogenesis can provide insights into the origin of pediatric diseases. We examined the transcriptional states of neural crest- and mesoderm-derived lineages differentiating into adrenal glands, kidneys, endothelium and hematopoietic tissue between post-conception weeks 6 and 14 of human development. Our results reveal transitions connecting the intermediate mesoderm and progenitors of organ primordia, the hematopoietic system and endothelial subtypes. Unexpectedly, by using a combination of single-cell transcriptomics and lineage tracing, we found that intra-adrenal sympathoblasts at that stage are directly derived from nerve-associated Schwann cell precursors, similarly to local chromaffin cells, whereas the majority of extra-adrenal sympathoblasts arise from the migratory neural crest. In humans, this process persists during several weeks of development within the large intra-adrenal ganglia-like structures, which may also serve as reservoirs of originating cells in neuroblastoma.

Quantifying the effect of experimental perturbations at single-cell resolution

Current methods for comparing single-cell RNA sequencing datasets collected in multiple conditions focus on discrete regions of the transcriptional state space, such as clusters of cells. Here we quantify the effects of perturbations at the single-cell level using a continuous measure of the effect of a perturbation across the transcriptomic space. We describe this space as a manifold and develop a relative likelihood estimate of observing each cell in each of the experimental conditions using graph signal processing. This likelihood estimate can be used to identify cell populations specifically affected by a perturbation. We also develop vertex frequency clustering to extract populations of affected cells at the level of granularity that matches the perturbation response. The accuracy of our algorithm at identifying clusters of cells that are enriched or depleted in each condition is, on average, 57% higher than the next-best-performing algorithm tested. Gene signatures derived from these clusters are more accurate than those of six alternative algorithms in ground truth comparisons.

Bayesian inference of gene expression states from single-cell RNA-seq data

Despite substantial progress in single-cell RNA-seq (scRNA-seq) data analysis methods, there is still little agreement on how to best normalize such data. Starting from the basic requirements that inferred expression states should correct for both biological and measurement sampling noise and that changes in expression should be measured in terms of fold changes, we here derive a Bayesian normalization procedure called Sanity (SAmpling-Noise-corrected Inference of Transcription activitY) from first principles. Sanity estimates expression values and associated error bars directly from raw unique molecular identifier (UMI) counts without any tunable parameters. Using simulated and real scRNA-seq datasets, we show that Sanity outperforms other normalization methods on downstream tasks, such as finding nearest-neighbor cells and clustering cells into subtypes. Moreover, we show that by systematically overestimating the expression variability of genes with low expression and by introducing spurious correlations through mapping the data to a lower-dimensional representation, other methods yield severely distorted pictures of the data.

The Cellular and Physiological Basis for Lung Repair and Regeneration: Past, Present, and Future

The respiratory system, which includes the trachea, airways, and distal alveoli, is a complex multi-cellular organ that intimately links with the cardiovascular system to accomplish gas exchange. In this review and as members of the NIH/NHLBI-supported Progenitor Cell Translational Consortium, we discuss key aspects of lung repair and regeneration. We focus on the cellular compositions within functional niches, cell-cell signaling in homeostatic health, the responses to injury, and new methods to study lung repair and regeneration. We also provide future directions for an improved understanding of the cell biology of the respiratory system, as well as new therapeutic avenues.

Single-cell profiling for advancing birth defects research and prevention

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

Neural crest multipotency and specification: power and limits of single cell transcriptomic approaches

The neural crest is a unique population of multipotent cells forming in vertebrate embryos. Their vast cell fate potential enables the generation of a diverse array of differentiated cell types in vivo. These include, among others, connective tissue, cartilage and bone of the face and skull, neurons and glia of the peripheral nervous system (including enteric nervous system), and melanocytes. Following migration, these derivatives extensively populate multiple germ layers. Within the competent neural border ectoderm, an area located at the junction between the neural and non-neural ectoderm during embryonic development, neural crest cells form in response to a series of inductive secreted cues including BMP, Wnt, and FGF signals. As cells become progressively specified, they express transcriptional modules conducive with their stage of fate determination or cell state. Those sequential states include the neural border state, the premigratory neural crest state, the epithelium-to-mesenchyme transitional state, and the migratory state to end with post-migratory and differentiation states. However, despite the extensive knowledge accumulated over 150 years of neural crest biology, many key questions remain open, in particular the timing of neural crest lineage determination, the control of potency during early developmental stages, and the lineage relationships between different subpopulations of neural crest cells. In this review, we discuss the recent advances in understanding early neural crest formation using cutting-edge high-throughput single cell sequencing approaches. We will discuss how this new transcriptomic data, from 2017 to 2021, has advanced our knowledge of the steps in neural crest cell lineage commitment and specification, the mechanisms driving multipotency, and diversification. We will then discuss the questions that remain to be resolved and how these approaches may continue to unveil the biology of these fascinating cells.

