RNA-Seq analysis to capture the transcriptome landscape of a single cell

Single-Cell Transcriptomics Revealed White Matter Repair Following Subarachnoid Hemorrhage

Existing research indicates the potential for white matter injury repair during the subacute phase following subarachnoid hemorrhage (SAH). However, elucidating the role of brain cell subpopulations in the acute and subacute phases of SAH pathogenesis remains challenging due to the cellular heterogeneity of the central nervous system. In this study, single-cell RNA sequencing was conducted on SAH model mice to delineate distinct cell populations. Gene Set Enrichment Analysis was performed to identify involved pathways, and cellular interactions were explored using the CellChat package in R software. Validation of the findings involved a comprehensive approach, including magnetic resonance imaging, immunofluorescence double staining, and Western blot analyses. This study identified ten major brain clusters with cell type-specific gene expression patterns. Notably, we observed infiltration and clonal expansion of reparative microglia in white matter-enriched regions during the subacute stage after SAH. Additionally, microglia-associated pleiotrophin (PTN) was identified as having a role in mediating the regulation of oligodendrocyte precursor cells (OPCs) in SAH model mice, implicating the activation of the mTOR signaling pathway. These findings emphasize the vital role of microglia-OPC interactions might occur via the PTN pathway, potentially contributing to white matter repair during the subacute phase after SAH. Our analysis revealed precise transcriptional changes in the acute and subacute phases after SAH, offering insights into the mechanism of SAH and for the development of drugs that target-specific cell subtypes.

Transcriptomic Analysis of the Spatiotemporal Axis of Oogenesis and Fertilization in C. elegans

The oocyte germline of the C. elegans hermaphrodite presents a unique model to study the formation of oocytes. However, the size of the model animal and difficulties in retrieval of specific stages of the germline have obviated closer systematic studies of this process throughout the years. Here, we present a transcriptomic level analysis into the oogenesis of C. elegans hermaphrodites. We dissected a hermaphrodite gonad into seven sections corresponding to the mitotic distal region, the pachytene, the diplotene, the early diakinesis region and the 3 most proximal oocytes, and deeply sequenced the transcriptome of each of them along with that of the fertilized egg using a single-cell RNA-seq protocol. We identified specific gene expression events as well as gene splicing events in finer detail along the oocyte germline and provided novel insights into underlying mechanisms of the oogenesis process. Furthermore, through careful review of relevant research literature coupled with patterns observed in our analysis, we attempt to delineate transcripts that may serve functions in the interaction between the germline and cells of the somatic gonad. These results expand our knowledge of the transcriptomic space of the C. elegans germline and lay a foundation on which future studies of the germline can be based upon.

Single-cell omics identifies inflammatory signaling as a trans-differentiation trigger in mouse embryos

Trans-differentiation represents a direct lineage conversion; however, insufficient characterization of this process hinders its potential applications. Here, to explore a potential universal principal for trans-differentiation, we performed single-cell transcriptomic analysis of endothelial-to-hematopoietic transition (EHT), endothelial-to-mesenchymal transition, and epithelial-to-mesenchymal transition in mouse embryos. We applied three scoring indexes of entropies, cell-type signature transcription factor expression, and critical transition signals to show common features underpinning the fate plasticity of transition states. Cross-model comparison identified inflammatory-featured transition states and a common trigger role of interleukin-33 in promoting fate conversions. Multimodal profiling (integrative transcriptomic and chromatin accessibility analysis) demonstrated the inflammatory regulation of hematopoietic specification. Furthermore, multimodal omics and fate-mapping analyses showed that endothelium-specific Spi1, as an inflammatory effector, governs appropriate chromatin accessibility and transcriptional programs to safeguard EHT. Overall, our study employs single-cell omics to identify critical transition states/signals and the common trigger role of inflammatory signaling in developmental-stress-induced fate conversions.

Imprinted X chromosome inactivation at the gamete-to-embryo transition

In mammals, dosage compensation involves two parallel processes: (1) X inactivation, which equalizes X chromosome dosage between males and females, and (2) X hyperactivation, which upregulates the active X for X-autosome balance. The field currently favors models whereby dosage compensation initiates "de novo" during mouse development. Here, we develop "So-Smart-seq" to revisit the question and interrogate a comprehensive transcriptome including noncoding genes and repeats in mice. Intriguingly, de novo silencing pertains only to a subset of Xp genes. Evolutionarily older genes and repetitive elements demonstrate constitutive Xp silencing, adopt distinct signatures, and do not require Xist to initiate silencing. We trace Xp silencing backward in developmental time to meiotic sex chromosome inactivation in the male germ line and observe that Xm hyperactivation is timed to Xp silencing on a gene-by-gene basis. Thus, during the gamete-to-embryo transition, older Xp genes are transmitted in a "pre-inactivated" state. These findings have implications for the evolution of imprinting.

Application of Single-Cell Sequencing Technology in Research on Colorectal Cancer

Colorectal cancer (CRC) is the third most prevalent and second most lethal cancer globally, with gene mutations and tumor metastasis contributing to its poor prognosis. Single-cell sequencing technology enables high-throughput analysis of the genome, transcriptome, and epigenetic landscapes at the single-cell level. It offers significant insights into analyzing the tumor immune microenvironment, detecting tumor heterogeneity, exploring metastasis mechanisms, and monitoring circulating tumor cells (CTCs). This article provides a brief overview of the technical procedure and data processing involved in single-cell sequencing. It also reviews the current applications of single-cell sequencing in CRC research, aiming to enhance the understanding of intratumoral heterogeneity, CRC development, CTCs, and novel drug targets. By exploring the diverse molecular and clinicopathological characteristics of tumor heterogeneity using single-cell sequencing, valuable insights can be gained into early diagnosis, therapy, and prognosis of CRC. Thus, this review serves as a valuable resource for identifying prognostic markers, discovering new therapeutic targets, and advancing personalized therapy in CRC.

Overview: Research on the Genetic Architecture of the Developing Cerebral Cortex in Norms and Diseases

The human brain is characterized by high cell numbers, diverse cell types with diverse functions, and intricate connectivity with an exceedingly broad surface of the cortex. Human-specific brain development was accomplished by a long timeline for maturation from the prenatal period to the third decade of life. The long timeline makes complicated architecture and circuits of human cerebral cortex possible, and it makes human brain vulnerable to intrinsic and extrinsic insults resulting in the development of variety of neuropsychiatric disorders. Unraveling the molecular and cellular processes underlying human brain development under the elaborate regulation of gene expression in a spatiotemporally specific manner, especially that of the cortex will provide a biological understanding of human cognition and behavior in health and diseases. Global research consortia and the advancing technologies in brain science including functional genomics equipped with emergent neuroinformatics such as single-cell multiomics, novel human models, and high-volume databases with high-throughput computation facilitate the biological understanding of the development of the human brain cortex. Knowing the process of interplay of the genome and the environment in cortex development will lead us to understand the human-specific cognitive function and its individual diversity. Thus, it is worthwhile to overview the recent progress in neurotechnology to foresee further understanding of the human brain and norms and diseases.

