Resolution of cell fate decisions revealed by single-cell gene expression analysis from zygote to blastocyst

Application of the modified handmade cloning technique to pigs

Although somatic cell nuclear transfer (SCNT) is frequently employed to produce cloned animals in laboratories, this technique is expensive and inefficient. Therefore, the handmade cloning (HMC) technique has been suggested to simplify and advance the cloning process, however, HMC wastes many oocytes and leads to mitochondrial heteroplasmy. To solve these problems, we propose a modified handmade cloning (mHMC) technique that uses simple laboratory equipment, i.e., a Pasteur pipette and an alcohol lamp, applying it to porcine embryo cloning. To validate the application of mHMC to pig cloning, embryos produced through SCNT and mHMC are compared using multiple methods, such as enucleation efficiency, oxidative stress, embryo developmental competence, and gene expression. The results show no significant differences between techniques except in the enucleation efficiency. The 8-cell and 16-cell embryo developmental competence and Oct4 expression levels exhibit significant differences. However, the blastocyst rate is not significantly different between mHMC and SCNT. This study verifies that cloned embryos derived from the two techniques exhibit similar generation and developmental competence. Thus, we suggest that mHMC could replace SCNT for simpler and cheaper porcine cloning.

DEEPsc: A Deep Learning-Based Map Connecting Single-Cell Transcriptomics and Spatial Imaging Data

Single-cell RNA sequencing (scRNA-seq) data provides unprecedented information on cell fate decisions; however, the spatial arrangement of cells is often lost. Several recent computational methods have been developed to impute spatial information onto a scRNA-seq dataset through analyzing known spatial expression patterns of a small subset of genes known as a reference atlas. However, there is a lack of comprehensive analysis of the accuracy, precision, and robustness of the mappings, along with the generalizability of these methods, which are often designed for specific systems. We present a system-adaptive deep learning-based method (DEEPsc) to impute spatial information onto a scRNA-seq dataset from a given spatial reference atlas. By introducing a comprehensive set of metrics that evaluate the spatial mapping methods, we compare DEEPsc with four existing methods on four biological systems. We find that while DEEPsc has comparable accuracy to other methods, an improved balance between precision and robustness is achieved. DEEPsc provides a data-adaptive tool to connect scRNA-seq datasets and spatial imaging datasets to analyze cell fate decisions. Our implementation with a uniform API can serve as a portal with access to all the methods investigated in this work for spatial exploration of cell fate decisions in scRNA-seq data. All methods evaluated in this work are implemented as an open-source software with a uniform interface.

A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development

During early mammalian embryo development, a small number of cells make robust fate decisions at particular spatial locations in a tight time window to form inner cell mass (ICM), and later epiblast (Epi) and primitive endoderm (PE). While recent single-cell transcriptomics data allows scrutinization of heterogeneity of individual cells, consistent spatial and temporal mechanisms the early embryo utilize to robustly form the Epi/PE layers from ICM remain elusive. Here we build a multiscale three-dimensional model for mammalian embryo to recapitulate the observed patterning process from zygote to late blastocyst. By integrating the spatiotemporal information reconstructed from multiple single-cell transcriptomic datasets, the data-informed modeling analysis suggests two major processes critical to the formation of Epi/PE layers: a selective cell-cell adhesion mechanism (via EphA4/EphrinB2) for fate-location coordination and a temporal attenuation mechanism of cell signaling (via Fgf). Spatial imaging data and distinct subsets of single-cell gene expression data are then used to validate the predictions. Together, our study provides a multiscale framework that incorporates single-cell gene expression datasets to analyze gene regulations, cell-cell communications, and physical interactions among cells in complex geometries at single-cell resolution, with direct application to late-stage development of embryogenesis.

Regulation of endoplasmic reticulum stress and trophectoderm lineage specification by the mevalonate pathway in the mouse preimplantation embryo

Early embryos are vulnerable to environmental insults, such as medications taken by the mother. Due to increasing prevalence of hypercholesterolemia, more women of childbearing potential are taking cholesterol-lowering medications called statins. Previously, we showed that inhibition of the mevalonate pathway by statins impaired mouse preimplantation development, by modulating HIPPO signaling, a key regulator for trophectoderm (TE) lineage specification. Here, we further evaluated molecular events that are altered by mevalonate pathway inhibition during the timeframe of morphogenesis and cell lineage specification. Whole transcriptome analysis revealed that statin treatment dysregulated gene expression underlying multiple processes, including cholesterol biosynthesis, HIPPO signaling, cell lineage specification and endoplasmic reticulum (ER) stress response. We explored mechanisms that link the mevalonate pathway to ER stress, because of its potential impact on embryonic health and development. Upregulation of ER stress-responsive genes was inhibited when statin-treated embryos were supplemented with the mevalonate pathway product, geranylgeranyl pyrophosphate (GGPP). Inhibition of geranylgeranylation was sufficient to upregulate ER stress-responsive genes. However, ER stress-responsive genes were not upregulated by inhibition of ras homolog family member A (RHOA), a geranylgeranylation target, although it interfered with TE specification and blastocyst cavity formation. In contrast, inhibition of Rac family small GTPase 1 (RAC1), another geranylgeranylation target, upregulated ER stress-responsive genes, while it did not impair TE specification or cavity formation. Thus, our study suggests that the mevalonate pathway regulates cellular homeostasis (ER stress repression) and differentiation (TE lineage specification) in preimplantation embryos through GGPP-dependent activation of two distinct small GTPases, RAC1 and RHOA, respectively. Translation of the findings to human embryos and clinical settings requires further investigations.

SSRE: Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement

Accurate identification of cell types from single-cell RNA sequencing (scRNA-seq) data plays a critical role in a variety of scRNA-seq analysis studies. This task corresponds to solving an unsupervised clustering problem, in which the similarity measurement between cells affects the result significantly. Although many approaches for cell type identification have been proposed, the accuracy still needs to be improved. In this study, we proposed a novel single-cell clustering framework based on similarity learning, called SSRE. SSRE models the relationships between cells based on subspace assumption, and generates a sparse representation of the cell-to-cell similarity. The sparse representation retains the most similar neighbors for each cell. Besides, three classical pairwise similarities are incorporated with a gene selection and enhancement strategy to further improve the effectiveness of SSRE. Tested on ten real scRNA-seq datasets and five simulated datasets, SSRE achieved the superior performance in most cases compared to several state-of-the-art single-cell clustering methods. In addition, SSRE can be extended to visualization of scRNA-seq data and identification of differentially expressed genes. The matlab and python implementations of SSRE are available at https://github.com/CSUBioGroup/SSRE.