Mapping the regulatory landscape of auditory hair cells from single-cell multi-omics data

Auditory hair cells transduce sound to the brain and in mammals these cells reside together with supporting cells in the sensory epithelium of the cochlea, called the organ of Corti. To establish the organ's delicate function during development and differentiation, spatiotemporal gene expression is strictly controlled by chromatin accessibility and cell type-specific transcription factors, jointly representing the regulatory landscape. Bulk-sequencing technology and cellular heterogeneity obscured investigations on the interplay between transcription factors and chromatin accessibility in inner ear development. To study the formation of the regulatory landscape in hair cells, we collected single-cell chromatin accessibility profiles accompanied by single-cell RNA data from genetically labeled murine hair cells and supporting cells after birth. Using an integrative approach, we predicted cell type-specific activating and repressing functions of developmental transcription factors. Furthermore, by integrating gene expression and chromatin accessibility datasets, we reconstructed gene regulatory networks. Then, using a comparative approach, 20 hair cell-specific activators and repressors, including putative downstream target genes, were identified. Clustering of target genes resolved groups of related transcription factors and was utilized to infer their developmental functions. Finally, the heterogeneity in the single-cell data allowed us to spatially reconstruct transcriptional as well as chromatin accessibility trajectories, indicating that gradual changes in the chromatin accessibility landscape were lagging behind the transcriptional identity of hair cells along the organ's longitudinal axis. Overall, this study provides a strategy to spatially reconstruct the formation of a lineage specific regulatory landscape using a single-cell multi-omics approach.

ACME dissociation: a versatile cell fixation-dissociation method for single-cell transcriptomics

Single-cell sequencing technologies are revolutionizing biology, but they are limited by the need to dissociate live samples. Here, we present ACME (ACetic-MEthanol), a dissociation approach for single-cell transcriptomics that simultaneously fixes cells. ACME-dissociated cells have high RNA integrity, can be cryopreserved multiple times, and are sortable and permeable. As a proof of principle, we provide single-cell transcriptomic data of different species, using both droplet-based and combinatorial barcoding single-cell methods. ACME uses affordable reagents, can be done in most laboratories and even in the field, and thus will accelerate our knowledge of cell types across the tree of life.

Single-cell resolution of lineage trajectories in the Arabidopsis stomatal lineage and developing leaf

Dynamic cell identities underlie flexible developmental programs. The stomatal lineage in the Arabidopsis leaf epidermis features asynchronous and indeterminate divisions that can be modulated by environmental cues. The products of the lineage, stomatal guard cells and pavement cells, regulate plant-atmosphere exchanges, and the epidermis as a whole influences overall leaf growth. How flexibility is encoded in development of the stomatal lineage and how cell fates are coordinated in the leaf are open questions. Here, by leveraging single-cell transcriptomics and molecular genetics, we uncovered models of cell differentiation within Arabidopsis leaf tissue. Profiles across leaf tissues identified points of regulatory congruence. In the stomatal lineage, single-cell resolution resolved underlying cell heterogeneity within early stages and provided a fine-grained profile of guard cell differentiation. Through integration of genome-scale datasets and spatiotemporally precise functional manipulations, we also identified an extended role for the transcriptional regulator SPEECHLESS in reinforcing cell fate commitment.

Single-cell genomics to study developmental cell fate decisions in zebrafish

New developments in single-cell genomics have transformed developmental biology in recent years by enabling systematic analysis of embryonic cell types and differentiation trajectories. Ongoing efforts in experimental and computational method development aim to reveal gene-regulatory mechanisms and to provide additional spatio-temporal information about developmental cell fate decisions. Here, we discuss recent technological developments as well as biological applications of single-cell genomics, with a particular focus on analysis of developmental cell fate decisions. Although the approaches described here are generally applicable to a broad range of model systems, we focus our discussion on applications in zebrafish, which has proven to be a particularly powerful model organism for establishing novel methods in single-cell genomics.

