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

Maximizing single cell dissociation protocol for individual zebrafish embryo

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and cell state, enabling investigations across diverse fields such as developmental biology, immunology, and cancer biology. However, obtaining a high-quality single-cell suspension is still challenging, particularly when starting with limited materials like Zebrafish embryos, a powerful animal model for studying developmental processes and human diseases. Here, we present an optimized protocol for isolating single cells from individual zebrafish embryos, offering a valuable resource for researchers interested in working with limited starting material. The protocol facilitates unique investigations utilizing individual embryos, such as inter-individual genetic differences and embryo-specific lineage tracing analysis. Using a refined single-cell isolation protocol alongside zebrafish as a model organism, researchers can access a resource for exploring the emergence of all types and states of cells, advancing our understanding of cellular processes and disease mechanisms.

The pericardium forms as a distinct structure during heart formation

The heart integrates diverse cell lineages into a functional unit, including the pericardium, a mesothelial sac that supports heart movement, homeostasis, and immune responses. However, despite its critical roles, the developmental origins of the pericardium remain uncertain due to disparate models. Here, using live imaging, lineage tracking, and single-cell transcriptomics in zebrafish, we find the pericardium forms within the lateral plate mesoderm from dedicated anterior mesothelial progenitors and distinct from the classic heart field. Imaging of transgenic reporters in zebrafish documents lateral plate mesoderm cells that emerge lateral of the classic heart field and among a continuous mesothelial progenitor field. Single-cell transcriptomics and trajectories of hand2-expressing lateral plate mesoderm reveal distinct populations of mesothelial and cardiac precursors, including pericardial precursors that are distinct from the cardiomyocyte lineage. The mesothelial gene expression signature is conserved in mammals and carries over to post-natal development. Light sheet-based live-imaging and machine learning-supported cell tracking documents that during heart tube formation, pericardial precursors that reside at the anterior edge of the heart field migrate anteriorly and medially before fusing, enclosing the embryonic heart to form a single pericardial cavity. Pericardium formation proceeds even upon genetic disruption of heart tube formation, uncoupling the two structures. Canonical Wnt/β-catenin signaling modulates pericardial cell number, resulting in a stretched pericardial epithelium with reduced cell number upon canonical Wnt inhibition. We connect the pathological expression of secreted Wnt antagonists of the SFRP family found in pediatric dilated cardiomyopathy to increased pericardial stiffness: sFRP1 in the presence of increased catecholamines causes cardiomyocyte stiffness in neonatal rats as measured by atomic force microscopy. Altogether, our data integrate pericardium formation as an independent process into heart morphogenesis and connect disrupted pericardial tissue properties such as pericardial stiffness to pediatric cardiomyopathies.

Drivers of vessel progenitor fate define intermediate mesoderm dimensions by inhibiting kidney progenitor specification

Proper organ formation depends on the precise delineation of organ territories containing defined numbers of progenitor cells. Kidney progenitors reside in bilateral stripes of posterior mesoderm that are referred to as the intermediate mesoderm (IM). Previously, we showed that the transcription factors Hand2 and Osr1 act to strike a balance between the specification of the kidney progenitors in the IM and the vessel progenitors in the laterally adjacent territory. Recently, the transcription factor Npas4l - an early and essential driver of vessel and blood progenitor formation - was shown to inhibit kidney development. Here we demonstrate how kidney progenitor specification is coordinated by hand2, osr1, and npas4l. We find that npas4l and the IM marker pax2a are transiently co-expressed in the posterior lateral mesoderm, and npas4l is necessary to inhibit IM formation. Consistent with the expression of npas4l flanking the medial and lateral sides of the IM, our findings suggest roles for npas4l in defining the IM boundaries at each of these borders. At the lateral IM border, hand2 promotes and osr1 inhibits the formation of npas4l-expressing lateral vessel progenitors, and hand2 requires npas4l to inhibit IM formation and to promote vessel formation. Meanwhile, npas4l appears to have an additional role in suppressing IM fate at the medial border: npas4l loss-of-function enhances hand2 mutant IM defects and results in excess IM generated outside of the lateral hand2-expressing territory. Together, our findings reveal that establishment of the medial and lateral boundaries of the IM requires inhibition of kidney progenitor specification by the neighboring drivers of vessel progenitor fate.

Robust Double Emulsions for Multicolor Fluorescence-Activated Cell Sorting

Cell-cell interactions are essential for the proper functioning of multicellular organisms. For example, T cells interact with antigen-presenting cells (APCs) through specific T-cell receptor (TCR)-antigen interactions during an immune response. Fluorescence-activated droplet sorting (FADS) is a high-throughput technique for efficiently screening cellular interaction events. Unfortunately, current droplet sorting instruments have significant limitations, most notably related to analytical throughput and complex operation. In contrast, commercial fluorescence-activated cell sorters offer superior speed, sensitivity, and multiplexing capabilities, although their use as droplet sorters is poorly defined and underutilized. Herein, we present a universally applicable and simple-to-implement workflow for generating double emulsions and performing multicolor cell sorting using a commercial FACS instrument. This workflow achieves a double emulsion detection rate exceeding 90%, enabling multicellular encapsulation and high-throughput immune cell activation sorting for the first time. We anticipate that the presented droplet sorting strategy will benefit cell biology laboratories by providing access to an advanced microfluidic toolbox with minimal effort and cost investment.

Inferring cell differentiation maps from lineage tracing data

During development, mulitpotent cells differentiate through a hierarchy of increasingly restricted progenitor cell types until they realize specialized cell types. A cell differentiation map describes this hierarchy, and inferring these maps is an active area of research spanning traditional single marker lineage studies to data-driven trajectory inference methods on single-cell RNA-seq data. Recent high-throughput lineage tracing technologies profile lineages and cell types at scale, but current methods to infer cell differentiation maps from these data rely on simple models with restrictive assumptions about the developmental process. We introduce a mathematical framework for cell differentiation maps based on the concept of potency, and develop an algorithm, Carta, that infers an optimal cell differentiation map from single-cell lineage tracing data. The key insight in Carta is to balance the trade-off between the complexity of the cell differentiation map and the number of unobserved cell type transitions on the lineage tree. We show that Carta more accurately infers cell differentiation maps on both simulated and real data compared to existing methods. In models of mammalian trunk development and mouse hematopoiesis, Carta identifies important features of development that are not revealed by other methods including convergent differentiation of specialized cell types, progenitor differentiation dynamics, and the refinement of routes of differentiation via new intermediate progenitors.