Maternal RNA binding protein with multiple splicing 2 (RBPMS2) is involved in mouse blastocyst formation through the bone morphogenetic protein pathway

RESEARCH QUESTION

Is early embryo development in mice influenced by RNA binding protein with multiple splicing 2 (RBPMS2), a maternal factor that accumulates and is stored in the cytoplasm of mature oocytes?

DESIGN

The expression patterns of RBPMS2 in mouse were analysed using quantitative real-time PCR (qRT PCR) and immunofluorescence staining. The effect of knockdown of RBPMS2 on embryo development was evaluated through a microinjection of specific morpholino or small interfering RNA. RNA sequencing was performed for mechanistic analysis. The interaction between RBPMS2 and the bone morphogenetic protein (BMP) pathway was studied using BMP inhibitor and activator. The effect on the localization of E-cadherin was determined by immunofluorescence staining.

RESULTS

Maternal protein RBPMS2 is highly expressed in mouse oocytes, and knockdown of RBPMS2 inhibits embryo development from the morula to the blastocyst stage. Mechanistically, RNA sequencing showed that the differentially expressed genes were enriched in the transforming growth factor-β (TGF-β) signalling pathway. BMPs are members of the TGF-β superfamily of growth factors. It was found that the addition of BMP inhibitor to the culture medium led to a morula-stage arrest, similar to that seen in RBPMS2 knockdown embryos. This morula-stage arrest defect caused by RBPMS2 knockdown was partially rescued by BMP activator. Furthermore, the localization of E-cadherin to the membrane was impaired in response to a knockdown of RBPMS2 or inhibition of the BMP pathway.

CONCLUSION

This study suggests that RBPMS2 activates the BMP pathway and thus influences the localization of E-cadherin, which is important for early mouse embryo development during blastocyst formation.

Microfluidic design in single-cell sequencing and application to cancer precision medicine

Single-cell sequencing (SCS) is a crucial tool to reveal the genetic and functional heterogeneity of tumors, providing unique insights into the clonal evolution, microenvironment, drug resistance, and metastatic progression of cancers. Microfluidics is a critical component of many SCS technologies and workflows, conferring advantages in throughput, economy, and automation. Here, we review the current landscape of microfluidic architectures and sequencing techniques for single-cell omics analysis and highlight how these have enabled recent applications in oncology research. We also discuss the challenges and the promise of microfluidics-based single-cell analysis in the future of precision oncology.

Use of cutting-edge RNA-sequencing technology to identify biomarkers and potential therapeutic targets in canine and feline cancers and other diseases

With the growing interest in companion animals and the rapidly expanding animal healthcare and pharmaceuticals market worldwide. With the advancements in RNA-sequencing (RNA-seq) technology, it has become a valuable tool for understanding biological processes in companion animals and has multiple applications in animal healthcare. Historically, veterinary diagnoses and treatments relied solely on clinical symptoms and drugs used in human diseases. However, RNA-seq has emerged as an effective technology for studying companion animals, providing insights into their genetic information. The sequencing technology has revealed that not only messenger RNAs (mRNAs) but also non-coding RNAs (ncRNAs) such as long ncRNAs and microRNAs can serve as biomarkers. Based on the examination of RNA-seq applications in veterinary medicine, particularly in dogs and cats, this review concludes that RNA-seq has significant potential as a diagnostic and research tool. It has enabled the identification of potential biomarkers for cancer and other diseases in companion animals. Further research and development are required to maximize the utilization of RNA-seq for improved disease diagnosis and therapeutic targeting in companion animals.

Intrinsic neural diversity quenches the dynamic volatility of neural networks

Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and ion channel distributions. While this biophysical diversity enriches neural systems' dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time (resilience). To better understand the relationship between excitability heterogeneity (variability in excitability within a population of neurons) and resilience, we analyzed both analytically and numerically a nonlinear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. Homogeneous networks demonstrated increases in excitability, and strong firing rate correlations-signs of instability-in response to a slowly varying modulatory fluctuation. Excitability heterogeneity tuned network stability in a context-dependent way by restraining responses to modulatory challenges and limiting firing rate correlations, while enriching dynamics during states of low modulatory drive. Excitability heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in population size, connection probability, strength and variability of synaptic weights, by quenching the volatility (i.e., its susceptibility to critical transitions) of its dynamics. Together, these results highlight the fundamental role played by cell-to-cell heterogeneity in the robustness of brain function in the face of change.

Activation of lineage competence in hemogenic endothelium precedes the formation of hematopoietic stem cell heterogeneity

Hematopoietic stem and progenitor cells (HSPCs) are considered as a heterogeneous population, but precisely when, where and how HSPC heterogeneity arises remain largely unclear. Here, using a combination of single-cell multi-omics, lineage tracing and functional assays, we show that embryonic HSPCs originate from heterogeneous hemogenic endothelial cells (HECs) during zebrafish embryogenesis. Integrated single-cell transcriptome and chromatin accessibility analysis demonstrates transcriptional heterogeneity and regulatory programs that prime lymphoid/myeloid fates at the HEC level. Importantly, spi2+ HECs give rise to lymphoid/myeloid-primed HSPCs (L/M-HSPCs) and display a stress-responsive function under acute inflammation. Moreover, we uncover that Spi2 is required for the formation of L/M-HSPCs through tightly controlling the endothelial-to-hematopoietic transition program. Finally, single-cell transcriptional comparison of zebrafish and human HECs and human induced pluripotent stem cell-based hematopoietic differentiation results support the evolutionary conservation of L/M-HECs and a conserved role of SPI1 (spi2 homolog in mammals) in humans. These results unveil the lineage origin, biological function and molecular determinant of HSPC heterogeneity and lay the foundation for new strategies for induction of transplantable lineage-primed HSPCs in vitro.

Metabolism-based cardiomyocytes production for regenerative therapy

Human pluripotent stem cells (hPSCs) are currently used in clinical applications such as cardiac regenerative therapy, studying disease models, and drug screening for heart failure. Transplantation of hPSC-derived cardiomyocytes (hPSC-CMs) can be used as an alternative therapy for heart transplantation. In contrast to differentiated somatic cells, hPSCs possess unique metabolic programs to maintain pluripotency, and understanding their metabolic features can contribute to the development of technologies that can be useful for their clinical applications. The production of hPSC-CMs requires stepwise specification during embryonic development and metabolic regulation is crucial for proper embryonic development. These metabolic features have been applied to hPSC-CM production methods, such as mesoderm induction, specifications for cardiac progenitors, and their maturation. This review describes the metabolic programs in hPSCs and the metabolic regulation in hPSC-CM production for cardiac regenerative therapy.

