Mapping single-cell atlases throughout Metazoa unravels cell type evolution

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.

Spatially resolved cell atlas of the teleost telencephalon and deep homology of the vertebrate forebrain

The telencephalon has undergone remarkable diversification and expansion throughout vertebrate evolution, exhibiting striking variations in structural and functional complexity. Nevertheless, fundamental features are shared across vertebrate taxa, such as the presence of distinct regions including the pallium, subpallium, and olfactory structures. Teleost fishes have a uniquely "everted" telencephalon, which has confounded comparisons of their brain regions to other vertebrates. Here we combine spatial transcriptomics and single nucleus RNA-sequencing to generate a spatially-resolved transcriptional atlas of the Mchenga conophorus cichlid fish telencephalon. We then compare cell-types and anatomical regions in the cichlid telencephalon with those in amphibians, reptiles, birds, and mammals. We uncover striking transcriptional similarities between cell-types in the fish telencephalon and subpallial, hippocampal, and cortical cell-types in tetrapods, and find support for partial eversion of the teleost telencephalon. Ultimately, our work lends new insights into the organization and evolution of conserved cell-types and regions in the vertebrate forebrain.

Single-nucleus transcriptional and chromatin accessible profiles reveal critical cell types and molecular architecture underlying chicken sex determination

INTRODUCTION

Understanding the sex determination mechanisms in birds has great significance for the biological sciences and production in the poultry industry. Sex determination in chickens is a complex process that involves fate decisions of supporting cells such as granulosa or Sertoli cells. However, a systematic understanding of the genetic regulation and cell commitment process underlying sex determination in chickens is still lacking.

OBJECTIVES

We aimed to dissect the molecular characteristics associated with sex determination in the gonads of chicken embryos.

METHODS

Single-nucleus RNA-seq (snRNA-seq) and ATAC-seq (snATAC-seq) analysis were conducted on the gonads of female and male chickens at embryonic day 3.5 (E3.5), E4.5, and E5.5.

RESULTS

Here, we provided a time-course transcriptional and chromatin accessible profiling of gonads during chicken sex determination at single-cell resolution. We uncovered differences in cell composition and developmental trajectories between female and male gonads and found that the divergence of transcription and accessibility in gonadal cells first emerged at E5.5. Furthermore, we revealed key cell-type-specific transcription factors (TFs) and regulatory networks that drive lineage commitment. Sex determination signaling pathways, dominated by BMP signaling, are preferentially activated in males during gonadal development. Further pseudotime analysis of the supporting cells indicated that granulosa cells were regulated mainly by the TEAD gene family and that Sertoli cells were driven by the DMRT1 regulons. Cross-species analysis suggested high conservation of both cell types and cell-lineage-specific TFs across the six vertebrates.

CONCLUSIONS

Overall, our study will contribute to accelerating the development of sex manipulation technology in the poultry industry and the application of chickens as a unique model for studying cell fate decisions.

Comparative single cell analysis reveals complex patterns of cell type and cell signaling innovations at the fetal-maternal interface

The decidual-placental interface is one of the most diverse and rapidly evolving tissues in mammals. Its origin as a chimeric fetal-maternal tissue poses a unique evolutionary puzzle. We present single-cell RNA sequencing atlases from the fetal-maternal interfaces of the opossum, a marsupial, the Malagasy common tenrec, an afrotherian with primitive reproductive features, and mouse, guinea pig, and human. Invasive trophoblast shares a common transcriptomic signature across eutherians, which we argue represents a cell type family that radiated following the evolution of hemochorial placentation. We find evidence that the eutherian decidual stromal cell evolved stepwise from a predecidual state retained in Tenrec , followed by a second decidual cell type originating in Boreoeutheria with endocrine characteristics. We reconstruct ligand-receptor signaling to test evolutionary hypotheses at scale. Novel trophoblast and decidual cell types display strong integration into signaling networks compared to other cells. Additionally, we find consistent disambiguation between fetal and maternal signaling. Using phylogenetic analysis, we infer the cell-cell signaling network of the Placental common ancestor, and identify increased rates of signaling evolution in Euarchontoglires. Together, our findings reveal novel cell type identities and cell signaling dynamics at the mammalian fetal-maternal interface.

Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells

Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can reveal links between cellular gene expression and the evolution of cell functions, features, and phenotypes. These comparisons evoke evolutionary histories, as depicted by phylogenetic trees, that define relationships between species, genes, and cells. This Essay considers each of these in turn, laying out challenges and solutions derived from a phylogenetic comparative approach and relating these solutions to previously proposed methods for the pairwise alignment of cellular dimensional maps. This Essay contends that species trees, gene trees, cell phylogenies, and cell lineages can all be reconciled as descriptions of the same concept-the tree of cellular life. By integrating phylogenetic approaches into scRNA-seq analyses, challenges for building informed comparisons across species can be overcome, and hypotheses about gene and cell evolution can be robustly tested.

Single-cell transcriptomics reveals evolutionary reconfiguration of embryonic cell fate specification in the sea urchin Heliocidaris erythrogramma

Altered regulatory interactions during development likely underlie a large fraction of phenotypic diversity within and between species, yet identifying specific evolutionary changes remains challenging. Analysis of single-cell developmental transcriptomes from multiple species provides a powerful framework for unbiased identification of evolutionary changes in developmental mechanisms. Here, we leverage a "natural experiment" in developmental evolution in sea urchins, where a major life history switch recently evolved in the lineage leading to Heliocidaris erythrogramma, precipitating extensive changes in early development. Comparative analyses of scRNA-seq developmental time courses from H. erythrogramma and Lytechinus variegatus (representing the derived and ancestral states respectively) reveals numerous evolutionary changes in embryonic patterning. The earliest cell fate specification events, and the primary signaling center are co-localized in the ancestral dGRN but remarkably, in H. erythrogramma they are spatially and temporally separate. Fate specification and differentiation are delayed in most embryonic cell lineages, although in some cases, these processes are conserved or even accelerated. Comparative analysis of regulator-target gene co-expression is consistent with many specific interactions being preserved but delayed in H. erythrogramma, while some otherwise widely conserved interactions have likely been lost. Finally, specific patterning events are directly correlated with evolutionary changes in larval morphology, suggesting that they are directly tied to the life history shift. Together, these findings demonstrate that comparative scRNA-seq developmental time courses can reveal a diverse set of evolutionary changes in embryonic patterning and provide an efficient way to identify likely candidate regulatory interactions for subsequent experimental validation.