Untangling Zebrafish Genetic Annotation: Addressing Complexities and Nomenclature Issues in Orthologous Evaluation of TCOF1 and NOLC1

Treacher Collins syndrome (TCS) is a genetic disorder affecting facial development, primarily caused by mutations in the TCOF1 gene. TCOF1, along with NOLC1, play important roles in ribosomal RNA transcription and processing. Previously, a zebrafish model of TCS successfully recapitulated the main characteristics of the syndrome by knocking down the expression of a gene on chromosome 13 (coding for Uniprot ID B8JIY2), which was identified as the TCOF1 orthologue. However, database updates renamed this gene as nolc1 and the zebrafish database (ZFIN) identified a different gene on chromosome 14 as the TCOF1 orthologue (coding for Uniprot ID E7F9D9). NOLC1 and TCOF1 are large proteins with unstructured regions and repetitive sequences that complicate alignments and comparisons. Also, the additional whole genome duplication of teleosts sets further difficulty. In this study, we present evidence that endorses that NOLC1 and TCOF1 are paralogs, and that the zebrafish gene on chromosome 14 is a low-complexity LisH domain-containing factor that displays homology to NOLC1 but lacks essential sequence features to accomplish TCOF1 nucleolar functions. Our analysis also supports the idea that zebrafish, as has been suggested for other non-tetrapod vertebrates, lack the TCOF1 gene that is associated with tripartite nucleolus. Using BLAST searches in a group of teleost genomes, we identified fish-specific sequences similar to E7F9D9 zebrafish protein. We propose naming them "LisH-containing Low Complexity Proteins" (LLCP). Interestingly, the gene on chromosome 13 (nolc1) displays the sequence features, developmental expression patterns, and phenotypic impact of depletion that are characteristic of TCOF1 functions. These findings suggest that in teleost fish, the nucleolar functions described for both NOLC1 and TCOF1 mediated by their repeated motifs, are carried out by a single gene, nolc1. Our study, which is mainly based on computational tools available as free web-based algorithms, could help to solve similar conflicts regarding gene orthology in zebrafish.

Single‑cell RNA sequencing analysis of human embryos from the late Carnegie to fetal development

BACKGROUND

The cell development atlas of transition stage from late Carnegie to fetal development (7-9 weeks) remain unclear. It can be seen that the early period of human embryos (7-9 weeks) is a critical research gap. Therefore, we employed single‑cell RNA sequencing to identify cell types and elucidate differentiation relationships.

RESULTS

The single‑cell RNA sequencing analysis determines eighteen cell clusters in human embryos during the 7-9 weeks period. We uncover two distinct pathways of cellular development and differentiation. Initially, mesenchymal progenitor cells differentiated into osteoblast progenitor cells and neural stem cells, respectively. Neural stem cells further differentiated into neurons. Alternatively, multipotential stem cells differentiated into adipocyte, hematopoietic stem cells and neutrophil, respectively. Additionally, COL1A2-(ITGA1 + ITGB1) mediated the cell communication between mesenchymal progenitor cells and osteoblast progenitor cells. NCAM1-FGFR1 facilitated the cell communication between mesenchymal progenitor cells and neural stem cells. Notably, NCAM1-NCAM1 as a major contributor mediated the cell communication between neural stem cells and neurons. Moreover, CGA-FSHR simultaneously mediated the communication between multipotential stem cells, adipocyte, hematopoietic stem cells and neutrophil. Distinct cell clusters activated specific transcription factors such as HIC1, LMX1B, TWIST1, and et al., which were responsible for their specific functions. These coregulators, such as HOXB13, VSX2, PAX5, and et al., may mediate cell development and differentiation in human embryos.

CONCLUSIONS

We provide the cell development atlas for human embryos (7-9 weeks). Two distinct cell development and differentiation pathways are revealed.

A single-nucleus transcriptomic atlas characterizes cell types and their molecular features in the ovary of adult Nile tilapia

In fish species, there is limited analysis of signature transcriptome profiles at the single-cell level in gonadal cells. Here, the molecular signatures of distinct ovarian cell categories in adult Nile tilapia (Oreochromis niloticus) were analysed using single-nucleus RNA sequencing (snRNA-seq). We identified four cell types (oogonia, oocytes, granulosa cell, and thecal cell) based on their specifically expressed genes and biological functions. Similarly, we found some key pathways involved in ovarian development that may affect germline-somatic interactions. A cell-to-cell communication network between the distinct cell types was constructed. We found that the bidirectional communication is mandatory for the development of germ cells and somatic cells in fish ovaries, and the granulosa cells and thecal cells play a central regulating role in the cell network in fish ovary. Additionally, we identified some novel candidate marker genes for various types of ovarian cells and also validated them using in situ hybridization. Our work reveals an ovarian atlas at the cellular and molecular levels and contributes to providing insights into oogenesis and gonad development in fish.

Achieving single-cell-resolution lineage tracing in zebrafish by continuous barcoding mutations during embryogenesis

Unraveling the lineage relationships of all descendants from a zygote is fundamental to advancing our understanding of developmental and stem cell biology. However, existing cell barcoding technologies in zebrafish lack the resolution to capture the majority of cell divisions during embryogenesis. A recently developed method, a substitution mutation-aided lineage-tracing system (SMALT), successfully reconstructed high-resolution cell phylogenetic trees for Drosophila melanogaster. Here, we implement the SMALT system in zebrafish, recording a median of 14 substitution mutations on a one-kilobase-pair barcoding sequence for one-day post-fertilization embryos. Leveraging this system, we reconstruct four cell lineage trees for zebrafish fin cells, encompassing both original and regenerated fin. Each tree consists of hundreds of internal nodes with a median bootstrap support of 99%. Analysis of the obtained cell lineage trees reveals that regenerated fin cells mainly originate from cells in the same part of the fins. Through multiple times sampling germ cells from the same individual, we show the stability of the germ cell pool and the early separation of germ cell and somatic cell progenitors. Our system offers the potential for reconstructing high-quality cell phylogenies across diverse tissues, providing valuable insights into development and disease in zebrafish.