Transcriptomic changes in single yeast cells under various stress conditions

BACKGROUND

The stress response of Saccharomyces cerevisiae has been extensively studied in the past decade. However, with the advent of recent technology in single-cell transcriptome profiling, there is a new opportunity to expand and further understanding of the yeast stress response with greater resolution on a system level. To understand transcriptomic changes in baker's yeast S. cerevisiae cells under stress conditions, we sequenced 117 yeast cells under three stress treatments (hypotonic condition, glucose starvation and amino acid starvation) using a full-length single-cell RNA-Seq method.

RESULTS

We found that though single cells from the same treatment showed varying degrees of uniformity, technical noise and batch effects can confound results significantly. However, upon careful selection of samples to reduce technical artifacts and account for batch-effects, we were able to capture distinct transcriptomic signatures for different stress conditions as well as putative regulatory relationships between transcription factors and target genes.

CONCLUSION

Our results show that a full-length single-cell based transcriptomic analysis of the yeast may help paint a clearer picture of how the model organism responds to stress than do bulk cell population-based methods.

Two Novel lncRNAs Regulate Primordial Germ Cell Development in Zebrafish

Long noncoding RNAs (lncRNAs) are regulatory transcripts in various biological processes. However, the role of lncRNAs in germline development remains poorly understood, especially for fish primordial germ cell (PGC) development. In this study, the lncRNA profile of zebrafish PGC was revealed by single cell RNA-sequencing and bioinformatic prediction. We established the regulation network of lncRNA-mRNA associated with PGC development, from which we identified three novel lncRNAs-lnc172, lnc196, and lnc304-highly expressing in PGCs and gonads. Fluorescent in situ hybridization indicated germline-specific localization of lnc196 and lnc304 in the cytoplasm and nucleus of spermatogonia, spermatocyte, and occyte, and they were co-localized with vasa in the cytoplasm of the spermatogonia. By contrast, lnc172 was localized in the cytoplasm of male germline, myoid cells and ovarian somatic cells. Loss- and gain-of-function experiments demonstrated that knockdown and PGC-specific overexpression of lnc304 as well as universal overexpression of lnc172 significantly disrupted PGC development. In summary, the present study revealed the lncRNA profile of zebrafish PGC and identified two novel lncRNAs associated with PGC development, providing new insights for understanding the regulatory mechanism of PGC development.

The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment

The initiation and progression of tumors are complex. The cancer evolution-development hypothesis holds that the dysregulation of immune balance is caused by the synergistic effect of immune genetic factors and environmental factors that stimulate and maintain non-resolving inflammation. Throughout the cancer development process, this inflammation creates a microenvironment for the evolution and development of cancer. Research on the inflammatory tumor microenvironment (TME) explains the initiation and progression of cancer and guides anti-cancer immunotherapy. Single-cell RNA sequencing (scRNA-seq) can detect the transcription levels of cells at the single-cell resolution level, reveal the heterogeneity and evolutionary trajectory of infiltrated immune cells and cancer cells, and provide insight into the composition and function of each cell group in the inflammatory TME. This paper summarizes the application of scRNA-seq in inflammatory TME.

Single-cell transcriptome sequencing atlas of cassava tuberous root

INTRODUCTION

Single-cell transcriptome sequencing (ScRNA-seq) has emerged as an effective method for examining cell differentiation and development. In non-model plants, it hasn't been employed very much, especially in sink organs that are abundant in secondary metabolites.

RESULTS

In this study, we sequenced the single-cell transcriptomes at two developmental phases of cassava tuberous roots using the technology known as 10x Genomics (S1, S2). In total, 14,566 cells were grouped into 15 different cell types, primarily based on the marker genes of model plants known to exist. In the pseudotime study, the cell differentiation trajectory was defined, and the difference in gene expression between the two stages on the pseudotime axis was compared. The differentiation process of the vascular tissue and cerebral tissue was identified by the trajectory. We discovered the rare cell type known as the casparian strip via the use of up-regulated genes and pseudotime analysis, and we explained how it differentiates from endodermis. The successful creation of a protoplast isolation technique for organs rich in starch was also described in our study.

DISCUSSION

Together, we created the first high-resolution single-cell transcriptome atlas of cassava tuberous roots, which made significant advancements in our understanding of how these roots differentiate and develop.

Identifying Network Biomarkers for Alzheimer's Disease Using Single-Cell RNA Sequencing Data

System-level network-based approaches are an emerging field in the biomedical domain since biological networks can be used to analyze complicated biological processes and complex human disorders more efficiently. Network biomarkers are groups of interconnected molecular components causing perturbations in the entire network topology that can be used as indicators of pathogenic biological processes when studying a given disease. Although in the last years computational systems-based approaches have gained ground on the path to discovering new network biomarkers, in complex diseases like Alzheimer's disease (AD), this approach has still much to offer. Especially the adoption of single-cell RNA sequencing (scRNA-seq) has now become the dominant technology for the study of stochastic gene expression. Toward this orientation, we propose an R workflow that extracts disease-perturbed subpathways within a pathway network. We construct a gene-gene interaction network integrated with scRNA-seq expression profiles, and after network processing and pruning, the most active subnetworks are isolated from the entire network topology. The proposed methodology was applied on a real AD-based scRNA-seq data, providing already existing and new potential AD biomarkers in gene network context.

Multi-lineage Differentiation from Hematopoietic Stem Cells

The hematopoietic stem cells (HSCs) have the ability to differentiate and give rise to all mature blood cells. Commitment to differentiation progressively limits the self-renewal potential of the original HSCs by regulating the level of lineage-specific gene expression. In this review, we will summarize the current understanding of the molecular mechanisms underlying HSC differentiation toward erythroid, myeloid, and lymphocyte lineages. Moreover, we will decipher how the single-cell technologies advance the lineage-biased HSC subpopulations and their differentiation potential.

Identification and mechanistic basis of non-ACE2 blocking neutralizing antibodies from COVID-19 patients with deep RNA sequencing and molecular dynamics simulations

Variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continue to cause disease and impair the effectiveness of treatments. The therapeutic potential of convergent neutralizing antibodies (NAbs) from fully recovered patients has been explored in several early stages of novel drugs. Here, we identified initially elicited NAbs (Ig Heavy, Ig lambda, Ig kappa) in response to COVID-19 infection in patients admitted to the intensive care unit at a single center with deep RNA sequencing (>100 million reads) of peripheral blood as a diagnostic tool for predicting the severity of the disease and as a means to pinpoint specific compensatory NAb treatments. Clinical data were prospectively collected at multiple time points during ICU admission, and amino acid sequences for the NAb CDR3 segments were identified. Patients who survived severe COVID-19 had significantly more of a Class 3 antibody (C135) to SARS-CoV-2 compared to non-survivors (15059.4 vs. 1412.7, p = 0.016). In addition to highlighting the utility of RNA sequencing in revealing unique NAb profiles in COVID-19 patients with different outcomes, we provided a physical basis for our findings via atomistic modeling combined with molecular dynamics simulations. We established the interactions of the Class 3 NAb C135 with the SARS-CoV-2 spike protein, proposing a mechanistic basis for inhibition via multiple conformations that can effectively prevent ACE2 from binding to the spike protein, despite C135 not directly blocking the ACE2 binding motif. Overall, we demonstrate that deep RNA sequencing combined with structural modeling offers the new potential to identify and understand novel therapeutic(s) NAbs in individuals lacking certain immune responses due to their poor endogenous production. Our results suggest a possible window of opportunity for administration of such NAbs when their full sequence becomes available. A method involving rapid deep RNA sequencing of patients infected with SARS-CoV-2 or its variants at the earliest infection time could help to develop personalized treatments using the identified specific NAbs.

Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers around the world. Precision oncology will be crucial for further improving the prognosis of HCC patients. Compared with traditional bulk RNA-seq, single-cell RNA sequencing (scRNA-seq) enables the transcriptomes of a great deal of individual cells assayed in an unbiased manner, showing the potential to deeply reveal tumor heterogeneity. In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. Expression profiles of HCC cells and normal liver cells were first analyzed by maximum relevance minimum redundancy (mRMR) to get a top 50 signature gene feature. For further analysis, the incremental feature selection (IFS) method and leave-one-out cross validation (LOOCV) were conducted to build an optimal classification model and to extract 21 potentially essential biomarkers for HCC cells. Our results provided new insights into HCC pathogenesis that might be valuable for HCC diagnosis and therapy.

Onepot-Seq: capturing single-cell transcriptomes simultaneously in a continuous medium via transient localization of mRNA

The development of single-cell RNA-seq has broadened the spectrum for biological research by providing a high-resolution analysis of cellular heterogeneity. However, the requirement for sophisticated devices for the compartmentalization of cells has limited its widespread applicability. Here, we develop Onepot-Seq, a device-free method, that harnesses the transient localization of mRNA after lysis to capture single-cell transcriptomes simultaneously in a continuous fluid medium. In mixed-species experiments, we obtained high-quality single-cell profiles. Further, cell type-specific poly(A)-conjugated antibodies allow Onepot-Seq to effectively capture target cells in complex populations. Chemical perturbations to cells can be profiled by Onepot-Seq at single-cell resolution. Onepot-Seq should allow routine transcriptional profiling at single-cell resolution, accelerating clinical and scientific discoveries in many fields of science.

Dissecting the process of human neutrophil lineage determination by using alpha-lipoic acid inducing neutrophil deficiency model

Granulocyte-monocyte progenitors (GMPs) differentiate into both neutrophils and monocytes. Recently, uni-potential neutrophil progenitors have been identified both in mice and humans using an array of surface markers. However, how human GMPs commit to neutrophil progenitors and the regulatory mechanisms of fate determination remain incompletely understood. In the present study, we established a human neutrophil deficiency model using the small molecule alpha-lipoic acid. Using this neutrophil deficiency model, we determined that the neutrophil progenitor commitment process from CD371⁺ CD115^– GMPs defined by CD34 and CD15 and discovered that critical signals generated by RNA splicing and rRNA biogenesis regulate the process of early commitment for human early neutrophil progenitors derived from CD371⁺ CD115^– GMPs. These processes were elucidated by single-cell RNA sequencing both in vitro and in vivo derived cells. Sequentially, we identified that the transcription factor ELK1 is essential for human neutrophil lineage commitment using the alpha-lipoic acid (ALA)-inducing neutrophil deficiency model. Finally, we also revealed differential roles for long-ELK1 and short-ELK1, balanced by SF3B1, in the commitment process of neutrophil progenitors. Taken together, we discovered a novel function of ALA in regulating neutrophil lineage specification and identified that the SF3B1-ELK axis regulates the commitment of human neutrophil progenitors from CD371⁺ CD115^– GMPs.

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ALA completely blocks the differentiation of human neutrophils derived from CD34⁺ stem cells in ex-vivo culture.

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CD34 and CD15 could be used to define the early differentiation stages of human neutrophil lineage determination.

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SF3B1-ELK1 signal axis regulates human neutrophil lineage determination.

Histologically resolved multiomics enables precise molecular profiling of human intratumor heterogeneity

Both the composition of cell types and their spatial distribution in a tissue play a critical role in cellular function, organ development, and disease progression. For example, intratumor heterogeneity and the distribution of transcriptional and genetic events in single cells drive the genesis and development of cancer. However, it can be challenging to fully characterize the molecular profile of cells in a tissue with high spatial resolution because microscopy has limited ability to extract comprehensive genomic information, and the spatial resolution of genomic techniques tends to be limited by dissection. There is a growing need for tools that can be used to explore the relationship between histological features, gene expression patterns, and spatially correlated genomic alterations in healthy and diseased tissue samples. Here, we present a technique that combines label-free histology with spatially resolved multiomics in unfixed and unstained tissue sections. This approach leverages stimulated Raman scattering microscopy to provide chemical contrast that reveals histological tissue architecture, allowing for high-resolution in situ laser microdissection of regions of interests. These microtissue samples are then processed for DNA and RNA sequencing to identify unique genetic profiles that correspond to distinct anatomical regions. We demonstrate the capabilities of this technique by mapping gene expression and copy number alterations to histologically defined regions in human oral squamous cell carcinoma (OSCC). Our approach provides complementary insights in tumorigenesis and offers an integrative tool for macroscale cancer tissues with spatial multiomics assessments.

Arginine Regulates Zygotic Genome Activation in Porcine Embryos Under Nutrition Restriction

Arginine has a positive effect on pre-implantation development in pigs. However, the exact mechanism by which arginine promotes embryonic development is undefined. Here, single-cell RNA sequencing technology was applied to porcine in vivo pre-implantation embryos from the zygote to morula stage, it was found that that the expression of arginine metabolism-related genes clearly changed from the 2-cell stage to the 4-cell stage, when zygotic genome activation (ZGA) occurs in porcine embryos. Further analysis showed that arginine metabolism-related genes are significantly correlated with key ZGA genes. To determine the function of arginine in porcine embryos during ZGA, the in vitro fertilization embryos were cultured in PZM-3 medium (0.12 mM arginine, Control group), a modified PZM-3 medium (0 mM arginine, Block group) and a modified PZM-3 medium supplemented with arginine (0.12 mM arginine, Block + Arg group). The results showed that the 4-cell arrest rate was significantly increased in the Block group compared to the Control group (P < 0.05). The 4-cell arrest rate in the Block + Arg group was significantly decreased than that in the Block group (P < 0.05). Meanwhile, the expression of ZGA marker genes and SIRT1 protein in 4-cell embryos was significantly decreased in the Block group compared to the Control group, and their expression was significantly increased in the Block + Arg group. In addition, we observed that the glutathione (GSH), ATP levels, and lipid droplet contents were significantly increased, and the reactive oxygen species (ROS) level was decreased in the Block + Arg group compared to the Block group. Compared with Control group, spermine content in culture medium and the mRNA expression of ornithine decarboxylase1 (ODC1) of embryos in the Block group were significantly decreased (P < 0.05), and those in the Block + Arg group were significantly increased compared with the Block group (P < 0.05). Moreover, when difluoromethylornithine (an inhibitor of ODC1) was added to the modified PZM-3 medium supplemented with arginine, the effect of arginine on ZGA was inhibited. In summary, our findings demonstrated that arginine may regulate ZGA under nutrition restriction in porcine embryos by promoting polyamine synthesis.