Pluripotent stem cells in the research for extraembryonic cell differentiation

Mouse embryonic stem cells (mESCs) are pluripotent stem cell populations derived from the preimplantation embryo and are used to study the differentiation of many types of somatic and germ cells in developing embryos. They are also used to study cell lineages of extraembryonic tissues, such as the trophectoderm (TE) and the primitive endoderm (PrE). mESC cultures are suitable systems for reproducing cellular and molecular events occurring during the differentiation of these cell types, such as changes in gene expression patterns, signaling events, and genome rearrangements although the consistency between the results obtained using mESCs and those of in vivo studies on embryos should be carefully taken into account. Since TE and PrE cells can be induced from mESCs in vitro, mESC cultures are useful systems to study differentiation of these cell lineages during development, if used appropriately. In addition, human pluripotent stem cells (hPSCs), such as human embryonic stem cells (hESCs) and human-induced pluripotent stem cells (hiPSCs), are capable of generating extraembryonic lineages in vitro and are promising tools to study the differentiation of these lineages in the human embryo.

OCT4 induces embryonic pluripotency via STAT3 signaling and metabolic mechanisms

OCT4 is a fundamental component of the molecular circuitry governing pluripotency in vivo and in vitro. To determine how OCT4 establishes and protects the pluripotent lineage in the embryo, we used comparative single-cell transcriptomics and quantitative immunofluorescence on control and OCT4 null blastocyst inner cell masses at two developmental stages. Surprisingly, activation of most pluripotency-associated transcription factors in the early mouse embryo occurs independently of OCT4, with the exception of the JAK/STAT signaling machinery. Concurrently, OCT4 null inner cell masses ectopically activate a subset of trophectoderm-associated genes. Inspection of metabolic pathways implicates the regulation of rate-limiting glycolytic enzymes by OCT4, consistent with a role in sustaining glycolysis. Furthermore, up-regulation of the lysosomal pathway was specifically detected in OCT4 null embryos. This finding implicates a requirement for OCT4 in the production of normal trophectoderm. Collectively, our findings uncover regulation of cellular metabolism and biophysical properties as mechanisms by which OCT4 instructs pluripotency.

Cell differentiation events in pre-implantation mouse and bovine embryos

Early mammal embryogenesis starts with oocyte fertilization, giving rise to the zygote. The events that the newly formed zygote surpasses are crucial to the embryo developmental success. Shortly after activation of its genome, cells of the embryo segregate into the inner cell mass (ICM) or the trophectoderm (TE). The first will give rise to the embryo while the latter will become the placenta. This first segregation involves cellular and molecular processes that include cell polarity linked to intracellular pathway activation, which will regulate the transcription of trophectoderm-related genes. Then, cells of the ICM undergo the second event of mammalian cell differentiation, which consists of the separation between epiblast (EPI) and hypoblast or primitive endoderm (PrE). This second segregation involves paracrine signaling, leading to differential expression of key genes that will dictate the fate of the cell. Although these processes are described in detail in the mouse, recent studies suggest that the bovine embryo could also be an interesting model for early development, since there are differences to the mouse and similarities with early human embryogenesis. In this review, we gathered the main data available in the literature upon bovine and mouse early development events, suggesting that both models should be analyzed and studied in a complementary way, to better model early events occurring in human development.

Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach

During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell-cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.

Measuring and Modeling Single-Cell Heterogeneity and Fate Decision in Mouse Embryos

Cellular heterogeneity is a property of any living system; however, its relationship with cellular fate decision remains an open question. Recent technological advances have enabled valuable insights, especially in complex systems such as the mouse embryo. In this review, we discuss recent studies that characterize cellular heterogeneity at different levels during mouse development, from the two-cell stage up to gastrulation. In addition to key experimental findings, we review mathematical modeling approaches that help researchers interpret these findings. Disentangling the role of heterogeneity in cell fate decision will likely rely on the refined integration of experiments, large-scale omics data, and mathematical modeling, complemented by the use of synthetic embryos and gastruloids as promising in vitro models.

Cell-Cycle-Dependent ERK Signaling Dynamics Direct Fate Specification in the Mammalian Preimplantation Embryo

Despite the noisy nature of single cells, multicellular organisms robustly generate different cell types from one zygote. This process involves dynamic cross regulation between signaling and gene expression that is difficult to capture with fixed-cell approaches. To study signaling dynamics and fate specification during preimplantation development, we generated a transgenic mouse expressing the ERK kinase translocation reporter and measured ERK activity in single cells of live embryos. Our results show primarily active ERK in both the inner cell mass and trophectoderm cells due to fibroblast growth factor (FGF) signaling. Strikingly, a subset of mitotic events results in a short pulse of ERK inactivity in both daughter cells that correlates with elevated endpoint NANOG levels. Moreover, endogenous tagging of Nanog in embryonic stem cells reveals that ERK inhibition promotes enhanced stabilization of NANOG protein after mitosis. Our data show that cell cycle, signaling, and differentiation are coordinated during preimplantation development.

Live Visualization of ERK Activity in the Mouse Blastocyst Reveals Lineage-Specific Signaling Dynamics

FGF/ERK signaling is crucial for the patterning and proliferation of cell lineages that comprise the mouse blastocyst. However, ERK signaling dynamics have never been directly visualized in live embryos. To address whether differential signaling is associated with particular cell fates and states, we generated a targeted mouse line expressing an ERK-kinase translocation reporter (KTR) that enables live quantification of ERK activity at single-cell resolution. 3D time-lapse imaging of this biosensor in embryos revealed spatially graded ERK activity in the trophectoderm prior to overt polar versus mural differentiation. Within the inner cell mass (ICM), all cells relayed FGF/ERK signals with varying durations and magnitude. Primitive endoderm cells displayed higher overall levels of ERK activity, while pluripotent epiblast cells exhibited lower basal activity with sporadic pulses. These results constitute a direct visualization of signaling events during mammalian pre-implantation development and reveal the existence of spatial and temporal lineage-specific dynamics.

Interpretable factor models of single-cell RNA-seq via variational autoencoders

Motivation

Single-cell RNA-seq makes possible the investigation of variability in gene expression among cells, and dependence of variation on cell type. Statistical inference methods for such analyses must be scalable, and ideally interpretable.

Results

We present an approach based on a modification of a recently published highly scalable variational autoencoder framework that provides interpretability without sacrificing much accuracy. We demonstrate that our approach enables identification of gene programs in massive datasets. Our strategy, namely the learning of factor models with the auto-encoding variational Bayes framework, is not domain specific and may be useful for other applications.

Availability and implementation

The factor model is available in the scVI package hosted at https://github.com/YosefLab/scVI/.

Contact

v@nxn.se

Supplementary information

Supplementary data are available at Bioinformatics online.