Transcriptome Profiling of the Ovarian Cells at the Single-Cell Resolution in Adult Asian Seabass

Single-cell RNA sequencing (scRNA-seq) is widely adopted for identifying the signature molecular markers or regulators in cells, as this would benefit defining or isolating various types of cells. Likewise, the signature transcriptome profile analysis at the single cell level would well illustrate the key regulators or networks involved in gametogenesis and gonad development in animals; however, there is limited scRNA-seq analysis on gonadal cells in lower vertebrates, especially in the sexual reversal fish species. In this study, we analyzed the molecular signature of several distinct cell populations of Asian seabass adult ovaries through scRNA-seq. We identified five cell types and also successfully validated some specific genes of germ cells and granulosa cells. Likewise, we found some key pathways involved in ovarian development that may concert germline-somatic interactions. Moreover, we compared the transcriptomic profiles across fruit fly, mammals, and fish, and thus uncovered the conservation and divergence in molecular mechanisms that might drive ovarian development. Our results provide a basis for studying the crucial features of germ cells and somatic cells, which will benefit the understandings of the molecular mechanisms behind gametogenesis and gonad development in fish.

Investigating the molecular guts of endoderm formation using zebrafish

The vertebrate endoderm makes major contributions to the respiratory and gastrointestinal tracts and all associated organs. Zebrafish and humans share a high degree of genetic homology and strikingly similar endodermal organ systems. Combined with a multitude of experimental advantages, zebrafish are an attractive model organism to study endoderm development and disease. Recent functional genomics studies have shed considerable light on the gene regulatory programs governing early zebrafish endoderm development, while advances in biological and technological approaches stand to further revolutionize our ability to investigate endoderm formation, function and disease. Here, we discuss the present understanding of endoderm specification in zebrafish compared to other vertebrates, how current and emerging methods will allow refined and enhanced analysis of endoderm formation, and how integration with human data will allow modeling of the link between non-coding sequence variants and human disease.

Oocyte Ageing in Zebrafish Danio rerio (Hamilton, 1822) and Its Consequence on the Viability and Ploidy Anomalies in the Progeny

Simple Summary

The maintenance and manipulation of AB strain zebrafish oocytes at 26 °C was found to be possible for 2 h without incurring a marked reduction in fertilization potential. However, the post-ovulatory ageing of oocytes for 6 h resulted in an almost complete loss of egg viability. All larvae derived from the 4- and 6-h aged oocytes were characterized by physical abnormalities. Ageing oocytes for 4 h resulted in the incidence of ploidy anomalies having a four-fold increase. These results make a valuable contribution with respect to the control of experimental reproduction in zebrafish, which is currently accepted as an excellent model animal.

Abstract

Fish egg quality can be markedly influenced by the oocyte age after ovulation. In this study, we examined the duration of oocyte ageing in the zebrafish (Danio rerio) and whether prolonged ageing is associated with the incidence of ploidy anomalies in the resulting embryos. Oocytes were incubated in vitro for 6 h post-stripping (HPS) at 26 °C and fertilized at 2-h intervals. Meanwhile, for eggs fertilized immediately after stripping, the fertilization, embryo survival, and hatching rates started at ~80%; these rates decreased to 39%, 24%, and 16%, respectively, for oocytes that had been stored for 4 h (p ˂ 0.05), and there was an almost complete loss of egg viability at 6 HPS. Furthermore, almost 90% of the embryos derived from 6-h aged oocytes died prior to hatching, and all larvae originating from 4- and 6-h aged oocytes showed malformations. The proportion of ploidy abnormal embryos was significantly greater at 4 HPS (18.5%) than at either 0 or 2 HPS (4.7% and 8.8%, respectively). The results revealed that zebrafish oocytes retained their fertilization potential for up to 2 h after stripping at 26 °C and indicated the contribution of post-ovulatory oocyte ageing in the occurrence of ploidy anomalies in the resulting embryos.

Recent technical progress in sample preparation and liquid-phase separation-mass spectrometry for proteomic analysis of mass-limited samples

Mass spectrometry (MS)-based proteomics has enabled the identification and quantification of thousands of proteins from complex proteomes in a single experiment. However, its performance for mass-limited proteome samples (e.g., single cells and tissue samples from laser capture microdissection) is still not satisfying. The development of novel proteomic methodologies with better overall sensitivity is vital. During the last several years, substantial technical progress has been achieved for the preparation and liquid-phase separation-MS characterization of mass-limited proteome samples. In this review, we summarize recent technological progress of sample preparation, liquid chromatography (LC)-MS, capillary zone electrophoresis (CZE)-MS and MS instrumentation for bottom-up proteomics of trace biological samples, highlight some exciting applications of the novel techniques for single-cell proteomics, and provide a very brief perspective about the field at the end.