Comparative Single Cell Analysis of Transcriptional Bursting Reveals the Role of Genome Organization on de novo Transcript Origination

Spermatogenesis is a key developmental process underlying the origination of newly evolved genes. However, rapid cell type-specific transcriptomic divergence of the Drosophila germline has posed a significant technical barrier for comparative single-cell RNA-sequencing (scRNA-Seq) studies. By quantifying a surprisingly strong correlation between species-and cell type-specific divergence in three closely related Drosophila species, we apply a simple statistical procedure to identify a core set of 198 genes that are highly predictive of cell type identity while remaining robust to species-specific differences that span over 25-30 million years of evolution. We then utilize cell type classifications based on the 198-gene set to show how transcriptional divergence in cell type increases throughout spermatogenic developmental time, contrasting with traditional hourglass models of whole-organism development. With these cross-species cell type classifications, we then investigate the influence of genome organization on the molecular evolution of spermatogenesis vis-a-vis transcriptional bursting. We first demonstrate how mechanistic control of pre-meiotic transcription is achieved by altering transcriptional burst size while post-meiotic control is exerted via altered bursting frequency. We then report how global differences in autosomal vs. X chromosomal transcription likely arise in a developmental stage preceding full testis organogenesis by showing evolutionarily conserved decreases in X-linked transcription bursting kinetics in all examined somatic and germline cell types. Finally, we provide evidence supporting the cultivator model of de novo gene origination by demonstrating how the appearance of newly evolved testis-specific transcripts potentially provides short-range regulation of the transcriptional bursting properties of neighboring genes during key stages of spermatogenesis.

Reconstruction of macroglia and adult neurogenesis evolution through cross-species single-cell transcriptomic analyses

Macroglia fulfill essential functions in the adult vertebrate brain, producing and maintaining neurons and regulating neuronal communication. However, we still know little about their emergence and diversification. We used the zebrafish D. rerio as a distant vertebrate model with moderate glial diversity as anchor to reanalyze datasets covering over 600 million years of evolution. We identify core features of adult neurogenesis and innovations in the mammalian lineage with a potential link to the rarity of radial glia-like cells in adult humans. Our results also suggest that functions associated with astrocytes originated in a multifunctional cell type fulfilling both neural stem cell and astrocytic functions before these diverged. Finally, we identify conserved elements of macroglial cell identity and function and their time of emergence during evolution.

Spatially resolved single-cell atlas of ascidian endostyle provides insight into the origin of vertebrate pharyngeal organs

The pharyngeal endoderm, an innovation of deuterostome ancestors, contributes to pharyngeal development by influencing the patterning and differentiation of pharyngeal structures in vertebrates; however, the evolutionary origin of the pharyngeal organs in vertebrates is largely unknown. The endostyle, a distinct pharyngeal organ exclusively present in basal chordates, represents a good model for understanding pharyngeal organ origins. Using Stereo-seq and single-cell RNA sequencing, we constructed aspatially resolved single-cell atlas for the endostyle of the ascidian Styela clava. We determined the cell composition of the hemolymphoid region, which illuminates a mixed ancestral structure for the blood and lymphoid system. In addition, we discovered a cluster of hair cell-like cells in zone 3, which has transcriptomic similarity with the hair cells of the vertebrate acoustico-lateralis system. These findings reshape our understanding of the pharynx of the basal chordate and provide insights into the evolutionary origin of multiplexed pharyngeal organs.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

Single cell atlas of Xenoturbella bocki highlights limited cell-type complexity

Phylogenetic analyses over the last two decades have united a few small, and previously orphan clades, the nematodermatids, acoels and xenoturbelids, into the phylum Xenacoelomorpha. Some phylogenetic analyses support a sister relationship between Xenacoelomorpha and Ambulacraria (Xenambulacraria), while others suggest that Xenacoelomorpha may be sister to the rest of the Bilateria (Nephrozoa). An understanding of the cell type complements of Xenacoelomorphs is essential to assessing these alternatives as well as to our broader understanding of bilaterian cell type evolution. Employing whole organism single-cell RNA-seq in the marine xenacoelomorph worm Xenoturbella bocki, we show that Xenambulacrarian nerve nets share regulatory features and a peptidergic identity with those found in cnidarians and protostomes and more broadly share muscle and gland cell similarities with other metazoans. Taken together, these data are consistent with broad homologies of animal gland, muscle, and neurons as well as more specific affinities between Xenoturbella and acoel gut and epidermal tissues, consistent with the monophyly of Xenacoelomorpha.

Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities

Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.

Plant biotechnology research with single-cell transcriptome: recent advancements and prospects

KEY MESSAGE

Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.

Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN

Analysis of single-cell datasets generated from diverse organisms offers unprecedented opportunities to unravel fundamental evolutionary processes of conservation and diversification of cell types. However, interspecies genomic differences limit the joint analysis of cross-species datasets to homologous genes. Here we present SATURN, a deep learning method for learning universal cell embeddings that encodes genes' biological properties using protein language models. By coupling protein embeddings from language models with RNA expression, SATURN integrates datasets profiled from different species regardless of their genomic similarity. SATURN can detect functionally related genes coexpressed across species, redefining differential expression for cross-species analysis. Applying SATURN to three species whole-organism atlases and frog and zebrafish embryogenesis datasets, we show that SATURN can effectively transfer annotations across species, even when they are evolutionarily remote. We also demonstrate that SATURN can be used to find potentially divergent gene functions between glaucoma-associated genes in humans and four other species.