Lighting up single-nucleotide variation in situ in single cells and tissues

The ability to 'see' genetic information directly in single cells can provide invaluable insights into complex biological systems. In this review, we discuss recent advances of in situ imaging technologies for visualizing the subtlest sequence alteration, single-nucleotide variation (SNV), at single-cell level. The mechanism of recently developed methods for SNV discrimination are summarized in detail. With recent developments, single-cell SNV imaging methods have opened a new door for studying the heterogenous and stochastic genetic information in individual cells. Furthermore, SNV imaging can be used on morphologically preserved tissue, which can provide information on histological context for gene expression profiling in basic research and genetic diagnosis. Moreover, the ability to visualize SNVs in situ can be further developed into in situ sequencing technology. We expect this review to inspire more research work into in situ SNV imaging technologies for investigating cellular phenotypes and gene regulation at single-nucleotide resolution, and developing new clinical and biomedical applications.

The inclusion of blastomeres into the inner cell mass in early-stage human embryos depends on the sequence of cell cleavages during the fourth division

The fate of the ICM in humans is still unknown, due to the ethical difficulties surrounding experimentation in this field. In this study we have explored the existing time-lapse recording data of embryos in the early stages of development, taking advantage of the large refractile bodies (RBs) within blastomeres as cellular markers. Our study found that the cellular composition of the ICM in humans is largely determined at the time of the fourth division and blastomeres which cleave first to fourth, during the fourth division from 8 cells to 16 cells, have the potential to be incorporated in the ICM.

Coordination between patterning and morphogenesis ensures robustness during mouse development

The mammalian preimplantation embryo is a highly tractable, self-organizing developmental system in which three cell types are consistently specified without the need for maternal factors or external signals. Studies in the mouse over the past decades have greatly improved our understanding of the cues that trigger symmetry breaking in the embryo, the transcription factors that control lineage specification and commitment, and the mechanical forces that drive morphogenesis and inform cell fate decisions. These studies have also uncovered how these multiple inputs are integrated to allocate the right number of cells to each lineage despite inherent biological noise, and as a response to perturbations. In this review, we summarize our current understanding of how these processes are coordinated to ensure a robust and precise developmental outcome during early mouse development. This article is part of a discussion meeting issue 'Contemporary morphogenesis'.

Identification of the Lineage Markers and Inhibition of DAB2 in In Vitro Fertilized Porcine Embryos

Specification of embryonic lineages is an important question in the field of early development. Numerous studies analyzed the expression patterns of the candidate transcripts and proteins in humans and mice and clearly determined the markers of each lineage. To overcome the limitations of human and mouse embryos, the expression of the marker transcripts in each cell has been investigated using in vivo embryos in pigs. In vitro produced embryos are more accessible, can be rapidly processed with low cost. Therefore, we analyzed the characteristics of lineage markers and the effects of the DAB2 gene (trophectoderm marker) in in vitro fertilized porcine embryos. We investigated the expression levels of the marker genes during embryonic stages and distribution of the marker proteins was assayed in day 7 blastocysts. Then, the shRNA vectors were injected into the fertilized embryos and the differences in the marker transcripts were analyzed. Marker transcripts showed diverse patterns of expression, and each embryonic lineage could be identified with localization of marker proteins. In DAB2-shRNA vectors injected embryos, HNF4A and PDGFRA were upregulated. DAB2 protein level was lower in shRNA-injected embryos without significant differences. Our results will contribute to understanding of the mechanisms of embryonic lineage specification in pigs.

Whole-Mount Immunofluorescence Staining of Early Mouse Embryos

Immunofluorescence staining enables the visualization of protein expression at a cellular or even sub-nuclear level. Whole-mount staining preserves the three-dimensional spatial information in biological samples allowing a comprehensive interpretation of expression domains. Here we describe the sample processing, protein detection using antibodies and confocal imaging of isolated preimplantation to early postimplantation mouse embryos up to Embryonic day 8.0 (E8.0).

From pluripotency to totipotency: an experimentalist's guide to cellular potency

Embryonic stem cells (ESCs) are derived from the pre-implantation mammalian blastocyst. At this point in time, the newly formed embryo is concerned with the generation and expansion of both the embryonic lineages required to build the embryo and the extra-embryonic lineages that support development. When used in grafting experiments, embryonic cells from early developmental stages can contribute to both embryonic and extra-embryonic lineages, but it is generally accepted that ESCs can give rise to only embryonic lineages. As a result, they are referred to as pluripotent, rather than totipotent. Here, we consider the experimental potential of various ESC populations and a number of recently identified in vitro culture systems producing states beyond pluripotency and reminiscent of those observed during pre-implantation development. We also consider the nature of totipotency and the extent to which cell populations in these culture systems exhibit this property.

Manipulating the Mediator complex to induce naïve pluripotency

Human naïve pluripotent stem cells (PSCs) represent an optimal homogenous starting point for molecular interventions and differentiation strategies. This is in contrast to the standard primed PSCs which fluctuate in identity and are transcriptionally heterogeneous. However, despite many efforts, the maintenance and expansion of human naïve PSCs remains a challenge. Here, we discuss our recent strategy for the stabilization of human PSC in the naïve state based on the use of a single chemical inhibitor of the related kinases CDK8 and CDK19. These kinases phosphorylate and negatively regulate the multiprotein Mediator complex, which is critical for enhancer-driven recruitment of RNA Pol II. The net effect of CDK8/19 inhibition is a global stimulation of enhancers, which in turn reinforces transcriptional programs including those related to cellular identity. In the case of pluripotent cells, the presence of CDK8/19i efficiently stabilizes the naïve state. Importantly, in contrast to previous chemical methods to induced the naïve state based on the inhibition of the FGF-MEK-ERK pathway, CDK8/19i-naïve human PSCs are chromosomally stable and retain developmental potential after long-term expansion. We suggest this could be related to the fact that CDK8/19 inhibition does not induce DNA demethylation. These principles may apply to other fate decisions.

Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by random circuit perturbation

Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not well understood. To address this question, we applied a recently developed computational method, random circuit perturbation (RACIPE), to a nine-component gene regulatory network (GRN) governing stemness, from which we identified robust gene states. Among them, four out of the five most probable gene states exhibit gene expression patterns observed in single mouse embryonic cells at 32-cell and 64-cell stages. These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN. Strikingly, we found a hierarchical structure of the GRN with the Oct4/Cdx2 motif functioning as the first decision-making module followed by Gata6/Nanog. We propose that stem cell populations, instead of being viewed as all having a specific cellular state, can be regarded as a heterogeneous mixture including cells in various states. Upon perturbations by external signals, stem cells lose the capacity to access certain cellular states, thereby becoming differentiated. The new gene states and key parameters regulating transitions among gene states proposed by RACIPE can be used to guide experimental strategies to better understand differentiation and design reprogramming. The findings demonstrate that the functions of the stemness GRN is mainly determined by its well-evolved network topology rather than by detailed kinetic parameters.

