Exploring single-cell RNA sequencing as a decision-making tool in the clinical management of Fuchs' endothelial corneal dystrophy.

Single-cell RNA sequencing (scRNA-seq) has enabled the identification of novel gene signatures and cell heterogeneity in numerous tissues and diseases. Here we review the use of this technology for Fuchs' Endothelial Corneal Dystrophy (FECD). FECD is the most common indication for corneal endothelial transplantation worldwide. FECD is challenging to manage because it is genetically heterogenous, can be autosomal dominant or sporadic, and progress at different rates. Single-cell RNA sequencing has enabled the discovery of several FECD subtypes, each with associated gene signatures, and cell heterogeneity. Current FECD treatments are mainly surgical, with various Rho kinase (ROCK) inhibitors used to promote endothelial cell metabolism and proliferation following surgery. A range of emerging therapies for FECD including cell therapies, gene therapies, tissue engineered scaffolds, and pharmaceuticals are in preclinical and clinical trials. Unlike conventional disease management methods based on clinical presentations and family history, targeting FECD using scRNA-seq based precision-medicine has the potential to pinpoint the disease subtypes, mechanisms, stages, severities, and help clinicians in making the best decision for surgeries and the applications of therapeutics. In this review, we first discuss the feasibility and potential of using scRNA-seq in clinical diagnostics for FECD, highlight advances from the latest clinical treatments and emerging therapies for FECD, integrate scRNA-seq results and clinical notes from our FECD patients and discuss the potential of applying alternative therapies to manage these cases clinically.

Single-cell sequencing reveals the correlation of aggrephagy signaling and multiple myeloma immune microenvironment composition.

Aggrephagy, a type of autophagy, degrades the aggregation of misfolded protein in cells. However, the role of aggrephagy in multiple myeloma (MM) has not been fully demonstrated. In this study, we first investigated the correlation between aggrephagy signaling, MM immune microenvironment composition and disease prognosis. Single-cell RNA-seq data, including the expression profiles of 12,187 single cells from seven MM bone marrow (BM) and seven healthy BM samples, were analyzed by non-negative matrix factorization for 44 aggrephagy-related genes. Bulk RNA-seq cohorts from the Gene Expression Omnibus database were used to evaluate the prognostic value of aggrephagy-related immune cell subtypes and predict immune checkpoint blockade immunotherapeutic response in MM. Compared with healthy BM, MM BM exhibited different patterns of aggrephagy-related gene expression. In MM BM, macrophages, CD8+ T cells, B cells and natural killer cells could be grouped into four to nine aggrephagy-related subclusters. The signature of aggrephagy signaling molecule expression in the immune cells correlates with the patient's prognosis. Our investigation provides a novel view of aggrephagy signaling in MM tumor microenvironment cells, which might be a prognostic indicator and potential target for MM treatment.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing.

Background: In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy. Methods: Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis. Results: ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype. Conclusions: This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Activation of non-classical Wnt signaling pathway effectively enhances HLA-A presentation in acute myeloid leukemia.

Objective: The escape from T cell-mediated immune surveillance is an important cause of death for patients with acute myeloid leukemia (AML). This study aims to identify clonal heterogeneity in leukemia progenitor cells and explore molecular or signaling pathways associated with AML immune escape. Methods: Single-cell RNA sequencing (scRNA-seq) was performed to identified AML-related cellular subsets, and intercellular communication was analyzed to investigate molecular mechanisms associated with AML immune escape. Bulk RNA sequencing (RNA-seq) was performed to screen differentially expressed genes (DEGs) related to hematopoietic stem cell progenitors (HSC-Prog) in AML, and critical ore signaling pathways and hub genes were found by Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The mRNA level of the hub gene was verified using quantitative real-time PCR (qRT-PCR) and the protein level of human leukocyte antigen A (HLA-A) using enzyme-linked immuno sorbent assay (ELISA). Results: scRNA-seq analysis revealed a large heterogeneity of HSC-Prog across samples, and the intercellular communication analysis indicated a strong association between HSC-Prog and CD8+-T cells, and HSC-Prog also had an association with HLA-A. Transcriptome analysis identified 1748 DEGs, enrichment analysis results showed that non-classical wnt signaling pathway was associated with AML, and 4 pathway-related genes (RHOA, RYK, CSNK1D, NLK) were obtained. After qRT-PCR and ELISA validation, hub genes and HLA-A were found to be down-regulated in AML and up-regulated after activation of the non-classical Wnt signaling pathway. Conclusion: In this study, clonal heterogeneity of HSC-Prog cells in AML was identified, non-classical wnt signaling pathways associated with AML were identified, and it was verified that HLA-A could be upregulated by activation of non-classical wnt signaling, thereby increasing antigen presentation.

Primary nasal influenza infection rewires tissue-scale memory response dynamics.