Integrating single-cell RNA-seq datasets with substantial batch effects

Integration of single-cell RNA-sequencing (scRNA-seq) datasets has become a standard part of the analysis, with conditional variational autoencoders (cVAE) being among the most popular approaches. Increasingly, researchers are asking to map cells across challenging cases such as cross-organs, species, or organoids and primary tissue, as well as different scRNA-seq protocols, including single-cell and single-nuclei. Current computational methods struggle to harmonize datasets with such substantial differences, driven by technical or biological variation. Here, we propose to address these challenges for the popular cVAE-based approaches by introducing and comparing a series of regularization constraints. The two commonly used strategies for increasing batch correction in cVAEs, that is Kullback-Leibler divergence (KL) regularization strength tuning and adversarial learning, suffer from substantial loss of biological information. Therefore, we adapt, implement, and assess alternative regularization strategies for cVAEs and investigate how they improve batch effect removal or better preserve biological variation, enabling us to propose an optimal cVAE-based integration strategy for complex systems. We show that using a VampPrior instead of the commonly used Gaussian prior not only improves the preservation of biological variation but also unexpectedly batch correction. Moreover, we show that our implementation of cycle-consistency loss leads to significantly better biological preservation than adversarial learning implemented in the previously proposed GLUE model. Additionally, we do not recommend relying only on the KL regularization strength tuning for increasing batch correction, as it removes both biological and batch information without discriminating between the two. Based on our findings, we propose a new model that combines VampPrior and cycle-consistency loss. We show that using it for datasets with substantial batch effects improves downstream interpretation of cell states and biological conditions. To ease the use of the newly proposed model, we make it available in the scvi-tools package as an external model named sysVI. Moreover, in the future, these regularization techniques could be added to other established cVAE-based models to improve the integration of datasets with substantial batch effects.

Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data

The origin and evolution of cell types has emerged as a key topic in evolutionary biology. Driven by rapidly accumulating single-cell datasets, recent attempts to infer cell type evolution have largely been limited to pairwise comparisons because we lack approaches to build cell phylogenies using model-based approaches. Here we approach the challenges of applying explicit phylogenetic methods to single-cell data by using principal components as phylogenetic characters. We infer a cell phylogeny from a large, comparative single-cell dataset of eye cells from five distantly related mammals. Robust cell type clades enable us to provide a phylogenetic, rather than phenetic, definition of cell type, allowing us to forgo marker genes and phylogenetically classify cells by topology. We further observe evolutionary relationships between diverse vessel endothelia and identify the myelinating and non-myelinating Schwann cells as sister cell types. Finally, we examine principal component loadings and describe the gene expression dynamics underlying the function and identity of cell type clades that have been conserved across the five species. A cell phylogeny provides a rigorous framework towards investigating the evolutionary history of cells and will be critical to interpret comparative single-cell datasets that aim to ask fundamental evolutionary questions.

Adult sex change leads to extensive forebrain reorganization in clownfish

Sexual differentiation of the brain occurs in all major vertebrate lineages but is not well understood at a molecular and cellular level. Unlike most vertebrates, sex-changing fishes have the remarkable ability to change reproductive sex during adulthood in response to social stimuli, offering a unique opportunity to understand mechanisms by which the nervous system can initiate and coordinate sexual differentiation. This study explores sexual differentiation of the forebrain using single nucleus RNA-sequencing in the anemonefish Amphiprion ocellaris, producing the first cellular atlas of a sex-changing brain. We uncover extensive sex differences in cell type-specific gene expression, relative proportions of cells, baseline neuronal excitation, and predicted inter-neuronal communication. Additionally, we identify the cholecystokinin, galanin, and estrogen systems as central molecular axes of sexual differentiation. Supported by these findings, we propose a model of neurosexual differentiation in the conserved vertebrate social decision-making network spanning multiple subtypes of neurons and glia, including neuronal subpopulations within the preoptic area that are positioned to regulate gonadal differentiation. This work deepens our understanding of sexual differentiation in the vertebrate brain and defines a rich suite of molecular and cellular pathways that differentiate during adult sex change in anemonefish.

Molecular organization of neuronal cell types and neuromodulatory systems in the zebrafish telencephalon

The function of neuronal networks is determined not only by synaptic connectivity but also by neuromodulatory systems that broadcast information via distributed connections and volume transmission. To understand the molecular constraints that organize neuromodulatory signaling in the telencephalon of adult zebrafish, we used transcriptomics and additional approaches to delineate cell types, to determine their phylogenetic conservation, and to map the expression of marker genes at high granularity. The combinatorial expression of GPCRs and cell-type markers indicates that all neuronal cell types are subject to modulation by multiple monoaminergic systems and distinct combinations of neuropeptides. Individual cell types were associated with multiple (typically >30) neuromodulatory signaling networks but expressed only a few diagnostic GPCRs at high levels, suggesting that different neuromodulatory systems act in combination, albeit with unequal weights. These results provide a detailed map of cell types and brain areas in the zebrafish telencephalon, identify core components of neuromodulatory networks, highlight the cell-type specificity of neuropeptides and GPCRs, and begin to decipher the logic of combinatorial neuromodulation.

Species-agnostic transfer learning for cross-species transcriptomics data integration without gene orthology

Novel hypotheses in biomedical research are often developed or validated in model organisms such as mice and zebrafish and thus play a crucial role. However, due to biological differences between species, translating these findings into human applications remains challenging. Moreover, commonly used orthologous gene information is often incomplete and entails a significant information loss during gene-id conversion. To address these issues, we present a novel methodology for species-agnostic transfer learning with heterogeneous domain adaptation. We extended the cross-domain structure-preserving projection toward out-of-sample prediction. Our approach not only allows knowledge integration and translation across various species without relying on gene orthology but also identifies similar GO among the most influential genes composing the latent space for integration. Subsequently, during the alignment of latent spaces, each composed of species-specific genes, it is possible to identify functional annotations of genes missing from public orthology databases. We evaluated our approach with four different single-cell sequencing datasets focusing on cell-type prediction and compared it against related machine-learning approaches. In summary, the developed model outperforms related methods working without prior knowledge when predicting unseen cell types based on other species' data. The results demonstrate that our novel approach allows knowledge transfer beyond species barriers without the dependency on known gene orthology but utilizing the entire gene sets.