NANOG initiates epiblast fate through the coordination of pluripotency genes expression

The epiblast is the source of all mammalian embryonic tissues and of pluripotent embryonic stem cells. It differentiates alongside the primitive endoderm in a “salt and pepper” pattern from inner cell mass (ICM) progenitors during the preimplantation stages through the activity of NANOG, GATA6 and the FGF pathway. When and how epiblast lineage specification is initiated is still unclear. Here, we show that the coordinated expression of pluripotency markers defines epiblast identity. Conversely, ICM progenitor cells display random cell-to-cell variability in expression of various pluripotency markers, remarkably dissimilar from the epiblast signature and independently from NANOG, GATA6 and FGF activities. Coordination of pluripotency markers expression fails in Nanog and Gata6 double KO (DKO) embryos. Collectively, our data suggest that NANOG triggers epiblast specification by ensuring the coordinated expression of pluripotency markers in a subset of cells, implying a stochastic mechanism. These features are likely conserved, as suggested by analysis of human embryos.

Pluripotent epiblast cells segregate from primitive endoderm in the blastocyst inner cell mass (ICM). Here the authors show that mosaic epiblast differentiation during mouse and human preimplantation development initiates stochastically in ICM progenitors, independently of the FGF pathway, and requires NANOG activity

An optimized protocol for single nuclei isolation from clinical biopsies for RNA-seq

Single nuclei RNA sequencing (snRNA-seq) has evolved as a powerful tool to study complex human diseases. Single cell resolution enables the study of novel cell types, biological processes, cell trajectories, and cell-cell signaling pathways. snRNA-seq largely relies on the dissociation of intact nuclei from human tissues. However, the study of complex tissues using small core biopsies presents many technical challenges. Here, an optimized protocol for single nuclei isolation is presented for frozen and RNAlater preserved human kidney biopsies. The described protocol is fast, low cost, and time effective due to the elimination of cell sorting and ultra-centrifugation. Samples can be processed in 90 min or less. This method is effective for obtaining normal nuclei morphology without signs of structural damage. Using snRNA-seq, 16 distinct kidney cell clusters were recovered from normal and peri-transplant acute kidney injury allograft samples, including immune cell clusters. Quality control measurements demonstrated that these optimizations eliminated cellular debris and allowed for a high yield of high-quality nuclei and RNA for library preparation and sequencing. Cellular disassociation did not induce cellular stress responses, which recapitulated transcriptional patterns associated with standardized methods of nuclei isolation. Future applications of this protocol will allow for thorough investigations of small biobank biopsies, identifying cell-specific injury pathways and driving the discovery of novel diagnostics and therapeutic targets.

N6-methyladenosine regulates maternal RNA maintenance in oocytes and timely RNA decay during mouse maternal-to-zygotic transition

N⁶-methyladenosine (m⁶A) and its regulatory components play critical roles in various developmental processes in mammals. However, the landscape and function of m⁶A in early embryos remain unclear owing to limited materials. Here we developed a method of ultralow-input m⁶A RNA immunoprecipitation followed by sequencing to reveal the transcriptome-wide m⁶A landscape in mouse oocytes and early embryos and found unique enrichment and dynamics of m⁶A RNA modifications on maternal and zygotic RNAs, including the transcripts of transposable elements MTA and MERVL. Notably, we found that the maternal protein KIAA1429, a component of the m⁶A methyltransferase complex, was essential for m⁶A deposition on maternal mRNAs that undergo decay after zygotic genome activation and MTA transcripts to maintain their stability in oocytes. Interestingly, m⁶A methyltransferases, especially METTL3, deposited m⁶A on mRNAs transcribed during zygotic genome activation and ensured their decay after the two-cell stage, including Zscan4 and MERVL. Together, our findings uncover the essential functions of m⁶A in specific contexts during the maternal-to-zygotic transition, namely ensuring the stability of mRNAs in oocytes and the decay of two-cell-specific transcripts after fertilization.

Aberrant H3K4me3 modification of epiblast genes of extraembryonic tissue causes placental defects and implantation failure in mouse IVF embryos

Assisted reproductive technology has been widely applied in the treatment of human infertility. However, accumulating evidence indicates that in vitro fertilization (IVF) is associated with a low pregnancy rate, placental defects, and metabolic diseases in offspring. Here, we find that IVF manipulation notably disrupts extraembryonic tissue-specific gene expression, and 334 epiblast (Epi)-specific genes and 24 Epi-specific transcription factors are abnormally expressed in extraembryonic ectoderm (ExE) of IVF embryos at embryonic day 7.5. Combined histone modification analysis reveals that aberrant H3K4me3 modification at the Epi active promoters results in increased expression of these genes in ExE. Importantly, we demonstrate that knockdown of the H3K4me3-recruited regulator Kmt2e, which is highly expressed in IVF embryos, greatly improves the development of IVF embryos and reduces abnormal gene expression in ExE. Our study therefore identifies that abnormal H3K4me3 modification in extraembryonic tissue is a major cause of implantation failure and abnormal placental development of IVF embryos.

Allele-specific H3K9me3 and DNA methylation co-marked CpG-rich regions serve as potential imprinting control regions in pre-implantation embryo

Parental DNA methylation and histone modifications undergo distinct global reprogramming in mammalian pre-implantation embryos, but the landscape of epigenetic crosstalk and its effects on embryogenesis are largely unknown. Here we comprehensively analyse the association between DNA methylation and H3K9me3 reprogramming in mouse pre-implantation embryos and reveal that CpG-rich genomic loci with high H3K9me3 signal and DNA methylation level (CHM) are hotspots of DNA methylation maintenance during pre-implantation embryogenesis. We further profile the allele-specific epigenetic map with unprecedented resolution in gynogenetic and androgenetic embryos, respectively, and identify 1,279 allele-specific CHMs, including 19 known imprinting control regions (ICRs). Our study suggests that 22 ICR-like regions (ICRLRs) may regulate allele-specific transcription similarly to known ICRs, and five of them are confirmed to be important for mouse embryo development. Taken together, our study reveals the widespread existence of allele-specific CHMs and largely extends the scope of allele-specific regulation in mammalian pre-implantation embryos.