The nasal mucosa is often the initial site of respiratory viral infection, replication, and transmission. Understanding how infection shapes tissue-scale primary and memory responses is critical for designing mucosal therapeutics and vaccines. We generated a single-cell RNA-sequencing atlas of the murine nasal mucosa, sampling three regions during primary influenza infection and rechallenge. Compositional analysis revealed restricted infection to the respiratory mucosa with stepwise changes in immune and epithelial cell subsets and states. We identified and characterized a rare subset of Krt13+ nasal immune-interacting floor epithelial (KNIIFE) cells, which concurrently increased with tissue-resident memory T (TRM)-like cells. Proportionality analysis, cell-cell communication inference, and microscopy underscored the CXCL16-CXCR6 axis between KNIIFE and TRM cells. Secondary influenza challenge induced accelerated and coordinated myeloid and lymphoid responses without epithelial proliferation. Together, this atlas serves as a reference for viral infection in the upper respiratory tract and highlights the efficacy of local coordinated memory responses.

Establishment of a conditionally reprogrammed primary eccrine sweat gland culture for evaluation of tissue-specific CFTR function.

BACKGROUND: Sweat chloride concentration is used both for CF diagnosis and for tracking CFTR modulator efficacy over time, but the relationship between sweat chloride and lung health is heterogeneous and informed by CFTR genotype. Here, we endeavored to characterize ion transport in eccrine sweat glands (ESGs). METHODS: First, ESGs were microdissected from a non-CF skin donor to analyze individual glands. We established primary cultures of ESG cells via conditional reprogramming for functional testing of ion transport by short circuit current measurement and examined cell composition by single-cell RNA-sequencing (scRNA-seq) comparing with whole dissociated ESGs. Secondly, we cultured nasal epithelial (NE) cells and ESGs from two people with CF (pwCF) to assess modulator efficacy. Finally, NEs and ESGs were grown from one person with the CFTR genotype F312del/F508del to explore genotype-phenotype heterogeneity. RESULTS: ESG primary cells from individuals without CF demonstrated robust ENaC and CFTR function. scRNA-seq demonstrated both secretory and ductal ESG markers in cultured ESG cells. In both NEs and ESGs from pwCF homozygous for F508del, minimal baseline CFTR function was observed, and treatment with CFTR modulators significantly enhanced function. Notably, NEs from an individual bearing F312del/F508del exhibited significant baseline CFTR function, whereas ESGs from the same person displayed minimal CFTR function, consistent with observed phenotype. CONCLUSIONS: This study has established a novel primary culture technique for ESGs that allows for functional ion transport measurement to assess modulator efficacy and evaluate genotype-phenoytpe heterogeneity. To our knowledge, this is the first reported application of conditional reprogramming and scRNA-seq of microdissected ESGs.

Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling.

Annotation of the cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.e. regulatory elements) and gene expression in malignant cells versus normal mammary epithelial cells. These data unveil regulatory elements with that switch from silencers of gene expression in normal cells to enhancers of gene expression in cancer cells, leading to the upregulation of clinically relevant oncogenes. To translate the utility of this dataset into tractable models, we generated matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing, for each subtype, a conserved oncogenic gene expression program between in vitro and in vivo cells. Together, this work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of BC cells at single-cell resolution.

Organoids for Cancer Research: Advances and Challenges.

As 3D culture technology advances, new avenues have opened for the development of physiological human cancer models. These preclinical models provide efficient ways to translate basic cancer research into clinical tumor therapies. Recently, cancer organoids have emerged as a model to dissect the more complex tumor microenvironment. Incorporating cancer organoids into preclinical programs have the potential to increase the success rate of oncology drug development and recapitulate the most efficacious treatment regimens for cancer patients. In this review, four main types of cancer organoids are introduced, their applications, advantages, limitations, and prospects are discussed, as well as the recent application of single-cell RNA-sequencing (scRNA-seq) in exploring cancer organoids to advance this field.

scGAAC: A graph attention autoencoder for clustering single-cell RNA-sequencing data.

Single-cell RNA-sequencing (scRNA-seq) enables the investigation of intricate mechanisms governing cell heterogeneity and diversity. Clustering analysis remains a pivotal tool in scRNA-seq for discerning cell types. However, persistent challenges arise from noise, high dimensionality, and dropout in single-cell data. Despite the proliferation of scRNA-seq clustering methods, these often focus on extracting representations from individual cell expression data, neglecting potential intercellular relationships. To overcome this limitation, we introduce scGAAC, a novel clustering method based on an attention-based graph convolutional autoencoder. By leveraging structural information between cells through a graph attention autoencoder, scGAAC uncovers latent relationships while extracting representation information from single-cell gene expression patterns. An attention fusion module amalgamates the learned features of the graph attention autoencoder and the autoencoder through attention weights. Ultimately, a self-supervised learning policy guides model optimization. scGAAC, a hypothesis-free framework, performs better on four real scRNA-seq datasets than most state-of-the-art methods. The scGAAC implementation is publicly available on Github at: https://github.com/labiip/scGAAC.