A resource of single-cell gene expression profiles in a planarian Dugesia japonica

The freshwater planarian Dugesia japonica maintains an abundant heterogeneous cell population called neoblasts, which include adult pluripotent stem cells. Thus, it is an excellent model organism for stem cell and regeneration research. Recently, many single-cell RNA sequencing (scRNA-seq) databases of several model organisms, including other planarian species, have become publicly available; these are powerful and useful resources to search for gene expression in various tissues and cells. However, the only scRNA-seq dataset for D. japonica has been limited by the number of genes detected. Herein, we collected D. japonica cells, and conducted an scRNA-seq analysis. A novel, automatic, iterative cell clustering strategy produced a dataset of 3,404 cells, which could be classified into 63 cell types based on gene expression profiles. We introduced two examples for utilizing the scRNA-seq dataset in this study using D. japonica. First, the dataset provided results consistent with previous studies as well as novel functionally relevant insights, that is, the expression of DjMTA and DjP2X-A genes in neoblasts that give rise to differentiated cells. Second, we conducted an integrative analysis of the scRNA-seq dataset and time-course bulk RNA-seq of irradiated animals, demonstrating that the dataset can help interpret differentially expressed genes captured via bulk RNA-seq. Using the R package "Seurat" and GSE223927, researchers can easily access and utilize this dataset.

Single-cell analysis of shared signatures and transcriptional diversity during zebrafish development

During development, animals generate distinct cell populations with specific identities, functions, and morphologies. We mapped transcriptionally distinct populations across 489,686 cells from 62 stages during wild-type zebrafish embryogenesis and early larval development (3-120 h post-fertilization). Using these data, we identified the limited catalog of gene expression programs reused across multiple tissues and their cell-type-specific adaptations. We also determined the duration each transcriptional state is present during development and identify unexpected long-term cycling populations. Focused clustering and transcriptional trajectory analyses of non-skeletal muscle and endoderm identified transcriptional profiles and candidate transcriptional regulators of understudied cell types and subpopulations, including the pneumatic duct, individual intestinal smooth muscle layers, spatially distinct pericyte subpopulations, and recently discovered best4+ cells. To enable additional discoveries, we make this comprehensive transcriptional atlas of early zebrafish development available through our website, Daniocell.

Marine Invertebrates One Cell at A Time: Insights from Single-Cell Analysis

Over the past decade, single-cell RNA-sequencing (scRNA-seq) has made it possible to study the cellular diversity of a broad range of organisms. Technological advances in single-cell isolation and sequencing have expanded rapidly, allowing the transcriptomic profile of individual cells to be captured. As a result, there has been an explosion of cell type atlases created for many different marine invertebrate species from across the tree of life. Our focus in this review is to synthesize current literature on marine invertebrate scRNA-seq. Specifically, we provide perspectives on key insights from scRNA-seq studies, including descriptive studies of cell type composition, how cells respond in dynamic processes such as development and regeneration, and the evolution of new cell types. Despite these tremendous advances, there also lie several challenges ahead. We discuss the important considerations that are essential when making comparisons between experiments, or between datasets from different species. Finally, we address the future of single-cell analyses in marine invertebrates, including combining scRNA-seq data with other 'omics methods to get a fuller understanding of cellular complexities. The full diversity of cell types across marine invertebrates remains unknown and understanding this diversity and evolution will provide rich areas for future study.

Conservation and contrast in cell states of echinoderm ovaries

Echinoderms produce functional gametes throughout their lifespan, in some cases exceeding 200 years. The histology and ultrastructure of echinoderm ovaries has been described but how these ovaries function and maintain the production of high-quality gametes remains a mystery. Here, we present the first single cell RNA sequencing data sets of mature ovaries from two sea urchin species (Strongylocentrotus purpuratus [Sp] and Lytechinus variegatus [Lv]), and one sea star species (Patiria miniata [Pm]). We find 14 cell states in the Sp ovary, 16 cell states in the Lv ovary and 13 cell states in the ovary of the sea star. This resource is essential to understand the structure and functional biology of the ovary in echinoderms, and better informs decisions in the utilization of in situ RNA hybridization probes selective for various cell types. We link key genes with cell clusters in validation of this approach. This resource also aids in the identification of the stem cells for prolonged and continuous gamete production, is a foundation for testing changes in the annual reproductive cycle, and is essential for understanding the evolution of reproduction of this important phylum.

Single-cell transcriptomics refuels the exploration of spiralian biology

Spiralians represent the least studied superclade of bilaterian animals, despite exhibiting the widest diversity of organisms. Although spiralians include iconic organisms, such as octopus, earthworms and clams, a lot remains to be discovered regarding their phylogeny and biology. Here, we review recent attempts to apply single-cell transcriptomics, a new pioneering technology enabling the classification of cell types and the characterisation of their gene expression profiles, to several spiralian taxa. We discuss the methodological challenges and requirements for applying this approach to marine organisms and explore the insights that can be brought by such studies, both from a biomedical and evolutionary perspective. For instance, we show that single-cell sequencing might help solve the riddle of the homology of larval forms across spiralians, but also to better characterise and compare the processes of regeneration across taxa. We highlight the capacity of single-cell to investigate the origin of evolutionary novelties, as the mollusc shell or the cephalopod visual system, but also to interrogate the conservation of the molecular fingerprint of cell types at long evolutionary distances. We hope that single-cell sequencing will open a new window in understanding the biology of spiralians, and help renew the interest for these overlooked but captivating organisms.