Establishment and transcriptome analysis of single blastomere-derived cell lines from zebrafish

Maintaining chromosome euploidy in zebrafish embryonic cells is challenging because of the degradation of genomic integrity during cell passaging. In this study, we report the derivation of zebrafish cell lines from single blastomeres. These cell lines have a stable chromosome status attributed to BMP4 and exhibit continuous proliferation in vitro. Twenty zebrafish cell lines are successfully established from single blastomeres. Single-cell transcriptome sequencing analysis confirms the fidelity of gene expression profiles throughout long-term culturing of at least 45 passages. The long-term cultured cells are specialized into epithelial cells, exhibiting similar expression patterns validated by integrative transcriptomic analysis. Overall, this work provides a protocol for establishing zebrafish cell lines from single blastomeres, which can serve as valuable tools for in vitro investigations of epithelial cell dynamics in terms of life-death balance and cell fate determination during normal homeostasis.

Akt is a mediator of artery specification during zebrafish development

The dorsal aorta (DA) is the first major blood vessel to develop in the embryonic cardiovascular system. Its formation is governed by a coordinated process involving the migration, specification, and arrangement of angioblasts into arterial and venous lineages, a process conserved across species. Although vascular endothelial growth factor a (VEGF-A) is known to drive DA specification and formation, the kinases involved in this process remain ambiguous. Thus, we investigated the role of protein kinase B (Akt) in zebrafish by generating a quadruple mutant (aktΔ/Δ), in which expression and activity of all Akt genes - akt1, -2, -3a and -3b - are strongly decreased. Live imaging of developing aktΔ/Δ DA uncovers early arteriovenous malformations. Single-cell RNA-sequencing analysis of aktΔ/Δ endothelial cells corroborates the impairment of arterial, yet not venous, cell specification. Notably, endothelial specific expression of ligand-independent activation of Notch or constitutively active Akt1 were sufficient to re-establish normal arterial specification in aktΔ/Δ. The Akt loss-of-function mutant unveils that Akt kinase can act upstream of Notch in arterial endothelial cells, and is involved in proper embryonic artery specification. This sheds light on cardiovascular development, revealing a mechanism behind congenital malformations.

Evolutionary origin of the chordate nervous system revealed by amphioxus developmental trajectories

The common ancestor of all vertebrates had a highly sophisticated nervous system, but questions remain about the evolution of vertebrate neural cell types. The amphioxus, a chordate that diverged before the origin of vertebrates, can inform vertebrate evolution. Here we develop and analyse a single-cell RNA-sequencing dataset from seven amphioxus embryo stages to understand chordate cell type evolution and to study vertebrate neural cell type origins. We identified many new amphioxus cell types, including homologues to the vertebrate hypothalamus and neurohypophysis, rooting the evolutionary origin of these structures. On the basis of ancestor-descendant reconstruction of cell trajectories of the amphioxus and other species, we inferred expression dynamics of transcription factor genes throughout embryogenesis and identified three ancient developmental routes forming chordate neurons. We characterized cell specification at the mechanistic level and generated mutant lines to examine the function of five key transcription factors involved in neural specification. Our results show three developmental origins for the vertebrate nervous system: an anterior FoxQ2-dependent mechanism that is deeply conserved in invertebrates, a less-conserved route leading to more posterior neurons in the vertebrate spinal cord and a mechanism for specifying neuromesoderm progenitors that is restricted to chordates. The evolution of neuromesoderm progenitors may have led to a dramatic shift in posterior neural and mesodermal cell fate decisions and the body elongation process in a stem chordate.

Comprehensive profiling of migratory primordial germ cells reveals niche-specific differences in non-canonical Wnt and Nodal-Lefty signaling in anterior vs posterior migrants

Mammalian primordial germ cells (PGCs) migrate asynchronously through the embryonic hindgut and dorsal mesentery to reach the gonads. We previously found that interaction with different somatic niches regulates PGC proliferation along the migration route. To characterize transcriptional heterogeneity of migrating PGCs and their niches, we performed single-cell RNA sequencing of 13,262 mouse PGCs and 7,868 surrounding somatic cells during migration (E9.5, E10.5, E11.5) and in anterior versus posterior locations to enrich for leading and lagging migrants. Analysis of PGCs by position revealed dynamic gene expression changes between faster or earlier migrants in the anterior and slower or later migrants in the posterior at E9.5; these differences include migration-associated actin polymerization machinery and epigenetic reprogramming-associated genes. We furthermore identified changes in signaling with various somatic niches, notably strengthened interactions with hindgut epithelium via non-canonical WNT (ncWNT) in posterior PGCs compared to anterior. Reanalysis of a previously published dataset suggests that ncWNT signaling from the hindgut epithelium to early migratory PGCs is conserved in humans. Trajectory inference methods identified putative differentiation trajectories linking cell states across timepoints and from posterior to anterior in our mouse dataset. At E9.5, we mainly observed differences in cell adhesion and actin cytoskeletal dynamics between E9.5 posterior and anterior migrants. At E10.5, we observed divergent gene expression patterns between putative differentiation trajectories from posterior to anterior including Nodal signaling response genes Lefty1, Lefty2, and Pycr2 and reprogramming factors Dnmt1, Prc1, and Tet1. At E10.5, we experimentally validated anterior migrant-specific Lefty1/2 upregulation via whole-mount immunofluorescence staining for LEFTY1/2 proteins, suggesting that elevated autocrine Nodal signaling accompanies the late stages of PGC migration. Together, this positional and temporal atlas of mouse PGCs supports the idea that niche interactions along the migratory route elicit changes in proliferation, actin dynamics, pluripotency, and epigenetic reprogramming.