A computational model of stem cell molecular mechanism to maintain tissue homeostasis

Stem cells, with their capacity to self-renew and to differentiate to more specialized cell types, play a key role to maintain homeostasis in adult tissues. To investigate how, in the dynamic stochastic environment of a tissue, non-genetic diversity and the precise balance between proliferation and differentiation are achieved, it is necessary to understand the molecular mechanisms of the stem cells in decision making process. By focusing on the impact of stochasticity, we proposed a computational model describing the regulatory circuitry as a tri-stable dynamical system to reveal the mechanism which orchestrate this balance. Our model explains how the distribution of noise in genes, linked to the cell regulatory networks, affects cell decision-making to maintain homeostatic state. The noise effect on tissue homeostasis is achieved by regulating the probability of differentiation and self-renewal through symmetric and/or asymmetric cell divisions. Our model reveals, when mutations due to the replication of DNA in stem cell division, are inevitable, how mutations contribute to either aging gradually or the development of cancer in a short period of time. Furthermore, our model sheds some light on the impact of more complex regulatory networks on the system robustness against perturbations.

Growth-factor-mediated coupling between lineage size and cell fate choice underlies robustness of mammalian development

Precise control and maintenance of population size is fundamental for organismal development and homeostasis. The three cell types of the mammalian blastocyst are generated in precise proportions over a short time, suggesting a mechanism to ensure a reproducible outcome. We developed a minimal mathematical model demonstrating growth factor signaling is sufficient to guarantee this robustness and which anticipates an embryo's response to perturbations in lineage composition. Addition of lineage-restricted cells both in vivo and in silico, causes a shift of the fate of progenitors away from the supernumerary cell type, while eliminating cells using laser ablation biases the specification of progenitors toward the targeted cell type. Finally, FGF4 couples fate decisions to lineage composition through changes in local growth factor concentration, providing a basis for the regulative abilities of the early mammalian embryo whereby fate decisions are coordinated at the population level to robustly generate tissues in the right proportions.

A Darwinian and Physical Look at Stem Cell Biology Helps Understanding the Role of Stochasticity in Development

Single-cell analysis allows biologists to gain huge insight into cell differentiation and tissue structuration. Randomness of differentiation, both in vitro and in vivo, of pluripotent (multipotent) stem cells is now demonstrated to be mainly based on stochastic gene expression. Nevertheless, it remains necessary to incorporate this inherent stochasticity of developmental processes within a coherent scheme. We argue here that the theory called ontophylogenesis is more relevant and better fits with experimental data than alternative theories which have been suggested based on the notions of self-organization and attractor states. The ontophylogenesis theory considers the generation of a differentiated state as a constrained random process: randomness is provided by the stochastic dynamics of biochemical reactions while the environmental constraints, including cell inner structures and cell-cell interactions, drive the system toward a stabilized state of equilibrium. In this conception, biological organization during development can be seen as the result of multiscale constraints produced by the dynamical organization of the biological system which retroacts on the stochastic dynamics at lower scales. This scheme makes it possible to really understand how the generation of reproducible structures at higher organization levels can be fully compatible with probabilistic behavior at the lower levels. It is compatible with the second law of thermodynamics but allows the overtaking of the limitations exhibited by models only based on entropy exchanges which cannot cope with the description nor the dynamics of the mesoscopic and macroscopic organization of biological systems.

Common principles of early mammalian embryo self-organisation

Pre-implantation mammalian development unites extreme plasticity with a robust outcome: the formation of a blastocyst, an organised multi-layered structure ready for implantation. The process of blastocyst formation is one of the best-known examples of self-organisation. The first three cell lineages in mammalian development specify and arrange themselves during the morphogenic process based on cell-cell interactions. Despite decades of research, the unifying principles driving early mammalian development are still not fully defined. Here, we discuss the role of physical forces, and molecular and cellular mechanisms, in driving self-organisation and lineage formation that are shared between eutherian mammals.

Generation of Artificial Gamete and Embryo From Stem Cells in Reproductive Medicine

In addition to the great growing need for assisted reproduction technologies (ART), additional solutions for patients without functional gametes are strongly needed. Due to ethical restrictions, limited studies can be performed on human gametes and embryos; however, artificial gametes and embryos represent a new hope for clinical application and basic research in the field of reproductive medicine. Here, we provide a review of the research progress and possible application of artificial gametes and embryos from different species, including mice, monkeys and humans. Gametes specification from adult stem cells and embryonic stem cells (ESCs) as well as propagation of stem cells from the reproductive system and from organized embryos, which are similar to blastocysts, have been realized in some nonhuman mammals, but not all achievements can be replicated in humans. This area of research remains noteworthy and requires further study and effort to achieve the reconstitution of the entire cycle of gametogenesis and embryo development in vitro.

LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks

Background

Gene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the data, resulting in missing information. Most of studies apply fuzzy logics to infer the logical gene-gene interactions from continuous data. However, all these approaches require an a priori known network structure.

Results

Here, by introducing a new probabilistic logic for continuous data, we propose a novel logic-based approach (called the LogicNet) for the simultaneous reconstruction of the GRN structure and identification of the logics among the regulatory genes, from the continuous gene expression data. In contrast to the previous approaches, the LogicNet does not require an a priori known network structure to infer the logics. The proposed probabilistic logic is superior to the existing fuzzy logics and is more relevant to the biological contexts than the fuzzy logics. The performance of the LogicNet is superior to that of several Mutual Information-based and regression-based tools for reconstructing GRNs.

Conclusions

The LogicNet reconstructs GRNs and logic functions without requiring prior knowledge of the network structure. Moreover, in another application, the LogicNet can be applied for logic function detection from the known regulatory genes-target interactions. We also conclude that computational modeling of the logical interactions among the regulatory genes significantly improves the GRN reconstruction accuracy.

A single cell transcriptional atlas of early synovial joint development

Synovial joint development begins with the formation of the interzone, a region of condensed mesenchymal cells at the site of the prospective joint. Recently, lineage-tracing strategies have revealed that Gdf5-lineage cells native to and from outside the interzone contribute to most, if not all, of the major joint components. However, there is limited knowledge of the specific transcriptional and signaling programs that regulate interzone formation and fate diversification of synovial joint constituents. To address this, we have performed single cell RNA-Seq analysis of 7329 synovial joint progenitor cells from the developing murine knee joint from E12.5 to E15.5. By using a combination of computational analytics, in situ hybridization and in vitro characterization of prospectively isolated populations, we have identified the transcriptional profiles of the major developmental paths for joint progenitors. Our freely available single cell transcriptional atlas will serve as a resource for the community to uncover transcriptional programs and cell interactions that regulate synovial joint development.