Enduring questions in regenerative biology and the search for answers

The potential for basic research to uncover the inner workings of regenerative processes and produce meaningful medical therapies has inspired scientists, clinicians, and patients for hundreds of years. Decades of studies using a handful of highly regenerative model organisms have significantly advanced our knowledge of key cell types and molecular pathways involved in regeneration. However, many questions remain about how regenerative processes unfold in regeneration-competent species, how they are curtailed in non-regenerative organisms, and how they might be induced (or restored) in humans. Recent technological advances in genomics, molecular biology, computer science, bioengineering, and stem cell research hold promise to collectively provide new experimental evidence for how different organisms accomplish the process of regeneration. In theory, this new evidence should inform the design of new clinical approaches for regenerative medicine. A deeper understanding of how tissues and organs regenerate will also undoubtedly impact many adjacent scientific fields. To best apply and adapt these new technologies in ways that break long-standing barriers and answer critical questions about regeneration, we must combine the deep knowledge of developmental and evolutionary biologists with the hard-earned expertise of scientists in mechanistic and technical fields. To this end, this perspective is based on conversations from a workshop we organized at the Banbury Center, during which a diverse cross-section of the regeneration research community and experts in various technologies discussed enduring questions in regenerative biology. Here, we share the questions this group identified as significant and unanswered, i.e., known unknowns. We also describe the obstacles limiting our progress in answering these questions and how expanding the number and diversity of organisms used in regeneration research is essential for deepening our understanding of regenerative capacity. Finally, we propose that investigating these problems collaboratively across a diverse network of researchers has the potential to advance our field and produce unexpected insights into important questions in related areas of biology and medicine.

oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data

SUMMARY

For model species, single-cell RNA-based cell atlases are available. A good cell atlas includes all major stages in a species' ontogeny, and soon, they will be standard even for nonmodel species. Here, we propose a Python package called oggmap, which allows for the easy extraction of an orthomap (gene ages per orthogroup) for any given query species from OrthoFinder and other gene family data resources, like homologous groups from eggNOG or PLAZA. oggmap provides extracted gene ages for more than thousand eukaryotic species which can be further used to calculate gene age-weighted expression data from scRNA sequencing objects using the Python Scanpy toolkit. Not limited to one transcriptome evolutionary index, oggmap can visualize the individual gene category (e.g. age class, nucleotide diversity bin) and their corresponding expression profiles to investigate scRNA-based cell type assignments in an evolutionary context.

AVAILABILITY AND IMPLEMENTATION

oggmap source code is available at https://github.com/kullrich/oggmap, documentation is available at https://oggmap.readthedocs.io/en/latest/. oggmap can be installed via PyPi or directly used via a docker container.

Cross-species imputation and comparison of single-cell transcriptomic profiles

Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.

Benchmarking strategies for cross-species integration of single-cell RNA sequencing data

The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has been particularly informative in this context. However, in order to do so robustly it is essential to have rigorous benchmarking and appropriate guidelines to ensure that integration results truly reflect biology. Here, we benchmark 28 combinations of gene homology mapping methods and data integration algorithms in a variety of biological settings. We examine the capability of each strategy to perform species-mixing of known homologous cell types and to preserve biological heterogeneity using 9 established metrics. We also develop a new biology conservation metric to address the maintenance of cell type distinguishability. Overall, scANVI, scVI and SeuratV4 methods achieve a balance between species-mixing and biology conservation. For evolutionarily distant species, including in-paralogs is beneficial. SAMap outperforms when integrating whole-body atlases between species with challenging gene homology annotation. We provide our freely available cross-species integration and assessment pipeline to help analyse new data and develop new algorithms.

Stepwise emergence of the neuronal gene expression program in early animal evolution

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

Multi-species atlas resolves an axolotl limb development and regeneration paradox

Humans and other tetrapods are considered to require apical-ectodermal-ridge (AER) cells for limb development, and AER-like cells are suggested to be re-formed to initiate limb regeneration. Paradoxically, the presence of AER in the axolotl, a primary model organism for regeneration, remains controversial. Here, by leveraging a single-cell transcriptomics-based multi-species atlas, composed of axolotl, human, mouse, chicken, and frog cells, we first establish that axolotls contain cells with AER characteristics. Further analyses and spatial transcriptomics reveal that axolotl limbs do not fully re-form AER cells during regeneration. Moreover, the axolotl mesoderm displays part of the AER machinery, revealing a program for limb (re)growth. These results clarify the debate about the axolotl AER and the extent to which the limb developmental program is recapitulated during regeneration.

Craniofacial developmental biology in the single-cell era

The evolution of a unique craniofacial complex in vertebrates made possible new ways of breathing, eating, communicating and sensing the environment. The head and face develop through interactions of all three germ layers, the endoderm, ectoderm and mesoderm, as well as the so-called fourth germ layer, the cranial neural crest. Over a century of experimental embryology and genetics have revealed an incredible diversity of cell types derived from each germ layer, signaling pathways and genes that coordinate craniofacial development, and how changes to these underlie human disease and vertebrate evolution. Yet for many diseases and congenital anomalies, we have an incomplete picture of the causative genomic changes, in particular how alterations to the non-coding genome might affect craniofacial gene expression. Emerging genomics and single-cell technologies provide an opportunity to obtain a more holistic view of the genes and gene regulatory elements orchestrating craniofacial development across vertebrates. These single-cell studies generate novel hypotheses that can be experimentally validated in vivo. In this Review, we highlight recent advances in single-cell studies of diverse craniofacial structures, as well as potential pitfalls and the need for extensive in vivo validation. We discuss how these studies inform the developmental sources and regulation of head structures, bringing new insights into the etiology of structural birth anomalies that affect the vertebrate head.