Zebrafish as a Neuroblastoma Model: Progress Made, Promise for the Future

For nearly a decade, researchers in the field of pediatric oncology have been using zebrafish as a model for understanding the contributions of genetic alternations to the pathogenesis of neuroblastoma (NB), and exploring the molecular and cellular mechanisms that underlie neuroblastoma initiation and metastasis. In this review, we will enumerate and illustrate the key advantages of using the zebrafish model in NB research, which allows researchers to: monitor tumor development in real-time; robustly manipulate gene expression (either transiently or stably); rapidly evaluate the cooperative interactions of multiple genetic alterations to disease pathogenesis; and provide a highly efficient and low-cost methodology to screen for effective pharmaceutical interventions (both alone and in combination with one another). This review will then list some of the common challenges of using the zebrafish model and provide strategies for overcoming these difficulties. We have also included visual diagram and figures to illustrate the workflow of cancer model development in zebrafish and provide a summary comparison of commonly used animal models in cancer research, as well as key findings of cooperative contributions between MYCN and diverse singling pathways in NB pathogenesis.

New tools for 'ZEBRA-FISHING'

Zebrafish has been established as a classical model for developmental studies, yet in the past years, with the explosion of novel technological methods, the use of zebrafish as a model has expanded. One of the prominent fields that took advantage of zebrafish as a model organism early on is hematopoiesis, the process of blood cell generation from hematopoietic stem and progenitor cells (HSPCs). In zebrafish, HSPCs are born early during development in the aorta-gonad-mesonephros region and then translocate to the caudal hematopoietic tissue, where they expand and finally take residence in the kidney marrow. This journey is tightly regulated at multiple levels from extracellular signals to chromatin. In order to delineate the mechanistic underpinnings of this process, next-generation sequencing techniques could be an important ally. Here, we describe genome-wide approaches that have been undertaken to delineate zebrafish hematopoiesis.

An atlas of neural crest lineages along the posterior developing zebrafish at single-cell resolution

Neural crest cells (NCCs) are vertebrate stem cells that give rise to various cell types throughout the developing body in early life. Here, we utilized single-cell transcriptomic analyses to delineate NCC-derivatives along the posterior developing vertebrate, zebrafish, during the late embryonic to early larval stage, a period when NCCs are actively differentiating into distinct cellular lineages. We identified several major NCC/NCC-derived cell-types including mesenchyme, neural crest, neural, neuronal, glial, and pigment, from which we resolved over three dozen cellular subtypes. We dissected gene expression signatures of pigment progenitors delineating into chromatophore lineages, mesenchyme cells, and enteric NCCs transforming into enteric neurons. Global analysis of NCC derivatives revealed they were demarcated by combinatorial hox gene codes, with distinct profiles within neuronal cells. From these analyses, we present a comprehensive cell-type atlas that can be utilized as a valuable resource for further mechanistic and evolutionary investigations of NCC differentiation.

Single-Cell Sequencing Applications in the Inner Ear

Genomics studies face specific challenges in the inner ear due to the multiple types and limited amounts of inner ear cells that are arranged in a very delicate structure. However, advances in single-cell sequencing (SCS) technology have made it possible to analyze gene expression variations across different cell types as well as within specific cell groups that were previously considered to be homogeneous. In this review, we summarize recent advances in inner ear research brought about by the use of SCS that have delineated tissue heterogeneity, identified unknown cell subtypes, discovered novel cell markers, and revealed dynamic signaling pathways during development. SCS opens up new avenues for inner ear research, and the potential of the technology is only beginning to be explored.

Phylodynamics for cell biologists

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how "tree thinking" is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.

A zebrafish model of granulin deficiency reveals essential roles in myeloid cell differentiation

Granulin is a pleiotropic protein involved in inflammation, wound healing, neurodegenerative disease, and tumorigenesis. These roles in human health have prompted research efforts to use granulin to treat rheumatoid arthritis and frontotemporal dementia and to enhance wound healing. But how granulin contributes to each of these diverse biological functions remains largely unknown. Here, we have uncovered a new role for granulin during myeloid cell differentiation. We have taken advantage of the tissue-specific segregation of the zebrafish granulin paralogues to assess the functional role of granulin in hematopoiesis without perturbing other tissues. By using our zebrafish model of granulin deficiency, we revealed that during normal and emergency myelopoiesis, myeloid progenitors are unable to terminally differentiate into neutrophils and macrophages in the absence of granulin a (grna), failing to express the myeloid-specific genes cebpa, rgs2, lyz, mpx, mpeg1, mfap4, and apoeb. Functionally, macrophages fail to recruit to the wound, resulting in abnormal healing. Our CUT&RUN experiments identify Pu.1, which together with Irf8, positively regulates grna expression. In vivo imaging and RNA sequencing experiments show that grna inhibits the expression of gata1, leading to the repression of the erythroid program. Importantly, we demonstrated functional conservation between the mammalian granulin and the zebrafish ortholog grna. Our findings uncover a previously unrecognized role for granulin during myeloid cell differentiation, which opens a new field of study that can potentially have an impact on different aspects of human health and expand the therapeutic options for treating myeloid disorders such as neutropenia or myeloid leukemia.