Bioengineering tissue morphogenesis and function in human neural organoids

Over the last decade, scientists have begun to model CNS development, function, and disease in vitro using human pluripotent stem cell (hPSC)-derived organoids. Using traditional protocols, these 3D tissues are generated by combining the innate emergent properties of differentiating hPSC aggregates with a bioreactor environment that induces interstitial transport of oxygen and nutrients and an optional supportive hydrogel extracellular matrix (ECM). During extended culture, the hPSC-derived neural organoids (hNOs) obtain millimeter scale sizes with internal microscale cytoarchitectures, cellular phenotypes, and neuronal circuit behaviors mimetic of those observed in the developing brain, eye, or spinal cord. Early studies evaluated the cytoarchitectural and phenotypical character of these organoids and provided unprecedented insight into the morphogenetic processes that govern CNS development. Comparisons to human fetal tissues revealed their significant similarities and differences. While hNOs have current disease modeling applications and significant future promise, their value as anatomical and physiological models is limited because they fail to form reproducibly and recapitulate more mature in vivo features. These include biomimetic macroscale tissue morphology, positioning of morphogen signaling centers to orchestrate appropriate spatial organization and intra- and inter-connectivity of discrete tissue regions, maturation of physiologically relevant neural circuits, and formation of vascular networks that can support sustained in vitro tissue growth. To address these inadequacies scientists have begun to integrate organoid culture with bioengineering techniques and methodologies including genome editing, biomaterials, and microfabricated and microfluidic platforms that enable spatiotemporal control of cellular differentiation or the biochemical and biophysical cues that orchestrate organoid morphogenesis. This review will examine recent advances in hNO technologies and culture strategies that promote reproducible in vitro morphogenesis and greater biomimicry in structure and function.

Notch signaling in mouse blastocyst development and hatching

Background

Mammalian early embryo development requires a well-orchestrated interplay of cell signaling pathways. Notch is a major regulatory pathway involved in cell-fate determination in embryonic and adult scenarios. However, the role of Notch in embryonic pre-implantation development is controversial. In particular, Notch role on blastocyst development and hatching remains elusive, and a complete picture of the transcription and expression patterns of Notch components during this time-period is not available.

Results

This study provided a comprehensive view on the dynamics of individual embryo gene transcription and protein expression patterns of Notch components (receptors Notch1–4; ligands Dll1 and Dll4, Jagged1–2; and effectors Hes1–2), and their relationship with transcription of gene markers of pluripotency and differentiation (Sox2, Oct4, Klf4, Cdx2) during mouse blastocyst development and hatching. Transcription of Notch1–2, Jagged1–2 and Hes1 was highly prevalent and dynamic along stages of development, whereas transcription of Notch3–4, Dll4 and Hes2 had a low prevalence among embryos. Transcription levels of Notch1, Notch2, Jagged2 and Hes1 correlated with each other and with those of pluripotency and differentiation genes. Gene transcription was associated to protein expression, except for Jagged2, where high transcription levels in all embryos were not translated into protein. Presence of Notch signaling activity was confirmed through nuclear NICD and Hes1 detection, and downregulation of Hes1 transcription following canonical signaling blockade with DAPT. In vitro embryo culture supplementation with Jagged1 had no effect on embryo developmental kinetics. In contrast, supplementation with Jagged2 abolished Jagged1 transcription, downregulated Cdx2 transcription and inhibited blastocyst hatching. Notch signaling blockade by DAPT downregulated transcription of Sox2, and retarded embryo hatching.

Conclusion

Transcription of Notch genes showed a dynamic pattern along blastocyst development and hatching. Data confirmed Notch signaling activity, and lead to the suggestion that Notch canonical signaling may be operating through Notch1, Notch3, Jagged1 and Hes1. Embryo culture supplementation with Jagged1 and Jagged2 unveiled a possible regulatory effect between Jagged1, Cdx2 and blastocyst hatching. Overall, results indicate that a deregulation in Notch signaling, either by its over or under-activation, affects blastocyst development and hatching.

The transition from local to global patterns governs the differentiation of mouse blastocysts

During mammalian blastocyst development, inner cell mass (ICM) cells differentiate into epiblast (Epi) or primitive endoderm (PrE). These two fates are characterized by the expression of the transcription factors NANOG and GATA6, respectively. Here, we investigate the spatio-temporal distribution of NANOG and GATA6 expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single cell-based neighbourhood analyses. We define the cell neighbourhood by local features, which include the expression levels of both fate markers expressed in each cell and its neighbours, and the number of neighbouring cells. We further include the position of a cell relative to the centre of the ICM as a global positional feature. Our analyses reveal a local three-dimensional pattern that is already present in early blastocysts: 1) Cells expressing the highest NANOG levels are surrounded by approximately nine neighbours, while 2) cells expressing GATA6 cluster according to their GATA6 levels. This local pattern evolves into a global pattern in the ICM that starts to emerge in mid blastocysts. We show that FGF/MAPK signalling is involved in the three-dimensional distribution of the cells and, using a mutant background, we further show that the GATA6 neighbourhood is regulated by NANOG. Our quantitative study suggests that the three-dimensional cell neighbourhood plays a role in Epi and PrE precursor specification. Our results highlight the importance of analysing the three-dimensional cell neighbourhood while investigating cell fate decisions during early mouse embryonic development.

A non-linear reverse-engineering method for inferring genetic regulatory networks

Hematopoiesis is a highly complex developmental process that produces various types of blood cells. This process is regulated by different genetic networks that control the proliferation, differentiation, and maturation of hematopoietic stem cells (HSCs). Although substantial progress has been made for understanding hematopoiesis, the detailed regulatory mechanisms for the fate determination of HSCs are still unraveled. In this study, we propose a novel approach to infer the detailed regulatory mechanisms. This work is designed to develop a mathematical framework that is able to realize nonlinear gene expression dynamics accurately. In particular, we intended to investigate the effect of possible protein heterodimers and/or synergistic effect in genetic regulation. This approach includes the Extended Forward Search Algorithm to infer network structure (top-down approach) and a non-linear mathematical model to infer dynamical property (bottom-up approach). Based on the published experimental data, we study two regulatory networks of 11 genes for regulating the erythrocyte differentiation pathway and the neutrophil differentiation pathway. The proposed algorithm is first applied to predict the network topologies among 11 genes and 55 non-linear terms which may be for heterodimers and/or synergistic effect. Then, the unknown model parameters are estimated by fitting simulations to the expression data of two different differentiation pathways. In addition, the edge deletion test is conducted to remove possible insignificant regulations from the inferred networks. Furthermore, the robustness property of the mathematical model is employed as an additional criterion to choose better network reconstruction results. Our simulation results successfully realized experimental data for two different differentiation pathways, which suggests that the proposed approach is an effective method to infer the topological structure and dynamic property of genetic regulations.