DUX4 is a multifunctional factor priming human embryonic genome activation

Double homeobox 4 (DUX4) is expressed at the early pre-implantation stage in human embryos. Here we show that induced human DUX4 expression substantially alters the chromatin accessibility of non-coding DNA and activates thousands of newly identified transcribed enhancer-like regions, preferentially located within ERVL-MaLR repeat elements. CRISPR activation of transcribed enhancers by C-terminal DUX4 motifs results in the increased expression of target embryonic genome activation (EGA) genes ZSCAN4 and KHDC1P1. We show that DUX4 is markedly enriched in human zygotes, followed by intense nuclear DUX4 localization preceding and coinciding with minor EGA. DUX4 knockdown in human zygotes led to changes in the EGA transcriptome but did not terminate the embryos. We also show that the DUX4 protein interacts with the Mediator complex via the C-terminal KIX binding motif. Our findings contribute to the understanding of DUX4 as a regulator of the non-coding genome.

Single-cell RNA-seq and its Applications in the Study of Psychiatric Disorders

Neuroscience is currently one of the most challenging research fields owing to the enormous complexity of the mammalian nervous system. We are yet to understand precise transcriptional programs that govern cell fate during neurodevelopment, resolve the connectome of the mammalian brain, and determine the etiology of various neurodegenerative and psychiatric disorders. Technological advances in the past decade, notably single-cell RNA sequencing, have enabled huge progress in our understanding of such features. Our current knowledge of the transcriptome is largely derived from bulk RNA sequencing, which reveals only the average gene expression of millions of cells, potentially missing out on minor transcriptome differences between cells detectable only at single-cell resolution. Since 2009, several single-cell RNA sequencing techniques have emerged that enable the accurate classification of neuronal and glial cell subtypes beyond classical molecular markers and electrophysiological features and allow the identification of previously unknown cell types. Furthermore, it enables the interrogation of molecular and disease-relevant mechanisms and offers further possibilities for the discovery of new drug targets and disease biomarkers. This review intends to familiarize the reader with the main single-cell RNA sequencing techniques developed throughout the past decade and discusses their application in the fields of brain cell taxonomy, neurodevelopment, and psychiatric disorders.

Single-Cell Transcriptomics Reveals Splicing Features of Adult Neural Stem Cells in the Subventricular Zone

The central nervous system has enormously complex cellular diversity with hundreds of distinct cell types, yet alternative splicing features in single cells of important cell types at neurogenic regions are not well understood. By employing in silico analysis, we systematically identified 3,611 alternative splicing events from 1,908 genes in 28 single-cell transcriptomic data of adult mouse ependymal and subependymal regions, and found that single-cell RNA-seq has the advantage in uncovering rare splicing isoforms compared to bulk RNA-seq at the population level. We uncovered that the simultaneous presence of multiple isoforms from the same gene in a single cell is prevalent, and quiescent stem cells, activated stem cells, and neuroblast cells exhibit high heterogeneity of splicing variants. Furthermore, we also demonstrated the existence of novel bicistronic transcripts in quiescent stem cells.

Mouse Oocytes, A Complex Single Cell Transcriptome

Germinal vesicle (GV) stage is a critical transition point from growth to maturation in mammalian oocyte development. During the following meiotic maturation, active RNA degradation and absence of transcription significantly reprofile the oocyte transcriptome to determine oocyte quality. Oocyte RNA-seq has revealed transcriptome differences between two defined phases of GV stage, namely non-surrounded nucleolus (NSN) and surrounded nucleolus (SN) phases. In addition, oocyte RNA-seq has identified a variety of dysregulated genes upon genetic mutation or environmental perturbation. Historically, due to the low amount of RNA per oocyte, a few (20–200) oocytes were needed for a regular library construction in bulk RNA-seq. In recent years, development of single cell sequencing allows detailing the transcriptome of individual oocytes. Here in this study, different RNA-seq datasets from single and bulk of mouse oocytes are compared, and single oocyte RNA-seq (soRNA-seq) shows higher reproducibility. In addition, soRNA-seq better illustrates developmental progression of GV oocytes, revealing more complex gene changes than traditional views. Specially, an elevated level of ribosomal RNA 5′-ETS (5′ external transcribed spacer) has been shown to highly correlate with SN property. This study further demonstrates that UMI (unique molecular identifiers) based and other deduplication methods are limited in their ability to improve the precision of the soRNA-seq datasets. Finally, this study proposes that external spike-in molecules are useful for normalizing samples of different transcriptome sizes. A list of stable genes has been identified during oocyte maturation that are comparable to external spike-in molecules. These findings highlight the advantage of soRNA-seq, and have established ways for better clustering and cross-stage normalization, which can provide more insight into the biological features of oocyte maturation.

Insights Gained and Future Outlook From scRNAseq Studies in Autoimmune Rheumatic Diseases

Autoimmune rheumatic diseases have a major impact on public health as one of the most common morbidities, and many of these disorders involve both local and systemic manifestations with severe consequences for patient health and quality of life. However, treatment options for many of these diseases remain inadequate for a substantial portion of patients, and progress in developing novel therapeutics has been slow. This lack of progress can be largely attributed to an insufficient understanding of the complex mechanisms driving pathogenesis. Recently, the emergence of single-cell RNA sequencing (scRNAseq) has offered a powerful new tool for interrogating rheumatic diseases, with the potential to assess biological heterogeneity and individual cell function in rheumatic diseases. In this review, we discuss the major insights gained from current scRNAseq interrogations of human rheumatic diseases. We highlight novel cell populations and key molecular signatures uncovered, and also raise a number of hypotheses for follow-up study that may be of interest to the field. We also provide an outlook into two emerging single-cell technologies (repertoire sequencing and spatial transcriptomics) that have yet to be utilized in the field of rheumatic diseases, but which offer immense potential in expanding our understanding of immune and stromal cell behavior. We hope that scRNAseq may serve as a wellspring for the generation and interrogation of novel hypotheses regarding autoreactive lymphocytes and tissue infiltration patterns, and help uncover novel avenues for therapeutic development.

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17-31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.

Single-cell RNA sequencing reveals abnormal fluctuations in human eight-cell embryos associated with blastocyst formation failure

Infertility has become a global health issue, with the number of people suffering from the disease increasing year by year, and ART offering great promise for infertility treatment. However, the regulation of early embryonic development is complicated and a series of processes takes place, including the maternal-to-zygotic transition. In addition, developmental arrest is frequently observed during human early embryonic development. In this study, we performed single-cell RNA sequencing on a biopsied blastomere from human eight-cell embryos and tracked the developmental potential of the remaining cells. To compare the sequencing results between different eight-cell embryos, we have combined the research data of this project with the data previously shared in the database and found that cells from the same embryo showed a higher correlation. Additionally, the transcriptome of embryos with blastocyst formation failure was significantly different from developed embryos, and the gene expression as well as cell signaling pathways related to embryonic development were also altered. In particular, the expression of some maternal and zygotic genes in the failed blastocyst formation group was significantly altered: the overall expression level of maternal genes was significantly higher in the failed blastocyst than the developed blastocyst group. In general, these findings provide clues for the causes of human embryonic arrest after the eight-cell stage, and they also provide new ideas for improving the success rate of ART in clinical practice.