A lamprey neural cell type atlas illuminates the origins of the vertebrate brain

The vertebrate brain emerged more than ~500 million years ago in common evolutionary ancestors. To systematically trace its cellular and molecular origins, we established a spatially resolved cell type atlas of the entire brain of the sea lamprey-a jawless species whose phylogenetic position affords the reconstruction of ancestral vertebrate traits-based on extensive single-cell RNA-seq and in situ sequencing data. Comparisons of this atlas to neural data from the mouse and other jawed vertebrates unveiled various shared features that enabled the reconstruction of cell types, tissue structures and gene expression programs of the ancestral vertebrate brain. However, our analyses also revealed key tissues and cell types that arose later in evolution. For example, the ancestral brain was probably devoid of cerebellar cell types and oligodendrocytes (myelinating cells); our data suggest that the latter emerged from astrocyte-like evolutionary precursors in the jawed vertebrate lineage. Altogether, our work illuminates the cellular and molecular architecture of the ancestral vertebrate brain and provides a foundation for exploring its diversification during evolution.

Towards Universal Cell Embeddings: Integrating Single-cell RNA-seq Datasets across Species with SATURN

Analysis of single-cell datasets generated from diverse organisms offers unprecedented opportunities to unravel fundamental evolutionary processes of conservation and diversification of cell types. However, inter-species genomic differences limit the joint analysis of cross-species datasets to homologous genes. Here, we present SATURN, a deep learning method for learning universal cell embeddings that encodes genes' biological properties using protein language models. By coupling protein embeddings from language models with RNA expression, SATURN integrates datasets profiled from different species regardless of their genomic similarity. SATURN has a unique ability to detect functionally related genes co-expressed across species, redefining differential expression for cross-species analysis. We apply SATURN to three species whole-organism atlases and frog and zebrafish embryogenesis datasets. We show that cell embeddings learnt in SATURN can be effectively used to transfer annotations across species and identify both homologous and species-specific cell types, even across evolutionarily remote species. Finally, we use SATURN to reannotate the five species Cell Atlas of Human Trabecular Meshwork and Aqueous Outflow Structures and find evidence of potentially divergent functions between glaucoma associated genes in humans and other species.

SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks

Joint profiling of chromatin accessibility and gene expression in individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (GRNs). Here we present a method for the inference of enhancer-driven GRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TFs) and links these enhancers to candidate target genes. To improve both recall and precision of TF identification, we curated and clustered a motif collection with more than 30,000 motifs. We benchmarked SCENIC+ on diverse datasets from different species, including human peripheral blood mononuclear cells, ENCODE cell lines, melanoma cell states and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers and GRNs between human and mouse cell types in the cerebral cortex. Finally, we use SCENIC+ to study the dynamics of gene regulation along differentiation trajectories and the effect of TF perturbations on cell state. SCENIC+ is available at scenicplus.readthedocs.io .

Yolk sac cell atlas reveals multiorgan functions during human early development

The extraembryonic yolk sac (YS) ensures delivery of nutritional support and oxygen to the developing embryo but remains ill-defined in humans. We therefore assembled a comprehensive multiomic reference of the human YS from 3 to 8 postconception weeks by integrating single-cell protein and gene expression data. Beyond its recognized role as a site of hematopoiesis, we highlight roles in metabolism, coagulation, vascular development, and hematopoietic regulation. We reconstructed the emergence and decline of YS hematopoietic stem and progenitor cells from hemogenic endothelium and revealed a YS-specific accelerated route to macrophage production that seeds developing organs. The multiorgan functions of the YS are superseded as intraembryonic organs develop, effecting a multifaceted relay of vital functions as pregnancy proceeds.

The maturation and aging trajectory of Marchantia polymorpha at single-cell resolution

Bryophytes represent a sister to the rest of land plants. Despite their evolutionary importance and relatively simple body plan, a comprehensive understanding of the cell types and transcriptional states that underpin the temporal development of bryophytes has not been achieved. Using time-resolved single-cell RNA sequencing, we define the cellular taxonomy of Marchantia polymorpha across asexual reproduction phases. We identify two maturation and aging trajectories of the main plant body of M. polymorpha at single-cell resolution: the gradual maturation of tissues and organs along the tip-to-base axis of the midvein and the progressive decline of meristem activities in the tip along the chronological axis. Specifically, we observe that the latter aging axis is temporally correlated with the formation of clonal propagules, suggesting an ancient strategy to optimize allocation of resources to producing offspring. Our work thus provides insights into the cellular heterogeneity that underpins the temporal development and aging of bryophytes.

Single-cell atlases of two lophotrochozoan larvae highlight their complex evolutionary histories

Pelagic larval stages are widespread across animals, yet it is unclear whether larvae were present in the last common ancestor of animals or whether they evolved multiple times due to common selective pressures. Many marine larvae are at least superficially similar; they are small, swim through the beating of bands of cilia, and sense the environment with an apical organ. To understand these similarities, we have generated single-cell atlases for marine larvae from two animal phyla and have compared their cell types. We found clear similarities among ciliary band cells and between neurons of the apical organ in the two larvae pointing to possible homology of these structures, suggesting a single origin of larvae within Spiralia. We also find several clade-specific innovations in each larva, including distinct myocytes and shell gland cells in the oyster larva. Oyster shell gland cells express many recently evolved genes that have made previous gene age estimates for the origin of trochophore larvae too young.

Spatially resolved cell atlas of the teleost telencephalon and deep homology of the vertebrate forebrain

The telencephalon has undergone remarkable diversification and expansion throughout vertebrate evolution, exhibiting striking differences in structural and functional complexity. Nevertheless, fundamental features are shared across vertebrate taxa, such as the presence of distinct regions including the pallium, subpallium, and olfactory structures. Teleost fishes have a uniquely 'everted' telencephalon, which has made it challenging to compare brain regions in fish to those in other vertebrates. Here we combine spatial transcriptomics and single-nucleus RNA-sequencing to generate a spatially-resolved transcriptional atlas of the cichlid fish telencephalon. We then compare cell-types and anatomical regions in the cichlid telencephalon with those in amphibians, reptiles, birds, and mammals. We uncover striking transcriptional similarities between cell populations in the fish telencephalon and subpallial, hippocampal, and cortical cell populations in tetrapods. Ultimately, our work lends new insights into the organization and evolution of conserved cell-types and regions in the vertebrate forebrain.