scRCMF: Identification of Cell Subpopulations and Transition States From Single-Cell Transcriptomes

Single cell technologies provide an unprecedented opportunity to explore the heterogeneity in a biological process at the level of single cells. One major challenge in analyzing single cell data is to identify cell subpopulations, stable cell states, and cells in transition between states. To elucidate the transition mechanisms in cell fate dynamics, it is highly desirable to quantitatively characterize cellular states and intermediate states. Here, we present scRCMF, an unsupervised method that identifies stable cell states and transition cells by adopting a nonlinear optimization model that infers the latent substructures from a gene-cell matrix. We incorporate a random coefficient matrix-based regularization into the standard nonnegative matrix decomposition model to improve the reliability and stability of estimating latent substructures. To quantify the transition capability of each cell, we propose two new measures: single-cell transition entropy (scEntropy) and transition probability (scTP). When applied to two simulated and three published scRNA-seq datasets, scRCMF not only successfully captures multiple subpopulations and transition processes in large-scale data, but also identifies transition states and some known marker genes associated with cell state transitions and subpopulations. Furthermore, the quantity scEntropy is found to be significantly higher for transition cells than other cellular states during the global differentiation, and the scTP predicts the "fate decisions" of transition cells within the transition. The present study provides new insights into transition events during differentiation and development.

Cell Atlas technologies and insights into tissue architecture

Since Robert Hooke first described the existence of 'cells' in 1665, scientists have sought to identify and further characterise these fundamental units of life. While our understanding of cell location, morphology and function has expanded greatly; our understanding of cell types and states at the molecular level, and how these function within tissue architecture, is still limited. A greater understanding of our cells could revolutionise basic biology and medicine. Atlasing initiatives like the Human Cell Atlas aim to identify all cell types at the molecular level, including their physical locations, and to make this reference data openly available to the scientific community. This is made possible by a recent technology revolution: both in single-cell molecular profiling, particularly single-cell RNA sequencing, and in spatially resolved methods for assessing gene and protein expression. Here, we review available and upcoming atlasing technologies, the biological insights gained to date and the promise of this field for the future.

Inherent mitochondrial activity influences specification of the germ line in pluripotent stem cells

Herein we investigated whether inherent differences in mitochondrial activity in mouse pluripotent cells could be used to identify populations with an intrinsic ability to differentiate into primordial germ cells (PGCs). Notably, we determined that stem cells sorted based on differences in mitochondrial membrane activity exhibited altered germline differentiation capacity, with low-mitochondrial membrane potential associated with an increase in PGC-like cells. This specification was not further enhanced by hypoxia. We additionally noted differences between these populations in metabolism, transcriptome, and cell-cycle. These data contribute to a growing body of work demonstrating that pluripotent cells exhibit a large range of mitochondrial activity, which impacts cellular function and differentiation potential. Furthermore, pluripotent cells possess a subpopulation of cells with an improved ability to differentiate into the germ lineage that can be identified based on differences in mitochondrial membrane potential.

Derivation of porcine extraembryonic endoderm-like cells from blastocysts

OBJECTIVES

Extraembryonic endoderm (XEN) cells are isolated from primitive endoderm (PrE) of blastocysts. Just like PrE, XEN cells have the ability to differentiate into parietal endoderm (PE) and visceral endoderm (VE), and therefore, they are useful tools for studying mechanisms of PrE cells development and differentiation. Pig is an ideal model for studying human cardiovascular and metabolic diseases and a potential organ source for allotransplantation, while no XEN cell has been obtained from porcine embryos.

MATERIALS AND METHODS

Using a serum-free culture system, we directly derived porcine extraembryonic endoderm-like cells (pXEN-like cells) from day 6-7 blastocysts, which could maintain self-renewal for at least 30 passages.

RESULTS

The pXEN-like cells resembled mouse XEN cells with large and flat clone morphology and expressed XEN marker genes but not pluripotent genes. Upon in vitro induction, the cells could differentiate into VE and PE. FGF/MEK signalling was not only essential for the maintenance of pXEN-like cells, but also the induction of pXEN-like cells from porcine embryonic stem (pES) cells.

CONCLUSIONS

We directly obtained cell lines with XEN characteristics from porcine embryos for the first time. The cells will be helpful tools for studying embryonic development and cell differentiation, which also represent promising cell sources for human regenerative medicine.

Specification of the First Mammalian Cell Lineages In Vivo and In Vitro

Our understanding of how the first mammalian cell lineages arise has been shaped largely by studies of the preimplantation mouse embryo. Painstaking work over many decades has begun to reveal how a single totipotent cell is transformed into a multilayered structure representing the foundations of the body plan. Here, we review how the first lineage decision is initiated by epigenetic regulation but consolidated by the integration of morphological features and transcription factor activity. The establishment of pluripotent and multipotent stem cell lines has enabled deeper analysis of molecular and epigenetic regulation of cell fate decisions. The capability to assemble these stem cells into artificial embryos is an exciting new avenue of research that offers a long-awaited window into cell fate specification in the human embryo. Together, these approaches are poised to profoundly increase our understanding of how the first lineage decisions are made during mammalian embryonic development.

Unsaturated polyurethane films grafted with enantiomeric polylysine promotes macrophage polarization to a M2 phenotype through PI3K/Akt1/mTOR axis

The immune system responds immediately to tissue trauma and to biomaterial implants under the participation of M1/M2 macrophages polarization. The surface properties of biomaterials can significantly influence the tissue repair progress through modulating the macrophage functions. In this study, the surface of poly(propylene fumarate) polyurethane films (PPFU) is grafted with a same density of enantiomeric poly-l-lysine (PPFU-g-PLL) and poly-d-lysine (PPFU-g-PDL), leading to a similar level of enhanced surface wettability for the PPFU-g-PLL and PPFU-g-PDL. The polylysine-grafted PPFU can restrict the M1 polarization, whereas promote M2 polarization of macrophages in vitro, judging from the secretion of cytokines and expression of key M1 and M2 related genes. Comparatively, the PPFU-g-PDL has a stronger effect in inducing M2 polarization in vivo, resulting in a thinner fibrous capsule surrounding the implant biomaterials. The CD44 and integrins of macrophages participate in the polarization process probably by activating focal adhesion kinase (FAK) and Rho-associated protein kinase (ROCK), and downstream PI3K/Akt1/mTOR signal axis to up regulate M2 related gene expression. This study confirms for the first time that polylysine coating is an effective method to regulate the immune response of biomaterials, and the polylysine-modified thermoplastic PPFU with the advantage to promote M2 polarization may be applied widely in regenerative medicine.