Effects of Nanoplastics and Butyl Methoxydibenzoylmethane on Early Zebrafish Embryos Identified by Single-Cell RNA Sequencing

Nanoplastics with small particle sizes and high surface area/volume ratios easily absorb environmental pollutants and affect their bioavailability. In this study, polystyrene nanoplastic beads (PS-NPBs) with a particle size of 100 nm and butyl methoxydibenzoylmethane (BMDBM) sunscreen in personal-care products were chosen as target pollutants to study their developmental toxicity and interactive effects on zebrafish embryos. The exposure period was set from 2 to 12 h postfertilization (hpf). BMDBM and PS-NPBs significantly upregulated genes related to antioxidant enzymes and downregulated the gene expression of aromatase and DNA methyltransferases, but the influenced genes were not exactly the same. The combined exposure reduced the adverse effects on the expression of all genes. With the help of the single-cell RNA sequencing technology, neural mid cells were identified as the target cells of both pollutants, and brain development, head development, and the notch signaling pathway were the functions they commonly altered. The key genes and functions that are specifically affected by BMDBM and/or PS-NPBs were identified. BMDBM mainly affects the differentiation and fate of neurons in the central nervous system through the regulation of her5, her6, her11, lfng, pax2a, and fgfr4. The PS-NPBs regulate the expression of olig2, foxg1a, fzd8b, six3a, rx1, lhx2b, nkx2.1a, and sfrp5 to alter nervous system development, retinal development, and stem cell differentiation. The phenotypic responses of zebrafish larvae at 120 hpf were tested, and significant inhibition of locomotor activity was found, indicating that early effects on the central nervous system would have a sustained impact on the behavior of zebrafish.

Turning Nature's own processes into design strategies for living bone implant biomanufacturing: a decade of Developmental Engineering

A decade after the term developmental engineering (DE) was coined to indicate the use of developmental processes as blueprints for the design and development of engineered living implants, a myriad of proof-of-concept studies demonstrate the potential of this approach in small animal models. This review provides an overview of DE work, focusing on applications in bone regeneration. Enabling technologies allow to quantify the distance between in vitro processes and their developmental counterpart, as well as to design strategies to reduce that distance. By embedding Nature's robust mechanisms of action in engineered constructs, predictive large animal data and subsequent positive clinical outcomes can be gradually achieved. To this end, the development of next generation biofabrication technologies should provide the necessary scale and precision for robust living bone implant biomanufacturing.

Navigating flower development with a new atlas

In this issue of Developmental Cell, a study presents a 4D atlas integrating live imaging data and expression patterns of 28 regulatory genes in early flower development, which can be used to test gene regulation networks, leading to new hypotheses about the interactions and growth control activities of regulatory genes.

DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

The growing attention toward the benefits of single-cell RNA sequencing (scRNA-seq) is leading to a myriad of computational packages for the analysis of different aspects of scRNA-seq data. For researchers without advanced programing skills, it is very challenging to combine several packages in order to perform the desired analysis in a simple and reproducible way. Here we present DIscBIO, an open-source, multi-algorithmic pipeline for easy, efficient and reproducible analysis of cellular sub-populations at the transcriptomic level. The pipeline integrates multiple scRNA-seq packages and allows biomarker discovery with decision trees and gene enrichment analysis in a network context using single-cell sequencing read counts through clustering and differential analysis. DIscBIO is freely available as an R package. It can be run either in command-line mode or through a user-friendly computational pipeline using Jupyter notebooks. We showcase all pipeline features using two scRNA-seq datasets. The first dataset consists of circulating tumor cells from patients with breast cancer. The second one is a cell cycle regulation dataset in myxoid liposarcoma. All analyses are available as notebooks that integrate in a sequential narrative R code with explanatory text and output data and images. R users can use the notebooks to understand the different steps of the pipeline and will guide them to explore their scRNA-seq data. We also provide a cloud version using Binder that allows the execution of the pipeline without the need of downloading R, Jupyter or any of the packages used by the pipeline. The cloud version can serve as a tutorial for training purposes, especially for those that are not R users or have limited programing skills. However, in order to do meaningful scRNA-seq analyses, all users will need to understand the implemented methods and their possible options and limitations.