Dissecting the regulatory logic of specification and differentiation during vertebrate embryogenesis

The interplay between transcription factors and chromatin accessibility regulates cell type diversification during vertebrate embryogenesis. To systematically decipher the gene regulatory logic guiding this process, we generated a single-cell multi-omics atlas of RNA expression and chromatin accessibility during early zebrafish embryogenesis. We developed a deep learning model to predict chromatin accessibility based on DNA sequence and found that a small number of transcription factors underlie cell-type-specific chromatin landscapes. While Nanog is well-established in promoting pluripotency, we discovered a new function in priming the enhancer accessibility of mesendodermal genes. In addition to the classical stepwise mode of differentiation, we describe instant differentiation, where pluripotent cells skip intermediate fate transitions and terminally differentiate. Reconstruction of gene regulatory interactions reveals that this process is driven by a shallow network in which maternally deposited regulators activate a small set of transcription factors that co-regulate hundreds of differentiation genes. Notably, misexpression of these transcription factors in pluripotent cells is sufficient to ectopically activate their targets. This study provides a rich resource for analyzing embryonic gene regulation and reveals the regulatory logic of instant differentiation.

StaVia: spatially and temporally aware cartography with higher-order random walks for cell atlases

Single-cell atlases pose daunting computational challenges pertaining to the integration of spatial and temporal information and the visualization of trajectories across large atlases. We introduce StaVia, a computational framework that synergizes multi-faceted single-cell data with higher-order random walks that leverage the memory of cells' past states, fused with a cartographic Atlas View that offers intuitive graph visualization. This spatially aware cartography captures relationships between cell populations based on their spatial location as well as their gene expression and developmental stage. We demonstrate this using zebrafish gastrulation data, underscoring its potential to dissect complex biological landscapes in both spatial and temporal contexts.

Population Diversity at the Single-Cell Level

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease.

Systematic analysis on the horse-shoe-like effect in PCA plots of scRNA-seq data

Motivation

In single-cell studies, principal component analysis (PCA) is widely used to reduce the dimensionality of dataset and visualize in 2D or 3D PC plots. Scientists often focus on different clusters within PC plot, overlooking the specific phenomenon, such as horse-shoe-like effect, that may reveal hidden knowledge about underlying biological dataset. This phenomenon remains largely unexplored in single-cell studies.

Results

In this study, we investigated into the horse-shoe-like effect in PC plots using simulated and real scRNA-seq datasets. We systematically explain horse-shoe-like phenomenon from various inter-related perspectives. Initially, we establish an intuitive understanding with the help of simulated datasets. Then, we generalized the acquired knowledge on real biological scRNA-seq data. Experimental results provide logical explanations and understanding for the appearance of horse-shoe-like effect in PC plots. Furthermore, we identify a potential problem with a well-known theory of 'distance saturation property' attributed to induce horse-shoe phenomenon. Finally, we analyse a mathematical model for horse-shoe effect that suggests trigonometric solutions to estimated eigenvectors. We observe significant resemblance after comparing the results of mathematical model with simulated and real scRNA-seq datasets.

Availability and implementation

The code for reproducing the results of this study is available at: https://github.com/najeebullahshah/PCA-Horse-Shoe.

The evolution of developmental biology through conceptual and technological revolutions

Developmental biology-the study of the processes by which cells, tissues, and organisms develop and change over time-has entered a new golden age. After the molecular genetics revolution in the 80s and 90s and the diversification of the field in the early 21st century, we have entered a phase when powerful technologies provide new approaches and open unexplored avenues. Progress in the field has been accelerated by advances in genomics, imaging, engineering, and computational biology and by emerging model systems ranging from tardigrades to organoids. We summarize how revolutionary technologies have led to remarkable progress in understanding animal development. We describe how classic questions in gene regulation, pattern formation, morphogenesis, organogenesis, and stem cell biology are being revisited. We discuss the connections of development with evolution, self-organization, metabolism, time, and ecology. We speculate how developmental biology might evolve in an era of synthetic biology, artificial intelligence, and human engineering.

scMultiome analysis identifies a single caudal hindbrain compartment in the developing zebrafish nervous system

BACKGROUND

A key step in nervous system development involves the coordinated control of neural progenitor specification and positioning. A long-standing model for the vertebrate CNS postulates that transient anatomical compartments - known as neuromeres - function to position neural progenitors along the embryonic anteroposterior neuraxis. Such neuromeres are apparent in the embryonic hindbrain - that contains six rhombomeres with morphologically apparent boundaries - but other neuromeres lack clear morphological boundaries and have instead been defined by different criteria, such as differences in gene expression patterns and the outcomes of transplantation experiments. Accordingly, the caudal hindbrain (CHB) posterior to rhombomere (r) 6 has been variably proposed to contain from two to five 'pseudo-rhombomeres', but the lack of comprehensive molecular data has precluded a detailed definition of such structures.

METHODS

We used single-cell Multiome analysis, which allows simultaneous characterization of gene expression and chromatin state of individual cell nuclei, to identify and characterize CHB progenitors in the developing zebrafish CNS.

RESULTS

We identified CHB progenitors as a transcriptionally distinct population, that also possesses a unique profile of accessible transcription factor binding motifs, relative to both r6 and the spinal cord. This CHB population can be subdivided along its dorsoventral axis based on molecular characteristics, but we do not find any molecular evidence that it contains multiple pseudo-rhombomeres. We further observe that the CHB is closely related to r6 at the earliest embryonic stages, but becomes more divergent over time, and that it is defined by a unique gene regulatory network.

CONCLUSIONS

We conclude that the early CHB represents a single neuromere compartment that cannot be molecularly subdivided into pseudo-rhombomeres and that it may share an embryonic origin with r6.

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Mapping the chromatin accessibility landscape of zebrafish embryogenesis at single-cell resolution by SPATAC-seq

Currently, the dynamic accessible elements that determine regulatory programs responsible for the unique identity and function of each cell type during zebrafish embryogenesis lack detailed study. Here we present SPATAC-seq: a split-pool ligation-based assay for transposase-accessible chromatin using sequencing. Using SPATAC-seq, we profiled chromatin accessibility in more than 800,000 individual nuclei across 20 developmental stages spanning the sphere stage to the early larval protruding mouth stage. Using this chromatin accessibility map, we identified 604 cell states and inferred their developmental relationships. We also identified 959,040 candidate cis-regulatory elements (cCREs) and delineated development-specific cCREs, as well as transcription factors defining diverse cell identities. Importantly, enhancer reporter assays confirmed that the majority of tested cCREs exhibited robust enhanced green fluorescent protein expression in restricted cell types or tissues. Finally, we explored gene regulatory programs that drive pigment and notochord cell differentiation. Our work provides a valuable open resource for exploring driver regulators of cell fate decisions in zebrafish embryogenesis.