Forkhead transcription factor FKH-8 cooperates with RFX in the direct regulation of sensory cilia in Caenorhabditis elegans

Cilia, either motile or non-motile (a.k.a primary or sensory), are complex evolutionarily conserved eukaryotic structures composed of hundreds of proteins required for their assembly, structure and function that are collectively known as the ciliome. Ciliome gene mutations underlie a group of pleiotropic genetic diseases known as ciliopathies. Proper cilium function requires the tight coregulation of ciliome gene transcription, which is only fragmentarily understood. RFX transcription factors (TF) have an evolutionarily conserved role in the direct activation of ciliome genes both in motile and non-motile cilia cell-types. In vertebrates, FoxJ1 and FoxN4 Forkhead (FKH) TFs work with RFX in the direct activation of ciliome genes, exclusively in motile cilia cell-types. No additional TFs have been described to act together with RFX in primary cilia cell-types in any organism. Here we describe FKH-8, a FKH TF, as a direct regulator of the sensory ciliome genes in Caenorhabditis elegans. FKH-8 is expressed in all ciliated neurons in C. elegans, binds the regulatory regions of ciliome genes, regulates ciliome gene expression, cilium morphology and a wide range of behaviors mediated by sensory ciliated neurons. FKH-8 and DAF-19 (C. elegans RFX) physically interact and synergistically regulate ciliome gene expression. C. elegans FKH-8 function can be replaced by mouse FOXJ1 and FOXN4 but not by other members of other mouse FKH subfamilies. In conclusion, RFX and FKH TF families act jointly as direct regulators of ciliome genes also in sensory ciliated cell types suggesting that this regulatory logic could be an ancient trait predating functional cilia sub-specialization.

An atlas of rabbit development as a model for single-cell comparative genomics

Traditionally, the mouse has been the favoured vertebrate model for biomedical research, due to its experimental and genetic tractability. However, non-rodent embryological studies highlight that many aspects of early mouse development, such as its egg-cylinder gastrulation and method of implantation, diverge from other mammals, thus complicating inferences about human development. Like the human embryo, rabbits develop as a flat-bilaminar disc. Here we constructed a morphological and molecular atlas of rabbit development. We report transcriptional and chromatin accessibility profiles for over 180,000 single cells and high-resolution histology sections from embryos spanning gastrulation, implantation, amniogenesis and early organogenesis. Using a neighbourhood comparison pipeline, we compare the transcriptional landscape of rabbit and mouse at the scale of the entire organism. We characterize the gene regulatory programmes underlying trophoblast differentiation and identify signalling interactions involving the yolk sac mesothelium during haematopoiesis. We demonstrate how the combination of both rabbit and mouse atlases can be leveraged to extract new biological insights from sparse macaque and human data. The datasets and computational pipelines reported here set a framework for a broader cross-species approach to decipher early mammalian development, and are readily adaptable to deploy single-cell comparative genomics more broadly across biomedical research.

Cell type matching across species using protein embeddings and transfer learning

MOTIVATION

Knowing the relation between cell types is crucial for translating experimental results from mice to humans. Establishing cell type matches, however, is hindered by the biological differences between the species. A substantial amount of evolutionary information between genes that could be used to align the species is discarded by most of the current methods since they only use one-to-one orthologous genes. Some methods try to retain the information by explicitly including the relation between genes, however, not without caveats.

RESULTS

In this work, we present a model to transfer and align cell types in cross-species analysis (TACTiCS). First, TACTiCS uses a natural language processing model to match genes using their protein sequences. Next, TACTiCS employs a neural network to classify cell types within a species. Afterward, TACTiCS uses transfer learning to propagate cell type labels between species. We applied TACTiCS on scRNA-seq data of the primary motor cortex of human, mouse, and marmoset. Our model can accurately match and align cell types on these datasets. Moreover, our model outperforms Seurat and the state-of-the-art method SAMap. Finally, we show that our gene matching method results in better cell type matches than BLAST in our model.

AVAILABILITY AND IMPLEMENTATION

The implementation is available on GitHub (https://github.com/kbiharie/TACTiCS). The preprocessed datasets and trained models can be downloaded from Zenodo (https://doi.org/10.5281/zenodo.7582460).

CAGEE: Computational Analysis of Gene Expression Evolution

Despite the increasing abundance of whole transcriptome data, few methods are available to analyze global gene expression across phylogenies. Here, we present a new software package (Computational Analysis of Gene Expression Evolution [CAGEE]) for inferring patterns of increases and decreases in gene expression across a phylogenetic tree, as well as the rate at which these changes occur. In contrast to previous methods that treat each gene independently, CAGEE can calculate genome-wide rates of gene expression, along with ancestral states for each gene. The statistical approach developed here makes it possible to infer lineage-specific shifts in rates of evolution across the genome, in addition to possible differences in rates among multiple tissues sampled from the same species. We demonstrate the accuracy and robustness of our method on simulated data and apply it to a data set of ovule gene expression collected from multiple self-compatible and self-incompatible species in the genus Solanum to test hypotheses about the evolutionary forces acting during mating system shifts. These comparisons allow us to highlight the power of CAGEE, demonstrating its utility for use in any empirical system and for the analysis of most morphological traits. Our software is available at https://github.com/hahnlab/CAGEE/.