Single-Cell Analysis of the Transcriptome and Epigenome

Epigenome regulation has emerged as an important mechanism for the maintenance of organ function in health and disease. Dissecting epigenomic alterations and resultant gene expression changes in single cells provides unprecedented resolution and insight into cellular diversity, modes of gene regulation, transcription factor dynamics and 3D genome organization. In this chapter, we summarize the transformative single-cell epigenomic technologies that have deepened our understanding of the fundamental principles of gene regulation. We provide a historical perspective of these methods, brief procedural outline with emphasis on the computational tools used to meaningfully dissect information. Our overall goal is to aid scientists using these technologies in their favorite system of interest.

Single-Cell Sequencing to Unveil the Mystery of Embryonic Development

Embryonic development is a fundamental physiological process that can provide tremendous insights into stem cell biology and regenerative medicine. In this process, cell fate decision is highly heterogeneous and dynamic, and investigations at the single-cell level can greatly facilitate the understanding of the molecular roadmap of embryonic development. Rapid advances in the technology of single-cell sequencing offer a perfectly useful tool to fulfill this purpose. Despite its great promise, single-cell sequencing is highly interdisciplinary, and successful applications in specific biological contexts require a general understanding of its diversity as well as the advantage versus limitations for each of its variants. Here, the technological principles of single-cell sequencing are consolidated and its applications in the study of embryonic development are summarized. First, the technology basics are presented and the available tools for each step including cell isolation, library construction, sequencing, and data analysis are discussed. Then, the works that employed single-cell sequencing are reviewed to investigate the specific processes of embryonic development, including preimplantation, peri-implantation, gastrulation, and organogenesis. Further, insights are provided on existing challenges and future research directions.

Embryonic LTR retrotransposons supply promoter modules to somatic tissues

Long terminal repeat (LTR) retrotransposons are widely distributed across the human genome. They have accumulated through retroviral integration into germline DNA and are latent genetic modules. Active LTR promoters are observed in germline cells; however, little is known about the mechanisms underlying their active transcription in somatic tissues. Here, by integrating our previous transcriptome data set with publicly available data sets, we show that the LTR families MLT2A1 and MLT2A2 are primarily expressed in human four-cell and eight-cell embryos and are also activated in some adult somatic tissues, particularly pineal gland. Three MLT2A elements function as the promoters and first exons of the protein-coding genes ABCE1, COL5A1, and GALNT13 specifically in the pineal gland of humans but not in that of macaques, suggesting that the exaptation of these LTRs as promoters occurred during recent primate evolution. This analysis provides insight into the possible transition from germline insertion to somatic expression of LTR retrotransposons.

Melatonin improves the maturation and developmental ability of bovine oocytes by up-regulating GJA4 to enhance gap junction intercellular communication

Melatonin (MT) increases oocyte maturation by reducing reactive oxygen species level and enhancing oocyte antioxidant capacity. However, the mechanisms via which MT works are still poorly understood. In the present study, the effects of MT on the maturation rate and development ability of bovine oocytes were investigated. Then, the transcriptome of oocytes treated by MT was sequenced. Finally, the expression of gap junction protein alpha 4 (GJA4) protein and cAMP level were detected in bovine oocytes, and isoprenaline (enhancer of gap junctional intercellular communication (GJIC)) and heptanol (inhibitor of GJIC) were used to investigate the effect of MT on GJIC activity in bovine oocytes. Our results showed that MT significantly improved the maturation, developmental ability and mRNA expression of GJA4 of bovine oocytes. Meanwhile, MT significantly increased GJA4 protein level and cAMP level in bovine oocytes. In contrast to heptanol, both isoproterenol and MT significantly increased GJIC activity, nuclear maturation and the development ability of bovine oocytes. However, MT significantly restored the nuclear maturation and developmental ability of oocytes treated by heptanol. In conclusion, our results showed that MT improves the maturation and developmental ability of bovine oocytes by enhancing GJIC activity via up-regulating GJA4 protein expression in IVM progress.

Consensus-based clustering of single cells by reconstructing cell-to-cell dissimilarity

The development of single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) technology has led to great opportunities for the identification of heterogeneous cell types in complex tissues. Clustering algorithms are of great importance to effectively identify different cell types. In addition, the definition of the distance between each two cells is a critical step for most clustering algorithms. In this study, we found that different distance measures have considerably different effects on clustering algorithms. Moreover, there is no specific distance measure that is applicable to all datasets. In this study, we introduce a new single-cell clustering method called SD-h, which generates an applicable distance measure for different kinds of datasets by optimally synthesizing commonly used distance measures. Then, hierarchical clustering is performed based on the new distance measure for more accurate cell-type clustering. SD-h was tested on nine frequently used scRNA-seq datasets and it showed great superiority over almost all the compared leading single-cell clustering algorithms.

Introduction to Single-Cell DNA Methylation Profiling Methods

DNA methylation is an epigenetic mechanism that is related to mammalian cellular differentiation, gene expression regulation, and disease. In several studies, DNA methylation has been identified as an effective marker to identify differences between cells. In this review, we introduce single-cell DNA-methylation profiling methods, including experimental strategies and approaches to computational data analysis. Furthermore, the blind spots of the basic analysis and recent alternatives are briefly described. In addition, we introduce well-known applications and discuss future development.

Multimodal detection of protein isoforms and nucleic acids from low starting cell numbers

Protein isoforms play a key role in disease progression and arise from mechanisms involving multiple molecular subtypes, including DNA, mRNA and protein. Recently introduced multimodal assays successfully link genomes and transcriptomes to protein expression landscapes. However, the specificity of the protein measurement relies on antibodies alone, leading to major challenges when measuring different isoforms of the same protein. Here we utilize microfluidic design to perform same-cell profiling of DNA, mRNA and protein isoforms (triBlot) on low starting cell numbers (1-100 s of cells). After fractionation lysis, cytoplasmic proteins are resolved by molecular mass during polyacrylamide gel electrophoresis (PAGE), adding a degree of specificity to the protein measurement, while nuclei are excised from the device in sections termed "gel pallets" for subsequent off-chip nucleic acid analysis. By assaying TurboGFP-transduced glioblastoma cells, we observe a strong correlation between protein expression prior to lysis and immunoprobed protein. We measure both mRNA and DNA from retrieved nuclei, and find that mRNA levels correlate with protein abundance in TurboGFP-expressing cells. Furthermore, we detect the presence of TurboGFP isoforms differing by an estimated <1 kDa in molecular mass, demonstrating the ability to discern different proteoforms with the same antibody probe. By directly relating nucleic acid modifications to protein isoform expression in 1-100 s of cells, the triBlot assay holds potential as a screening tool for novel biomarkers in diseases driven by protein isoform expression.