Longitudinal single-cell RNA-seq of hESCs-derived retinal organoids

Human retina development involves multiple well-studied signaling pathways that promote the genesis of a wide arrange of different cell types in a complex architectural structure. Human embryonic stem cells (hESCs)-derived retinal organoids could recapitulate the human retinal development. We performed single-cell RNA-seq of retinal organoids from 5 time points (D36, D66, D96, D126, D186) and identified 9 distinct populations of cells. In addition, we analyzed the molecular characteristics of each main population and followed them from genesis to maturity by pseudotime analysis and characterized the cell-cell interactions between different cell types. Interestingly, we identified insulin receptor (INSR) as a specifically expressed receptor involved in the genesis of photoreceptors, and pleiothropin (PTN)-protein tyrosine phosphatase receptor type Z1 (PTPRZ1) as a mediator of a previously unknown interaction between Müller and retinal progenitor cells. Taken together, these findings provide a rich transcriptome-based lineage map for studying human retinal development and modeling developmental disorders in retinal organoids.

Sexual and asexual development: two distinct programs producing the same tunicate

Colonial tunicates are the only chordate that possess two distinct developmental pathways to produce an adult body: either sexually through embryogenesis or asexually through a stem cell-mediated renewal termed blastogenesis. Using the colonial tunicate Botryllus schlosseri, we combine transcriptomics and microscopy to build an atlas of the molecular and morphological signatures at each developmental stage for both pathways. The general molecular profiles of these processes are largely distinct. However, the relative timing of organogenesis and ordering of tissue-specific gene expression are conserved. By comparing the developmental pathways of B. schlosseri with other chordates, we identify hundreds of putative transcription factors with conserved temporal expression. Our findings demonstrate that convergent morphology need not imply convergent molecular mechanisms but that it showcases the importance that tissue-specific stem cells and transcription factors play in producing the same mature body through different pathways.

Functional Role of the RNA-Binding Protein Rbm24a and Its Target sox2 in Microphthalmia

Congenital eye defects represent a large class of disorders affecting roughly 21 million children worldwide. Microphthalmia and anophthalmia are relatively common congenital defects, with approximately 20% of human cases caused by mutations in SOX2. Recently, we identified the RNA-binding motif protein 24a (Rbm24a) which binds to and regulates sox2 in zebrafish and mice. Here we show that morpholino knockdown of rbm24a leads to microphthalmia and visual impairment. By utilizing sequential injections, we demonstrate that addition of exogenous sox2 RNA to rbm24a-deplete embryos is sufficient to suppress morphological and visual defects. This research demonstrates a critical role for understanding the post-transcriptional regulation of genes needed for development.

Microtubule Severing Protein Fignl2 Contributes to Endothelial and Neuronal Branching in Zebrafish Development

Previously, fidgetin (fign) and its family members fidgetin-like 1 (fignl1) and fidgetin-like 2 (fignl2) were found to be highly expressed during zebrafish brain development, suggesting their functions in the nervous system. In this study, we report the effects of loss-of-function of these genes on development. We designed and identified single-guide RNAs targeted to generate fign, fignl1, and fignl2 mutants and then observed the overall morphological and behavioral changes. Our findings showed that while fign and fignl1 null mutants displayed no significant defects, fignl2 null zebrafish mutants displayed pericardial edema, reduced heart rate, and smaller eyes; fignl2 null mutants responded to the light-darkness shift with a lower swimming velocity. fignl2 mRNAs were identified in vascular endothelial cells by in situ hybridization and re-analysis of an online dataset of single-cell RNAseq results. Finally, we used morpholino oligonucleotides to confirm that fignl2 knockdown resulted in severe heart edema, which was caused by abnormal vascular branching. The zebrafish fignl2 morphants also showed longer axonal length and more branches of caudal primary neurons. Taken together, we summarize that Fignl2 functions on cellular branches in endothelial cells and neurons. This study reported for the first time that the microtubule-severing protein Fignl2 contributes to cell branching during development.

Diverse Routes toward Early Somites in the Mouse Embryo

Somite formation is foundational to creating the vertebrate segmental body plan. Here, we describe three transcriptional trajectories toward somite formation in the early mouse embryo. Precursors of the anterior-most somites ingress through the primitive streak before E7 and migrate anteriorly by E7.5, while a second wave of more posterior somites develops in the vicinity of the streak. Finally, neuromesodermal progenitors (NMPs) are set aside for subsequent trunk somitogenesis. Single-cell profiling of T-/- chimeric embryos shows that the anterior somites develop in the absence of T and suggests a cell-autonomous function of T as a gatekeeper between paraxial mesoderm production and the building of the NMP pool. Moreover, we identify putative regulators of early T-independent somites and challenge the T-Sox2 cross-antagonism model in early NMPs. Our study highlights the concept of molecular flexibility during early cell-type specification, with broad relevance for pluripotent stem cell differentiation and disease modeling.