Application of Lineage Tracing in Central Nervous System Development and Regeneration

The central nervous system (CNS) is a complicated neural network. The origin and evolution of functional neurons and glia cells remain unclear, as do the cellular alterations that occur during the course of cerebral disease rehabilitation. Lineage tracing is a valuable method for tracing specific cells and achieving a better understanding of the CNS. Recently, various technological breakthroughs have been made in lineage tracing, such as the application of various combinations of fluorescent reporters and advances in barcode technology. The development of lineage tracing has given us a deeper understanding of the normal physiology of the CNS, especially the pathological processes. In this review, we summarize these advances of lineage tracing and their applications in CNS. We focus on the use of lineage tracing techniques to elucidate the process CNS development and especially the mechanism of injury repair. Deep understanding of the central nervous system will help us to use existing technologies to diagnose and treat diseases.

Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data

MOTIVATION

Eukaryotic cells contain organelles called mitochondria that have their own genome. Most cells contain thousands of mitochondria which replicate, even in nondividing cells, by means of a relatively error-prone process resulting in somatic mutations in their genome. Because of the higher mutation rate compared to the nuclear genome, mitochondrial mutations have been used to track cellular lineage, particularly using single-cell sequencing that measures mitochondrial mutations in individual cells. However, existing methods to infer the cell lineage tree from mitochondrial mutations do not model "heteroplasmy," which is the presence of multiple mitochondrial clones with distinct sets of mutations in an individual cell. Single-cell sequencing data thus provide a mixture of the mitochondrial clones in individual cells, with the ancestral relationships between these clones described by a mitochondrial clone tree. While deconvolution of somatic mutations from a mixture of evolutionarily related genomes has been extensively studied in the context of bulk sequencing of cancer tumor samples, the problem of mitochondrial deconvolution has the additional constraint that the mitochondrial clone tree must be concordant with the cell lineage tree.

RESULTS

We formalize the problem of inferring a concordant pair of a mitochondrial clone tree and a cell lineage tree from single-cell sequencing data as the Nested Perfect Phylogeny Mixture (NPPM) problem. We derive a combinatorial characterization of the solutions to the NPPM problem, and formulate an algorithm, MERLIN, to solve this problem exactly using a mixed integer linear program. We show on simulated data that MERLIN outperforms existing methods that do not model mitochondrial heteroplasmy nor the concordance between the mitochondrial clone tree and the cell lineage tree. We use MERLIN to analyze single-cell whole-genome sequencing data of 5220 cells of a gastric cancer cell line and show that MERLIN infers a more biologically plausible cell lineage tree and mitochondrial clone tree compared to existing methods.

AVAILABILITY AND IMPLEMENTATION

https://github.com/raphael-group/MERLIN.

Maximum likelihood phylogeographic inference of cell motility and cell division from spatial lineage tracing data

MOTIVATION

Recently developed spatial lineage tracing technologies induce somatic mutations at specific genomic loci in a population of growing cells and then measure these mutations in the sampled cells along with the physical locations of the cells. These technologies enable high-throughput studies of developmental processes over space and time. However, these applications rely on accurate reconstruction of a spatial cell lineage tree describing both past cell divisions and cell locations. Spatial lineage trees are related to phylogeographic models that have been well-studied in the phylogenetics literature. We demonstrate that standard phylogeographic models based on Brownian motion are inadequate to describe the spatial symmetric displacement (SD) of cells during cell division.

RESULTS

We introduce a new model-the SD model for cell motility that includes symmetric displacements of daughter cells from the parental cell followed by independent diffusion of daughter cells. We show that this model more accurately describes the locations of cells in a real spatial lineage tracing of mouse embryonic stem cells. Combining the spatial SD model with an evolutionary model of DNA mutations, we obtain a phylogeographic model for spatial lineage tracing. Using this model, we devise a maximum likelihood framework-MOLLUSC (Maximum Likelihood Estimation Of Lineage and Location Using Single-Cell Spatial Lineage tracing Data)-to co-estimate time-resolved branch lengths, spatial diffusion rate, and mutation rate. On both simulated and real data, we show that MOLLUSC accurately estimates all parameters. In contrast, the Brownian motion model overestimates spatial diffusion rate in all test cases. In addition, the inclusion of spatial information improves accuracy of branch length estimation compared to sequence data alone. On real data, we show that spatial information has more signal than sequence data for branch length estimation, suggesting augmenting lineage tracing technologies with spatial information is useful to overcome the limitations of genome-editing in developmental systems.

AVAILABILITY AND IMPLEMENTATION

The python implementation of MOLLUSC is available at https://github.com/raphael-group/MOLLUSC.

SCTC: inference of developmental potential from single-cell transcriptional complexity

Inferring the developmental potential of single cells from scRNA-Seq data and reconstructing the pseudo-temporal path of cell development are fundamental but challenging tasks in single-cell analysis. Although single-cell transcriptional diversity (SCTD) measured by the number of expressed genes per cell has been widely used as a hallmark of developmental potential, it may lead to incorrect estimation of differentiation states in some cases where gene expression does not decrease monotonously during the development process. In this study, we propose a novel metric called single-cell transcriptional complexity (SCTC), which draws on insights from the economic complexity theory and takes into account the sophisticated structure information of scRNA-Seq count matrix. We show that SCTC characterizes developmental potential more accurately than SCTD, especially in the early stages of development where cells typically have lower diversity but higher complexity than those in the later stages. Based on the SCTC, we provide an unsupervised method for accurate, robust, and transferable inference of single-cell pseudotime. Our findings suggest that the complexity emerging from the interplay between cells and genes determines the developmental potential, providing new insights into the understanding of biological development from the perspective of complexity theory.

The Mechanics of Building Functional Organs

Organ morphogenesis is multifaceted, multiscale, and fundamentally a robust process. Despite the complex and dynamic nature of embryonic development, organs are built with reproducible size, shape, and function, allowing them to support organismal growth and life. This striking reproducibility of tissue form exists because morphogenesis is not entirely hardwired. Instead, it is an emergent product of mechanochemical information flow, operating across spatial and temporal scales-from local cellular deformations to organ-scale form and function, and back. In this review, we address the mechanical basis of organ morphogenesis, as understood by observations and experiments in living embryos. To this end, we discuss how mechanical information controls the emergence of a highly conserved set of structural motifs that shape organ architectures across the animal kingdom: folds and loops, tubes and lumens, buds, branches, and networks. Moving forward, we advocate for a holistic conceptual framework for the study of organ morphogenesis, which rests on an interdisciplinary toolkit and brings the embryo center stage.