Expression of immunoglobulin G in human proximal tubular epithelial cells

Proximal tubular epithelial cells (PTECs) have innate immune characteristics, and produce proinflammatory factors, chemokines and complement components that drive epithelial‑mesenchymal transition (EMT). Our previous studies revealed that human mesangial cells and podocytes were able to synthesize and secrete immunoglobulin (Ig)A and IgG, respectively. The aim of the present study was to evaluate the expression of Igs in PTECs. Firstly, IgG was detected in the cytoplasm, the cell membrane and the lumen of PTECs in the normal renal cortex by immunohistochemistry. Secondly, Igγ gene transcription and V(D)J recombination were detected in single PTECs by nested PCR and Sanger sequencing. Thirdly, Igγ, Igκ and Igλ were clearly detected in an immortalized PTEC line (HK‑2) by immunostaining and western blotting, in which RP215 (an antibody that predominantly binds to non‑B cell‑derived IgG) was used. In addition, Igγ, Igκ and Igλ gene transcripts, conservative V(D)J recombination in the Igγ variable region, recombination activating gene 1/2 and activation‑induced cytidine deaminase were all detected in HK‑2 cells. These data suggested that PTECs may express IgG in a similar manner to B cells. Furthermore, IgG expression was upregulated by TGF‑β1 and may be involved in EMT.

A novel homozygous mutation of phospholipase C zeta leading to defective human oocyte activation and fertilization failure

STUDY QUESTION

Is a novel homozygous phospholipase C zeta (PLCζ), c.1658 G>C; p. R553P mutation in the C2 domain associated with the outcomes of recurrent fertilization failure after ICSI?

SUMMARY ANSWER

PLCζ, c.1658 G>C led to defective human oocyte activation and fertilization failure, while this mutation in the C2 domain of PLCζ did not compromise concentration, motility and chromosome ploidy of sperm.

WHAT IS KNOWN ALREADY

Sperm-specific PLCζ is now widely considered to be the physiological stimulus that evokes intracellular calcium (Ca2+) oscillations, which are essential for egg activation during mammalian fertilization. Thus far, few genetic studies have shown that different point mutations in the PLCζ gene are associated with male infertility.

STUDY DESIGN, SIZE, DURATION

This was a basic medical research to assess pathogenicity for novel mutation in the C2 domain of PLCζ during human fertilization.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Single-cell omics were applied to analyze the DNA methylation state of the fertilization failure oocytes and the ploidy of the patient's sperm. Whole genome sequencing data for the patient were analyzed for mutations in PLCζ. Sanger sequencing confirmed the presence of a rare variant, and then the mutant and wild-type PLCζ mRNA were injected to observe oocyte activation.

MAIN RESULTS AND THE ROLE OF CHANCE

The fertilization failure oocytes (n = 4) were triploid and lacking proper DNA demethylation. The whole genome sequencing analysis revealed a novel missense homozygous mutation in PLCζ, c.1658 G>C; p. R553P, which leads to the conversion of arginine 553 to proline. This point mutation does not affect the production of the corresponding protein in sperm. However, microinjection of the mRNA transcribed from the PLCζ R553P mutation gene failed to trigger oocyte activation and the subsequent embryo development.

LIMITATIONS, REASONS FOR CAUTION

Only one patient with PLCζ mutations was available because of its rare incidence.

WIDER IMPLICATIONS OF THE FINDINGS

Notably, we discovered a novel homozygous mutation in PLCζ, which results in an abnormal conformation at the C2 domain of the PLCζ protein. Our findings indicate an essential role of PLCζ in human fertilization and the requirement of a normal structure of C2 domain in PLCζ-mediated physiological function.

STUDY FUNDING/COMPETING INTEREST(S)

This project is funded by the National Natural Science Foundation of China (31571544, 31871482, 31871447) and National Key Research and Development Program (2018YFC1004000, 2017YFA0103801). All authors declared no competing interests.

TRIAL REGISTRATION NUMBER

Not applicable.

Advanced single-cell technologies to guide the development of bioengineered lungs

Lung transplantation remains the only viable option for individuals suffering from end-stage lung failure. However, a number of current limitations exist including a continuing shortage of suitable donor lungs and immune rejection following transplantation. To address these concerns, engineering a decellularized biocompatible lung scaffold from cadavers reseeded with autologous lung cells to promote tissue regeneration is being explored. Proof-of-concept transplantation of these bioengineered lungs into animal models has been accomplished. However, these lungs were incompletely recellularized with resulting epithelial and endothelial leakage and insufficient basement membrane integrity. Failure to repopulate lung scaffolds with all of the distinct cell populations necessary for proper function remains a significant hurdle for the progression of current engineering approaches and precludes clinical translation. Advancements in 3D bioprinting, lung organoid models, and microfluidic device and bioreactor development have enhanced our knowledge of pulmonary lung development, as well as important cell-cell and cell-matrix interactions, all of which will help in the path to a bioengineered transplantable lung. However, a significant gap in knowledge of the spatiotemporal interactions between cell populations as well as relative quantities and localization within each compartment of the lung necessary for its proper growth and function remains. This review will provide an update on cells currently used for reseeding decellularized scaffolds with outcomes of recent lung engineering attempts. Focus will then be on how data obtained from advanced single-cell analyses, coupled with multiomics approaches and high-resolution 3D imaging, can guide current lung bioengineering efforts for the development of fully functional, transplantable lungs.

Single-Cell Sequencing Confirms Transcripts and VHDJH Rearrangements of Immunoglobulin Genes in Human Podocytes

Most glomerular diseases are associated with inflammation caused by deposited pathogenic immunoglobulins (Igs), which are believed to be produced by B cells. However, our previous study indicated that the human podocyte cell line can produce IgG. In this study, we aimed to confirm the transcripts and characterize the repertoires of Igs in primary podocytes at single cell level. First, single-cell RNA sequencing of cell suspensions from “normal” kidney cortexes by a 10xGenomics Chromium system detected Ig transcripts in 7/360 podocytes and Ig gene segments in 106/360 podocytes. Then, we combined nested PCR with Sanger sequencing to detect the transcripts and characterize the repertoires of Igs in 48 single podocytes and found that five classes of Ig heavy chains were amplified in podocytes. Four-hundred and twenty-nine V_HDJ_H rearrangement sequences were analyzed; podocyte-derived Igs exhibited classic V_HDJ_H rearrangements with nucleotide additions and somatic hypermutations, biased VH1 usage and restricted diversity. Moreover, compared with the podocytes from healthy control that usually expressed one class of Ig and one V_HDJ_H pattern, podocytes from patients expressed more classes of Ig, V_HDJ_H patterns and somatic hypermutations. These findings suggested that podocytes can express Igs in normal condition and increase diversity in pathological situations.

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.