What machine learning can do for developmental biology

Developmental biology has grown into a data intensive science with the development of high-throughput imaging and multi-omics approaches. Machine learning is a versatile set of techniques that can help make sense of these large datasets with minimal human intervention, through tasks such as image segmentation, super-resolution microscopy and cell clustering. In this Spotlight, I introduce the key concepts, advantages and limitations of machine learning, and discuss how these methods are being applied to problems in developmental biology. Specifically, I focus on how machine learning is improving microscopy and single-cell 'omics' techniques and data analysis. Finally, I provide an outlook for the futures of these fields and suggest ways to foster new interdisciplinary developments.

Computational Stem Cell Biology: Open Questions and Guiding Principles

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology. We also discuss important challenges for this field with the hope that it will inspire more to join this exciting area.

Evolution of Cellular Differentiation: From Hypotheses to Models

Cellular differentiation is one of the hallmarks of complex multicellularity, allowing individual organisms to capitalize on among-cell functional diversity. The evolution of multicellularity is a major evolutionary transition that allowed for the increase of organismal complexity in multiple lineages, a process that relies on the functional integration of cell-types within an individual. Multiple hypotheses have been proposed to explain the origins of cellular differentiation, but we lack a general understanding of what makes one cell-type distinct from others, and how such differentiation arises. Here, we describe how the use of Boolean networks (BNs) can aid in placing empirical findings into a coherent conceptual framework, and we emphasize some of the standing problems when interpreting data and model behaviors.

Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning

High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and functions at scale. Recent studies have demonstrated that information in large imaging datasets can be used to estimate gene mutations and to predict the cell-cycle state and the cellular decision making directly from cellular morphology. Thus, high-throughput imaging methodologies, such as imaging flow cytometry can potentially aim beyond simple sorting of cell-populations. We introduce IFC-seq, a machine learning methodology for predicting the expression profile of every cell in an imaging flow cytometry experiment. Since it is to-date unfeasible to observe single-cell gene expression and morphology in flow, we integrate uncoupled imaging data with an independent transcriptomics dataset by leveraging common surface markers. We demonstrate that IFC-seq successfully models gene expression of a moderate number of key gene-markers for two independent imaging flow cytometry datasets: (i) human blood mononuclear cells and (ii) mouse myeloid progenitor cells. In the case of mouse myeloid progenitor cells IFC-seq can predict gene expression directly from brightfield images in a label-free manner, using a convolutional neural network. The proposed method promises to add gene expression information to existing and new imaging flow cytometry datasets, at no additional cost.

Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation

MOTIVATION

The advent of in vivo automated techniques for single-cell lineaging, sequencing and analysis of gene expression has begun to dramatically increase our understanding of organismal development. We applied novel meta-analysis and visualization techniques to the EPIC single-cell-resolution developmental gene expression dataset for Caenorhabditis elegans from Bao, Murray, Waterston et al. to gain insights into regulatory mechanisms governing the timing of development.

RESULTS

Our meta-analysis of the EPIC dataset revealed that a simple linear combination of the expression levels of the developmental genes is strongly correlated with the developmental age of the organism, irrespective of the cell division rate of different cell lineages. We uncovered a pattern of collective sinusoidal oscillation in gene activation, in multiple dominant frequencies and in multiple orthogonal axes of gene expression, pointing to the existence of a coordinated, multi-frequency global timing mechanism. We developed a novel method based on Fisher's Discriminant Analysis to identify gene expression weightings that maximally separate traits of interest, and found that remarkably, simple linear gene expression weightings are capable of producing sinusoidal oscillations of any frequency and phase, adding to the growing body of evidence that oscillatory mechanisms likely play an important role in the timing of development. We cross-linked EPIC with gene ontology and anatomy ontology terms, employing Fisher's Discriminant Analysis methods to identify previously unknown positive and negative genetic contributions to developmental processes and cell phenotypes. This meta-analysis demonstrates new evidence for direct linear and/or sinusoidal mechanisms regulating the timing of development. We uncovered a number of previously unknown positive and negative correlations between developmental genes and developmental processes or cell phenotypes. Our results highlight both the continued relevance of the EPIC technique, and the value of meta-analysis of previously published results. The presented analysis and visualization techniques are broadly applicable across developmental and systems biology.