The Transcription Factor OVOL2 Represses ID2 and Drives Differentiation of Trophoblast Stem Cells and Placental Development in Mice

Trophoblasts are the first cell type to be specified during embryogenesis, and they are essential for placental morphogenesis and function. Trophoblast stem (TS) cells are the progenitor cells for all trophoblast lineages; control of TS cell differentiation into distinct trophoblast subtypes is not well understood. Mice lacking the transcription factor OVO-like 2 (OVOL2) fail to produce a functioning placenta, and die around embryonic day 10.5, suggesting that OVOL2 may be critical for trophoblast development. Therefore, our objective was to determine the role of OVOL2 in mouse TS cell fate. We found that OVOL2 was highly expressed in mouse placenta and differentiating TS cells. Placentas and TS cells lacking OVOL2 showed poor trophoblast differentiation potential, including increased expression of stem-state associated genes (Eomes, Esrrb, Id2) and decreased levels of differentiation-associated transcripts (Gcm1, Tpbpa, Prl3b1, Syna). Ectopic OVOL2 expression in TS cells elicited precocious differentiation. OVOL2 bound proximate to the gene encoding inhibitor of differentiation 2 (ID2), a dominant negative helix-loop-helix protein, and directly repressed its activity. Overexpression of ID2 was sufficient to reinforce the TS cell stem state. Our findings reveal a critical role of OVOL2 as a regulator of TS cell differentiation and placental development, in-part by coordinating repression of ID2.

ROCK and RHO Playlist for Preimplantation Development: Streaming to HIPPO Pathway and Apicobasal Polarity in the First Cell Differentiation

In placental mammalian development, the first cell differentiation produces two distinct lineages that emerge according to their position within the embryo: the trophectoderm (TE, placenta precursor) differentiates in the surface, while the inner cell mass (ICM, fetal body precursor) forms inside. Here, we discuss how such position-dependent lineage specifications are regulated by the RHOA subfamily of small GTPases and RHO-associated coiled-coil kinases (ROCK). Recent studies in mouse show that activities of RHO/ROCK are required to promote TE differentiation and to concomitantly suppress ICM formation. RHO/ROCK operate through the HIPPO signaling pathway, whose cell position-specific modulation is central to establishing unique gene expression profiles that confer cell fate. In particular, activities of RHO/ROCK are essential in outside cells to promote nuclear localization of transcriptional co-activators YAP/TAZ, the downstream effectors of HIPPO signaling. Nuclear localization of YAP/TAZ depends on the formation of apicobasal polarity in outside cells, which requires activities of RHO/ROCK. We propose models of how RHO/ROCK regulate lineage specification and lay out challenges for future investigations to deepen our understanding of the roles of RHO/ROCK in preimplantation development. Finally, as RHO/ROCK may be inhibited by certain pharmacological agents, we discuss their potential impact on human preimplantation development in relation to fertility preservation in women.

CALISTA: Clustering and LINEAGE Inference in Single-Cell Transcriptional Analysis

We present Clustering and Lineage Inference in Single-Cell Transcriptional Analysis (CALISTA), a numerically efficient and highly scalable toolbox for an end-to-end analysis of single-cell transcriptomic profiles. CALISTA includes four essential single-cell analyses for cell differentiation studies, including single-cell clustering, reconstruction of cell lineage specification, transition gene identification, and cell pseudotime ordering, which can be applied individually or in a pipeline. In these analyses, we employ a likelihood-based approach where single-cell mRNA counts are described by a probabilistic distribution function associated with stochastic gene transcriptional bursts and random technical dropout events. We illustrate the efficacy of CALISTA using single-cell gene expression datasets from different single-cell transcriptional profiling technologies and from a few hundreds to tens of thousands of cells. CALISTA is freely available on https://www.cabselab.com/calista.

Progress and applications of single-cell sequencing techniques

Single-cell sequencing (SCS) is a next-generation sequencing method that is mainly used to analyze differences in genetic and protein information between cells, to obtain genetic information on microorganisms that are difficult to cultivate at a single-cell level and to better understand their specific roles in the microenvironment. By sequencing the whole genome, transcriptome and epigenome of a single cell, the complex heterogeneous mechanisms involved in disease occurrence and progression can be revealed, further improving disease diagnosis, prognosis prediction and monitoring of the therapeutic effects of drugs. In this study, we mainly summarized the methods and application fields of SCS, which may provide potential references for its future clinical applications, including the analysis of embryonic and organ development, the immune system, cancer progression, and parasitic and infectious diseases as well as stem cell research, antibody screening, and therapeutic research and development.

Phosphorylation of TFCP2L1 by CDK1 is required for stem cell pluripotency and bladder carcinogenesis

Molecular programs involved in embryogenesis are frequently upregulated in oncogenic dedifferentiation and metastasis. However, their precise roles and regulatory mechanisms remain elusive. Here, we showed that CDK1 phosphorylation of TFCP2L1, a pluripotency-associated transcription factor, orchestrated pluripotency and cell-cycling in embryonic stem cells (ESCs) and was aberrantly activated in aggressive bladder cancers (BCs). In murine ESCs, the protein interactome and transcription targets of Tfcp2l1 indicated its involvement in cell cycle regulation. Tfcp2l1 was phosphorylated at Thr177 by Cdk1, which affected ESC cell cycle progression, pluripotency, and differentiation. The CDK1-TFCP2L1 pathway was activated in human BC cells, stimulating their proliferation, self-renewal, and invasion. Lack of TFCP2L1 phosphorylation impaired the tumorigenic potency of BC cells in a xenograft model. In patients with BC, high co-expression of TFCP2L1 and CDK1 was associated with unfavorable clinical characteristics including tumor grade, lymphovascular and muscularis propria invasion, and distant metastasis and was an independent prognostic factor for cancer-specific survival. These findings demonstrate the molecular and clinical significance of CDK1-mediated TFCP2L1 phosphorylation in stem cell pluripotency and in the tumorigenic stemness features associated with BC progression.