Sequential emergence and contraction of epithelial subtypes in the prenatal human choroid plexus revealed by a stem cell model

Despite the major roles of choroid plexus epithelial cells (CPECs) in brain homeostasis and repair, their developmental lineage and diversity remain undefined. In simplified differentiations from human pluripotent stem cells, derived CPECs (dCPECs) displayed canonical properties and dynamic multiciliated phenotypes that interacted with Aβ uptake. Single dCPEC transcriptomes over time correlated well with human organoid and fetal CPECs, while pseudotemporal and cell cycle analyses highlighted the direct CPEC origin from neuroepithelial cells. In addition, time series analyses defined metabolic (type 1) and ciliogenic dCPECs (type 2) at early timepoints, followed by type 1 diversification into anabolic-secretory (type 1a) and catabolic-absorptive subtypes (type 1b) as type 2 cells contracted. These temporal patterns were then confirmed in independent derivations and mapped to prenatal stages using human tissues. In addition to defining the prenatal lineage of human CPECs, these findings suggest new dynamic models of ChP support for the developing human brain.

Resolving tumor evolution: a phylogenetic approach

The evolutionary dynamics of cancer, characterized by its profound heterogeneity, demand sophisticated tools for a holistic understanding. This review delves into tumor phylogenetics, an essential approach bridging evolutionary biology with oncology, offering unparalleled insights into cancer's evolutionary trajectory. We provide an overview of the workflow, encompassing study design, data acquisition, and phylogeny reconstruction. Notably, the integration of diverse data sets emerges as a transformative step, enhancing the depth and breadth of evolutionary insights. With this integrated perspective, tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Ascidian embryonic cells with properties of neural-crest cells and neuromesodermal progenitors of vertebrates

Neural-crest cells and neuromesodermal progenitors (NMPs) are multipotent cells that are important for development of vertebrate embryos. In embryos of ascidians, which are the closest invertebrate relatives of vertebrates, several cells located at the border between the neural plate and the epidermal region have neural-crest-like properties; hence, the last common ancestor of ascidians and vertebrates may have had ancestral cells similar to neural-crest cells. However, these ascidian neural-crest-like cells do not produce cells that are commonly of mesodermal origin. Here we showed that a cell population located in the lateral region of the neural plate has properties resembling those of vertebrate neural-crest cells and NMPs. Among them, cells with Tbx6-related expression contribute to muscle near the tip of the tail region and cells with Sox1/2/3 expression give rise to the nerve cord. These observations and cross-species transcriptome comparisons indicate that these cells have properties similar to those of NMPs. Meanwhile, transcription factor genes Dlx.b, Zic-r.b and Snai, which are reminiscent of a gene circuit in vertebrate neural-crest cells, are involved in activation of Tbx6-related.b. Thus, the last common ancestor of ascidians and vertebrates may have had cells with properties of neural-crest cells and NMPs and such ancestral cells may have produced cells commonly of ectodermal and mesodermal origins.

An amphioxus neurula stage cell atlas supports a complex scenario for the emergence of vertebrate head mesoderm

The emergence of new structures can often be linked to the evolution of novel cell types that follows the rewiring of developmental gene regulatory subnetworks. Vertebrates are characterized by a complex body plan compared to the other chordate clades and the question remains of whether and how the emergence of vertebrate morphological innovations can be related to the appearance of new embryonic cell populations. We previously proposed, by studying mesoderm development in the cephalochordate amphioxus, a scenario for the evolution of the vertebrate head mesoderm. To further test this scenario at the cell population level, we used scRNA-seq to construct a cell atlas of the amphioxus neurula, stage at which the main mesodermal compartments are specified. Our data allowed us to validate the presence of a prechordal-plate like territory in amphioxus. Additionally, the transcriptomic profile of somite cell populations supports the homology between specific territories of amphioxus somites and vertebrate cranial/pharyngeal and lateral plate mesoderm. Finally, our work provides evidence that the appearance of the specific mesodermal structures of the vertebrate head was associated to both segregation of pre-existing cell populations, and co-option of new genes for the control of myogenesis.

Establishing a conceptual framework for holistic cell states and state transitions

Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types.

Novel cell states arise in embryonic cells devoid of key reprogramming factors

The capacity for embryonic cells to differentiate relies on a large-scale reprogramming of the oocyte and sperm nucleus into a transient totipotent state. In zebrafish, this reprogramming step is achieved by the pioneer factors Nanog, Pou5f3, and Sox19b (NPS). Yet, it remains unclear whether cells lacking this reprogramming step are directed towards wild type states or towards novel developmental canals in the Waddington landscape of embryonic development. Here we investigate the developmental fate of embryonic cells mutant for NPS by analyzing their single-cell gene expression profiles. We find that cells lacking the first developmental reprogramming steps can acquire distinct cell states. These states are manifested by gene expression modules that result from a failure of nuclear reprogramming, the persistence of the maternal program, and the activation of somatic compensatory programs. As a result, most mutant cells follow new developmental canals and acquire new mixed cell states in development. In contrast, a group of mutant cells acquire primordial germ cell-like states, suggesting that NPS-dependent reprogramming is dispensable for these cell states. Together, these results demonstrate that developmental reprogramming after fertilization is required to differentiate most canonical developmental programs, and loss of the transient totipotent state canalizes embryonic cells into new developmental states in vivo.