Single-cell analysis of shared signatures and transcriptional diversity during zebrafish development

During development, animals generate distinct cell populations with specific identities, functions, and morphologies. We mapped transcriptionally distinct populations across 489,686 cells from 62 stages during wild-type zebrafish embryogenesis and early larval development (3-120 hours post-fertilization). Using these data, we identified the limited catalog of gene expression programs reused across multiple tissues and their cell-type-specific adaptations. We also determined the duration each transcriptional state is present during development and suggest new long-term cycling populations. Focused analyses of non-skeletal muscle and the endoderm identified transcriptional profiles of understudied cell types and subpopulations, including the pneumatic duct, individual intestinal smooth muscle layers, spatially distinct pericyte subpopulations, and homologs of recently discovered human best4+ enterocytes. The transcriptional regulators of these populations remain unknown, so we reconstructed gene expression trajectories to suggest candidates. To enable additional discoveries, we make this comprehensive transcriptional atlas of early zebrafish development available through our website, Daniocell.

Evolution of homology: From archetype towards a holistic concept of cell type

The concept of homology lies in the heart of comparative biological science. The distinction between homology as structure and analogy as function has shaped the evolutionary paradigm for a century and formed the axis of comparative anatomy and embryology, which accept the identity of structure as a ground measure of relatedness. The advent of single-cell genomics overturned the classical view of cell homology by establishing a backbone regulatory identity of cell types, the basic biological units bridging the molecular and phenotypic dimensions, to reveal that the cell is the most flexible unit of living matter and that many approaches of classical biology need to be revised to understand evolution and diversity at the cellular level. The emerging theory of cell types explicitly decouples cell identity from phenotype, essentially allowing for the divergence of evolutionarily related morphotypes beyond recognition, as well as it decouples ontogenetic cell lineage from cell-type phylogeny, whereby explicating that cell types can share common descent regardless of their structure, function or developmental origin. The article succinctly summarizes current progress and opinion in this field and formulates a more generalistic view of biological cell types as avatars, transient or terminal cell states deployed in a continuum of states by the developmental programme of one and the same omnipotent cell, capable of changing or combining identities with distinct evolutionary histories or inventing ad hoc identities that never existed in evolution or development. It highlights how the new logic grounded in the regulatory nature of cell identity transforms the concepts of cell homology and phenotypic stability, suggesting that cellular evolution is inherently and massively network-like, with one-to-one homologies being rather uncommon and restricted to shallower levels of the animal tree of life.

Cross-species single-cell comparison of systemic and cardiac inflammatory responses after cardiac injury

The immune system coordinates the response to cardiac injury and is known to control regenerative and fibrotic scar outcomes in the heart and subsequent chronic low-grade inflammation associated with heart failure. Here we profiled the inflammatory response to heart injury using single cell transcriptomics to compare and contrast two experimental models with disparate outcomes. We used adult mice, which like humans lack the ability to fully recover and zebrafish which spontaneously regenerate after heart injury. The extracardiac reaction to cardiomyocyte necrosis was also interrogated to assess the specific peripheral tissue and immune cell reaction to chronic stress. Cardiac macrophages are known to play a critical role in determining tissue homeostasis by healing versus scarring. We identified distinct transcriptional clusters of monocytes/macrophages in each species and found analogous pairs in zebrafish and mice. However, the reaction to myocardial injury was largely disparate between mice and zebrafish. The dichotomous response to heart damage between the mammalian and zebrafish monocytes/macrophages may underlie the impaired regenerative process in mice, representing a future therapeutic target.

Neurodegeneration cell per cell

The clinical definition of neurodegenerative diseases is based on symptoms that reflect terminal damage of specific brain regions. This is misleading as it tells little about the initial disease processes. Circuitry failures that underlie the clinical symptomatology are themselves preceded by clinically mostly silent, slowly progressing multicellular processes that trigger or are triggered by the accumulation of abnormally folded proteins such as Aβ, Tau, TDP-43, and α-synuclein, among others. Methodological advances in single-cell omics, combined with complex genetics and novel ways to model complex cellular interactions using induced pluripotent stem (iPS) cells, make it possible to analyze the early cellular phase of neurodegenerative disorders. This will revolutionize the way we study those diseases and will translate into novel diagnostics and cell-specific therapeutic targets, stopping these disorders in their early track before they cause difficult-to-reverse damage to the brain.

Mitochondria metabolism sets the species-specific tempo of neuronal development

Neuronal development in the human cerebral cortex is considerably prolonged compared with that of other mammals. We explored whether mitochondria influence the species-specific timing of cortical neuron maturation. By comparing human and mouse cortical neuronal maturation at high temporal and cell resolution, we found a slower mitochondria development in human cortical neurons compared with that in the mouse, together with lower mitochondria metabolic activity, particularly that of oxidative phosphorylation. Stimulation of mitochondria metabolism in human neurons resulted in accelerated development in vitro and in vivo, leading to maturation of cells weeks ahead of time, whereas its inhibition in mouse neurons led to decreased rates of maturation. Mitochondria are thus important regulators of the pace of neuronal development underlying human-specific brain neoteny.

A chromosome-scale epigenetic map of the Hydra genome reveals conserved regulators of cell state

The epithelial and interstitial stem cells of the freshwater polyp Hydra are the best-characterized stem cell systems in any cnidarian, providing valuable insight into cell type evolution and the origin of stemness in animals. However, little is known about the transcriptional regulatory mechanisms that determine how these stem cells are maintained and how they give rise to their diverse differentiated progeny. To address such questions, a thorough understanding of transcriptional regulation in Hydra is needed. To this end, we generated extensive new resources for characterizing transcriptional regulation in Hydra, including new genome assemblies for Hydra oligactis and the AEP strain of Hydra vulgaris, an updated whole-animal single-cell RNA-seq atlas, and genome-wide maps of chromatin interactions, chromatin accessibility, sequence conservation, and histone modifications. These data revealed the existence of large kilobase-scale chromatin interaction domains in the Hydra genome that contain transcriptionally coregulated genes. We also uncovered the transcriptomic profiles of two previously molecularly uncharacterized cell types: isorhiza-type nematocytes and somatic gonad ectoderm. Finally, we identified novel candidate regulators of cell type-specific transcription, several of which have likely been conserved at least since the divergence of Hydra and the jellyfish Clytia hemisphaerica more than 400 million years ago.