Methods for Single-Cell Isolation and Preparation

Within the last decade, single-cell analysis has revolutionized our understanding of cellular processes and heterogeneity across all disciplines of life science. As the transcriptome, genome, or epigenome of individual cells can nowadays be analyzed at low cost and in high-throughput within a few days by modern techniques, tremendous improvements in disease diagnosis on the one hand and the investigation of disease-relevant mechanisms on the other were achieved so far. This relies on the parallel development of reliable cell capturing and single-cell sequencing approaches that have paved the way for comprehensive single-cell studies. Apart from single-cell isolation methods in high-throughput, a variety of methods with distinct specializations were developed, allowing for correlation of transcriptomics with cellular parameters like electrophysiology or morphology.For all single-cell-based approaches, accurate and reliable isolation with proper quality controls is prerequisite, whereby different options exist dependent on sample type and tissue properties. Careful consideration of an appropriate method is required to avoid incorrect or biased data that may lead to misinterpretations.In this chapter, we will provide a broad overview of the current state of the art in matters of single-cell isolation methods mostly applied for sequencing-based downstream analysis, and their respective advantages and drawbacks. Distinct technologies will be discussed in detail addressing key parameters like sample compatibility, viability, purity, throughput, and isolation efficiency.

A cluster robustness score for identifying cell subpopulations in single cell gene expression datasets from heterogeneous tissues and tumors

MOTIVATION

A major aim of single cell biology is to identify important cell types such as stem cells in heterogeneous tissues and tumors. This is typically done by isolating hundreds of individual cells and measuring expression levels of multiple genes simultaneously from each cell. Then, clustering algorithms are used to group together similar single-cell expression profiles into clusters, each representing a distinct cell type. However, many of these clusters result from overfitting, meaning that rather than representing biologically meaningful cell types, they describe the intrinsic 'noise' in gene expression levels due to limitations in experimental precision or the intrinsic randomness of biochemical cellular processes. Consequentially, these non-meaningful clusters are most sensitive to noise: a slight shift in gene expression levels due to a repeated measurement will rearrange the grouping of data points such that these clusters break up.

RESULTS

To identify the biologically meaningful clusters we propose a 'cluster robustness score': We add increasing amounts of noise (zero mean and increasing variance) and check which clusters are most robust in the sense that they do not mix with their neighbors up to high levels of noise. We show that biologically meaningful cell clusters that were manually identified in previously published single cell expression datasets have high robustness scores. These scores are higher than what would be expected in corresponding randomized homogeneous datasets having the same expression level statistics. We believe that this scoring system provides a more automated way to identify cell types in heterogeneous tissues and tumors.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Single-cell analysis of CD8 T lymphocyte diversity during adaptive immunity

An effective adaptive immune response to microbial infection relies on the generation of heterogeneous T lymphocyte fates and functions. CD8 T lymphocytes play a pivotal role in mediating immediate and long-term protective immune responses to intracellular pathogen infection. Systems-based analysis of the immune response to infection has begun to identify cell fate determinants and the molecular mechanisms underpinning CD8 T lymphocyte diversity at single-cell resolution. Resolving CD8 T lymphocyte heterogeneity during adaptive immunity highlights the advantages of single-cell technologies and computational approaches to better understand the ontogeny of CD8 T cellular diversity following infection. Future directions of integrating single-cell multiplex approaches capitalize on the importance of systems biology in the understanding of immune CD8 T cell differentiation and functional diversity. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Biological Mechanisms > Cell Fates.

Reconstructing complex lineage trees from scRNA-seq data using MERLoT

Advances in single-cell transcriptomics techniques are revolutionizing studies of cellular differentiation and heterogeneity. It has become possible to track the trajectory of thousands of genes across the cellular lineage trees that represent the temporal emergence of cell types during dynamic processes. However, reconstruction of cellular lineage trees with more than a few cell fates has proved challenging. We present MERLoT (https://github.com/soedinglab/merlot), a flexible and user-friendly tool to reconstruct complex lineage trees from single-cell transcriptomics data. It can impute temporal gene expression profiles along the reconstructed tree. We show MERLoT’s capabilities on various real cases and hundreds of simulated datasets.

Trophectoderm regeneration to support full-term development in the inner cell mass isolated from bovine blastocyst

Which comes first: tissue structure or cell differentiation? Although different cell types establish distinct structures delineating the inside and outside of an embryo, they progressively become specified by the blastocyst stage, when two types of cell lineages are formed: the inner cell mass (ICM) and the trophectoderm (TE). This inside-outside aspect can be experimentally converted by the isolation of the ICM from a blastocyst, leading to a posteriori externalization of the blastomeres composing the outermost layer of the ICM. Here, we investigated the totipotency of isolated mouse and bovine ICMs to determine whether they are competent for TE regeneration. Surprisingly, a calf was generated from the bovine isolated ICM with re-formed blastocoel (re-iICM), but no mouse re-iICMs developed to term. To further explore the cause of difference in developmental competency between the mouse and bovine re-iICMs, we investigated the SOX17 protein expression that is a representative molecular marker of primitive endoderm. The localization pattern of SOX17 was totally different between mouse and bovine embryos. Particularly, the ectopic SOX17 localization in the TE might be associated with lethality of mouse re-iICMs. Meanwhile, transcriptome sequencing revealed that some of the bovine re-iICMs showed transcriptional patterns of TE-specific genes similar to those of whole blastocysts. Our findings suggest that TE regeneration competency is maintained longer in bovine ICMs than in mouse ICMs and provide evidence that the ICM/TE cell fate decision is influenced by structural determinants, including positional information of each blastomere in mammalian embryos.

Global transcriptome analysis of different stages of preimplantation embryo development in river buffalo

Background

Water buffalo (Bubalus bubalis) are divided into river buffalo and swamp buffalo subspecies and are essential livestock for agriculture and the local economy. Studies on buffalo reproduction have primarily focused on optimal fertility and embryonic mortality. There is currently limited knowledge on buffalo embryonic development, especially during the preimplantation period. Assembly of the river buffalo genome offers a reference for omics studies and facilitates transcriptomic analysis of preimplantation embryo development (PED).

Methods

We revealed transcriptomic profile of four stages (2-cell, 8-cell, Morula and Blastocyst) of PED via RNA-seq (Illumina HiSeq4000). Each stage comprised three biological replicates. The data were analyzed according to the basic RNA-seq analysis process. Ingenuity analysis of cell lineage control, especially transcription factor (TF) regulatory networks, was also performed.

Results

A total of 21,519 expressed genes and 67,298 transcripts were predicted from approximately 81.94 Gb of raw data. Analysis of transcriptome-wide expression, gene coexpression networks, and differentially expressed genes (DEGs) allowed for the characterization of gene-specific expression levels and relationships for each stage. The expression patterns of TFs, such as POU5F1, TEAD4, CDX4 and GATAs, were elucidated across diverse time series; most TF expression levels were increased during the blastocyst stage, during which time cell differentiation is initiated. All of these TFs were involved in the composition of the regulatory networks that precisely specify cell fate. These findings offer a deeper understanding of PED at the transcriptional level in the river buffalo.