An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

Spiders are a diverse order of chelicerates that diverged from other arthropods over 500 million years ago. Research on spider embryogenesis, particularly studies using the common house spider Parasteatoda tepidariorum, has made important contributions to understanding the evolution of animal development, including axis formation, segmentation, and patterning. However, we lack knowledge about the cells that build spider embryos, their gene expression profiles and fate. Single-cell transcriptomic analyses have been revolutionary in describing these complex landscapes of cellular genetics in a range of animals. Therefore, we carried out single-cell RNA sequencing of P. tepidariorum embryos at stages 7, 8 and 9, which encompass the establishment and patterning of the body plan, and initial differentiation of many tissues and organs. We identified 20 cell clusters, from 18.5 k cells, which were marked by many developmental toolkit genes, as well as a plethora of genes not previously investigated. We found differences in the cell cycle transcriptional signatures, suggestive of different proliferation dynamics, which related to distinctions between endodermal and some mesodermal clusters, compared with ectodermal clusters. We identified many Hox genes as markers of cell clusters, and Hox gene ohnologs were often present in different clusters. This provided additional evidence of sub- and/or neo-functionalisation of these important developmental genes after the whole genome duplication in an arachnopulmonate ancestor (spiders, scorpions, and related orders). We also examined the spatial expression of marker genes for each cluster to generate a comprehensive cell atlas of these embryonic stages. This revealed new insights into the cellular basis and genetic regulation of head patterning, hematopoiesis, limb development, gut development, and posterior segmentation. This atlas will serve as a platform for future analysis of spider cell specification and fate, and studying the evolution of these processes among animals at cellular resolution.

The future of rapid and automated single-cell data analysis using reference mapping

As the number of single-cell datasets continues to grow rapidly, workflows that map new data to well-curated reference atlases offer enormous promise for the biological community. In this perspective, we discuss key computational challenges and opportunities for single-cell reference-mapping algorithms. We discuss how mapping algorithms will enable the integration of diverse datasets across disease states, molecular modalities, genetic perturbations, and diverse species and will eventually replace manual and laborious unsupervised clustering pipelines.

A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Unsolved morphogenesis problems and the hidden order

In this work, the morphogenesis mechanisms are considered from the complexity perspective. It is shown that both morphogenesis and the functioning of organs should be unstable in the case of short-range interaction potentials. The repeatability of forms during evolution is a strong argument for its directionality. The formation of organs during evolution can occur only in the presence of a priori information about the structure of such an organ. The focus of the discussion is not merely on constraining potential possibilities but on the concept of directed evolution itself. A morphogenesis model was constructed based on nontrivial quantum effects. These interaction effects between biologically important molecules ensure the accurate synthesis of cells, tissues, and organs.

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

A dynamical perspective: moving towards mechanism in single-cell transcriptomics

As the field of single-cell transcriptomics matures, research is shifting focus from phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the gene regulation underneath. This perspective considers the value of capturing dynamical information at single-cell resolution for gaining mechanistic insight; reviews the available technologies for recording and inferring temporal information in single cells; and explores whether better dynamical resolution is sufficient to adequately capture the causal relationships driving complex biological systems. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

The chromatin accessibility dynamics during cell fate specifications in zebrafish early embryogenesis

Chromatin accessibility plays a critical role in the regulation of cell fate decisions. Although gene expression changes have been extensively profiled at the single-cell level during early embryogenesis, the dynamics of chromatin accessibility at cis-regulatory elements remain poorly studied. Here, we used a plate-based single-cell ATAC-seq method to profile the chromatin accessibility dynamics of over 10 000 nuclei from zebrafish embryos. We investigated several important time points immediately after zygotic genome activation (ZGA), covering key developmental stages up to dome. The results revealed key chromatin signatures in the first cell fate specifications when cells start to differentiate into enveloping layer (EVL) and yolk syncytial layer (YSL) cells. Finally, we uncovered many potential cell-type specific enhancers and transcription factor motifs that are important for the cell fate specifications.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Cell-type-specific mRNA transcription and degradation kinetics in zebrafish embryogenesis from metabolically labeled single-cell RNA-seq

During embryonic development, pluripotent cells assume specialized identities by adopting particular gene expression profiles. However, systematically dissecting the relative contributions of mRNA transcription and degradation to shaping those profiles remains challenging, especially within embryos with diverse cellular identities. Here, we combine single-cell RNA-Seq and metabolic labeling to capture temporal cellular transcriptomes of zebrafish embryos where newly-transcribed (zygotic) and pre-existing (maternal) mRNA can be distinguished. We introduce kinetic models to quantify mRNA transcription and degradation rates within individual cell types during their specification. These models reveal highly varied regulatory rates across thousands of genes, coordinated transcription and destruction rates for many transcripts, and link differences in degradation to specific sequence elements. They also identify cell-type-specific differences in degradation, namely selective retention of maternal transcripts within primordial germ cells and enveloping layer cells, two of the earliest specified cell types. Our study provides a quantitative approach to study mRNA regulation during a dynamic spatio-temporal response.

Single Cell RNA Sequencing Provides Clues for the Developmental Genetic Basis of Syngnathidae's Evolutionary Adaptations

Seahorses, pipefishes, and seadragons are fishes from the family Syngnathidae that have evolved extraordinary traits including male pregnancy, elongated snouts, loss of teeth, and dermal bony armor. The developmental genetic and cellular changes that led to the evolution of these traits are largely unknown. Recent syngnathid genomes revealed suggestive gene content differences and provide the opportunity for detailed genetic analyses. We created a single cell RNA sequencing atlas of Gulf pipefish embryos to understand the developmental basis of four traits: derived head shape, toothlessness, dermal armor, and male pregnancy. We completed marker gene analyses, built genetic networks, and examined spatial expression of select genes. We identified osteochondrogenic mesenchymal cells in the elongating face that express regulatory genes bmp4, sfrp1a, and prdm16. We found no evidence for tooth primordia cells, and we observed re-deployment of osteoblast genetic networks in developing dermal armor. Finally, we found that epidermal cells expressed nutrient processing and environmental sensing genes, potentially relevant for the brooding environment. The examined pipefish evolutionary innovations are composed of recognizable cell types, suggesting derived features originate from changes within existing gene networks. Future work addressing syngnathid gene networks across multiple stages and species is essential for understanding how their novelties evolved.

CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning

Circular RNAs (circRNAs) are a crucial yet relatively unexplored class of transcripts known for their tissue- and cell-type-specific expression patterns. Despite the advances in single-cell and spatial transcriptomics, these technologies face difficulties in effectively profiling circRNAs due to inherent limitations in circRNA sequencing efficiency. To address this gap, a deep learning model, CIRI-deep, is presented for comprehensive prediction of circRNA regulation on diverse types of RNA-seq data. CIRI-deep is trained on an extensive dataset of 25 million high-confidence circRNA regulation events and achieved high performances on both test and leave-out data, ensuring its accuracy in inferring differential events from RNA-seq data. It is demonstrated that CIRI-deep and its adapted version enable various circRNA analyses, including cluster- or region-specific circRNA detection, BSJ ratio map visualization, and trans and cis feature importance evaluation. Collectively, CIRI-deep's adaptability extends to all major types of RNA-seq datasets including single-cell and spatial transcriptomic data, which will undoubtedly broaden the horizons of circRNA research.

Elongation of the developing spinal cord is driven by Oct4-type transcription factor-mediated regulation of retinoic acid signaling in zebrafish embryos

BACKGROUND

Elongation of the spinal cord is dependent on neural development from neuromesodermal progenitors in the tail bud. We previously showed the involvement of the Oct4-type gene, pou5f3, in this process in zebrafish mainly by dominant-interference gene induction, but, to compensate for the limitation of this transgene approach, mutant analysis was indispensable. pou5f3 involvement in the signaling pathways was another unsolved question.

RESULTS

We examined the phenotypes of pou5f3 mutants and the effects of Pou5f3 activation by the tamoxifen-ERT2 system in the posterior neural tube, together confirming the involvement of pou5f3. The reporter assays using P19 cells implicated tail bud-related transcription factors in pou5f3 expression. Regulation of tail bud development by retinoic acid (RA) signaling was confirmed by treatment of embryos with RA and the synthesis inhibitor, and in vitro reporter assays further showed that RA signaling regulated pou5f3 expression. Importantly, the expression of the RA degradation enzyme gene, cyp26a1, was down-regulated in embryos with disrupted pou5f3 activity.

CONCLUSIONS

The involvement of pou5f3 in spinal cord extension was supported by using mutants and the gain-of-function approach. Our findings further suggest that pou5f3 regulates the RA level, contributing to neurogenesis in the posterior neural tube.

Maximum Likelihood Inference of Time-scaled Cell Lineage Trees with Mixed-type Missing Data

Recent dynamic lineage tracing technologies combine CRISPR-based genome editing with single-cell sequencing to track cell divisions during development. A key computational problem in dynamic lineage tracing is to infer a cell lineage tree from the measured CRISPR-induced mutations. Three features of dynamic lineage tracing data distinguish this problem from standard phylogenetic tree inference. First, the CRISPR-editing process modifies a genomic location exactly once. This non-modifiable property is not well described by the time-reversible models commonly used in phylogenetics. Second, as a consequence of non-modifiability, the number of mutations per time unit decreases over time. Third, CRISPR-based genome-editing and single-cell sequencing results in high rates of both heritable and non-heritable (dropout) missing data. To model these features, we introduce the Probabilistic Mixed-type Missing (PMM) model. We describe an algorithm, LAML (Lineage Analysis via Maximum Likelihood), to search for the maximum likelihood (ML) tree under the PMM model. LAML combines an Expectation Maximization (EM) algorithm with a heuristic tree search to jointly estimate tree topology, branch lengths and missing data parameters. We derive a closed-form solution for the M-step in the case of no heritable missing data, and a block coordinate ascent approach in the general case which is more efficient than the standard General Time Reversible (GTR) phylogenetic model. On simulated data, LAML infers more accurate tree topologies and branch lengths than existing methods, with greater advantages on datasets with higher ratios of heritable to non-heritable missing data. We show that LAML provides unbiased time-scaled estimates of branch lengths. In contrast, we demonstrate that maximum parsimony methods for lineage tracing data not only underestimate branch lengths, but also yield branch lengths which are not proportional to time, due to the nonlinear decay in the number of mutations on branches further from the root. On lineage tracing data from a mouse model of lung adenocarcinoma, we show that LAML infers phylogenetic distances that are more concordant with gene expression data compared to distances derived from maximum parsimony. The LAML tree topology is more plausible than existing published trees, with fewer total cell migrations between distant metastases and fewer reseeding events where cells migrate back to the primary tumor. Crucially, we identify three distinct time epochs of metastasis progression, which includes a burst of metastasis events to various anatomical sites during a single month.

Zebrafish and cellular models of SELENON-Related Myopathy exhibit novel embryonic and metabolic phenotypes

SELENON-Related Myopathy (SELENON-RM) is a rare congenital myopathy caused by mutations of the SELENON gene characterized by axial muscle weakness and progressive respiratory insufficiency. Muscle histopathology commonly includes multiminicores or a dystrophic pattern but is often non-specific. The SELENON gene encodes selenoprotein N (SelN), a selenocysteine-containing redox enzyme located in the endo/sarcoplasmic reticulum membrane where it colocalizes with mitochondria-associated membranes. However, the molecular mechanism(s) by which SelN deficiency causes SELENON-RM are undetermined. A hurdle is the lack of cellular and animal models that show assayable phenotypes. Here we report deep-phenotyping of SelN-deficient zebrafish and muscle cells. SelN-deficient zebrafish exhibit changes in embryonic muscle function and swimming activity in larvae. Analysis of single cell RNAseq data in a zebrafish embryo-atlas revealed coexpression between selenon and genes involved in glutathione redox pathway. SelN-deficient zebrafish and mouse myoblasts exhibit changes in glutathione and redox homeostasis, suggesting a direct relationship with SelN function. We report changes in metabolic function abnormalities in SelN-null myotubes when compared to WT. These results suggest that SelN has functional roles during zebrafish early development and myoblast metabolism.

MDIC3: Matrix decomposition to infer cell-cell communication

Crosstalk among cells is vital for maintaining the biological function and intactness of systems. Most existing methods for investigating cell-cell communications are based on ligand-receptor (L-R) expression, and they focus on the study between two cells. Thus, the final communication inference results are particularly sensitive to the completeness and accuracy of the prior biological knowledge. Because existing L-R research focuses mainly on humans, most existing methods can only examine cell-cell communication for humans. As far as we know, there is currently no effective method to overcome this species limitation. Here, we propose MDIC3 (matrix decomposition to infer cell-cell communication), an unsupervised tool to investigate cell-cell communication in any species, and the results are not limited by specific L-R pairs or signaling pathways. By comparing it with existing methods for the inference of cell-cell communication, MDIC3 obtained better performance in both humans and mice.