AVAILABILITY AND IMPLEMENTATION

Analysis software available upon request.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Emergence of Neuronal Diversity during Vertebrate Brain Development

Neurogenesis comprises many highly regulated processes including proliferation, differentiation, and maturation. However, the transcriptional landscapes underlying brain development are poorly characterized. We describe a developmental single-cell catalog of ∼220,000 zebrafish brain cells encompassing 12 stages from embryo to larva. We characterize known and novel gene markers for ∼800 clusters and provide an overview of the diversification of neurons and progenitors across these time points. We also introduce an optimized GESTALT lineage recorder that enables higher expression and recovery of Cas9-edited barcodes to query lineage segregation. Cell type characterization indicates that most embryonic neural progenitor states are transitory and transcriptionally distinct from neural progenitors of post-embryonic stages. Reconstruction of cell specification trajectories reveals that late-stage retinal neural progenitors transcriptionally overlap cell states observed in the embryo. The zebrafish brain development atlas provides a resource to define and manipulate specific subsets of neurons and to uncover the molecular mechanisms underlying vertebrate neurogenesis.

New era of trophoblast research: integrating morphological and molecular approaches

Many pregnancy complications are the result of dysfunction in the placenta. The pathogenic mechanisms of placenta-mediated pregnancy complications, however, are unclear. Abnormal placental development in these conditions begins in the first trimester, but no symptoms are observed during this period. To elucidate effective preventative treatments, understanding the differentiation and development of human placenta is crucial. This review elucidates the uniqueness of the human placenta in early development from the aspect of structural characteristics and molecular markers. We summarise the morphogenesis of human placenta based on human specimens and then compile molecular markers that have been clarified by immunostaining and RNA-sequencing data across species. Relevant studies were identified using the PubMed database and Google Scholar search engines up to March 2020. All articles were independently screened for eligibility by the authors based on titles and abstracts. In particular, the authors carefully examined literature on human placentation. This review integrates the development of human placentation from morphological approaches in comparison with other species and provides new insights into trophoblast molecular markers. The morphological features of human early placentation are described in Carnegie stages (CS), from CS3 (floating blastocyst) to CS9 (emerging point of tertiary villi). Molecular markers are described for each type of trophoblast involved in human placental development. We summarise the character of human trophoblast cell lines and explain how long-term culture system of human cytotrophoblast, both monolayer and spheroid, established in recent studies allows for the generation of human trophoblast cell lines. Due to differences in developmental features among species, it is desirable to understand early placentation in humans. In addition, reliable molecular markers that reflect normal human trophoblast are needed to advance trophoblast research. In the clinical setting, these markers can be valuable means for morphologically and functionally assessing placenta-mediated pregnancy complications and provide early prediction and management of these diseases.

Single-cell atlas of the first intra-mammalian developmental stage of the human parasite Schistosoma mansoni

Over 250 million people suffer from schistosomiasis, a tropical disease caused by parasitic flatworms known as schistosomes. Humans become infected by free-swimming, water-borne larvae, which penetrate the skin. The earliest intra-mammalian stage, called the schistosomulum, undergoes a series of developmental transitions. These changes are critical for the parasite to adapt to its new environment as it navigates through host tissues to reach its niche, where it will grow to reproductive maturity. Unravelling the mechanisms that drive intra-mammalian development requires knowledge of the spatial organisation and transcriptional dynamics of different cell types that comprise the schistomulum body. To fill these important knowledge gaps, we perform single-cell RNA sequencing on two-day old schistosomula of Schistosoma mansoni. We identify likely gene expression profiles for muscle, nervous system, tegument, oesophageal gland, parenchymal/primordial gut cells, and stem cells. In addition, we validate cell markers for all these clusters by in situ hybridisation in schistosomula and adult parasites. Taken together, this study provides a comprehensive cell-type atlas for the early intra-mammalian stage of this devastating metazoan parasite.

Why isn't sex optional? Stem-cell competition, loss of regenerative capacity, and cancer in metazoan evolution

Animals that can reproduce vegetatively by fission or budding and also sexually via specialized gametes are found in all five primary animal lineages (Bilateria, Cnidaria, Ctenophora, Placozoa, Porifera). Many bilaterian lineages, including roundworms, insects, and most chordates, have lost the capability of vegetative reproduction and are obligately gametic. We suggest a developmental explanation for this evolutionary phenomenon: obligate gametic reproduction is the result of germline stem cells winning a winner-take-all competition with non-germline stem cells for control of reproduction and hence lineage survival. We develop this suggestion by extending Hamilton's rule, which factors the relatedness between parties into the cost/benefit analysis that underpins cooperative behaviors, to include similarity of cellular state. We show how coercive or deceptive cell-cell signaling can be used to make costly cooperative behaviors appear less costly to the cooperating party. We then show how competition between stem-cell lineages can render an ancestral combination of vegetative reproduction with facultative sex unstable, with one or the other process driven to extinction. The increased susceptibility to cancer observed in obligately-sexual lineages is, we suggest, a side-effect of deceptive signaling that is exacerbated by the loss of whole-body regenerative abilities. We suggest a variety of experimental approaches for testing our predictions.