The SWI/SNF chromatin remodelling complex regulates pancreatic endocrine cell expansion and differentiation in mice in vivo.

AIMS/HYPOTHESIS: Strategies to augment functional beta cell mass include directed differentiation of stem cells towards a beta cell fate, which requires extensive knowledge of transcriptional programs governing endocrine progenitor cell differentiation in vivo. We aimed to study the contributions of the Brahma-related gene-1 (BRG1) and Brahma (BRM) ATPase subunits of the SWI/SNF chromatin remodelling complex to endocrine cell development. METHODS: We generated mice with endocrine progenitor-specific Neurog3-Cre BRG1 removal in the presence of heterozygous (Brg1Δendo;Brm+/-) or homozygous (double knockout: DKOΔendo) BRM deficiency. Whole-body metabolic phenotyping, islet function characterisation, islet quantitative PCR and histological characterisation were performed on animals and tissues postnatally. To test the mechanistic actions of SWI/SNF in controlling gene expression during endocrine cell development, single-cell RNA-seq was performed on flow-sorted endocrine-committed cells from embryonic day 15.5 control and mutant embryos. RESULTS: Brg1Δendo;Brm+/- mice exhibit severe glucose intolerance, hyperglycaemia and hypoinsulinaemia, resulting, in part, from reduced islet number; diminished alpha, beta and delta cell mass; compromised islet insulin secretion; and altered islet gene expression programs, including reductions in MAFA and urocortin 3 (UCN3). DKOΔendo mice were not recovered at weaning; however, postnatal day 6 DKOΔendo mice were severely hyperglycaemic with reduced serum insulin levels and beta cell area. Single-cell RNA-seq of embryonic day 15.5 lineage-labelled cells revealed endocrine progenitor, alpha and beta cell populations from SWI/SNF mutants have reduced expression of Mafa, Gcg, Ins1 and Ins2, suggesting limited differentiation capacity. Reduced Neurog3 transcripts were discovered in DKOΔendo endocrine progenitor clusters, and the proliferative capacity of neurogenin 3 (NEUROG3)+ cells was reduced in Brg1Δendo;Brm+/- and DKOΔendo mutants. CONCLUSIONS/INTERPRETATION: Loss of BRG1 from developing endocrine progenitor cells has a severe postnatal impact on glucose homeostasis, and loss of both subunits impedes animal survival, with both groups exhibiting alterations in hormone transcripts embryonically. Taken together, these data highlight the critical role SWI/SNF plays in governing gene expression programs essential for endocrine cell development and expansion. DATA AVAILABILITY: Raw and processed data for scRNA-seq have been deposited into the NCBI Gene Expression Omnibus (GEO) database under the accession number GSE248369.

Interleukin-7-based identification of liver lymphatic endothelial cells reveals their unique structural features.

Background & Aims: The lymphatic system plays crucial roles in maintaining fluid balance and immune regulation. Studying the liver lymphatics has been considered challenging, as common lymphatic endothelial cell (LyEC) markers are expressed by other liver cells. Additionally, isolation of sufficient numbers of LyECs has been challenging because of their extremely low abundance (<0.01% of entire liver cell population) in a normal liver. Methods: Potential LyEC markers was identified using our published single-cell RNA sequencing (scRNA-seq) dataset (GSE147581) in mouse livers. Interleukin-7 (IL7) promoter-driven green fluorescent protein knock-in heterozygous mice were used for the validation of IL7 expression in LyECs in the liver, for the development of liver LyEC isolation protocol, and generating liver ischemia/reperfusion (I/R) injury. Scanning electron microscopy was used for the structural analysis of LyECs. Changes in LyEC phenotypes in livers of mice with I/R were determined by RNA-seq analysis. Results: Through scRNA-seq analysis, we have identified IL7 as an exclusive marker for liver LyECs, with no overlap with other liver cell types. Based on IL7 expression in liver LyECs, we have established an LyEC isolation method and observed distinct cell surface structures of LyECs with fenestrae and cellular pores (ranging from 100 to 400 nm in diameter). Furthermore, we identified LyEC genes that undergo alterations during I/R liver injuries. Conclusions: This study not only identified IL7 as an exclusively expressed gene in liver LyECs, but also enhanced our understanding of LyEC structures and demonstrated transcriptomic changes in injured livers. Impact and implications: Understanding the lymphatic system in the liver is challenging because of the absence of specific markers for liver LyEC. This study has identified IL7 as a reliable marker for LyECs, enabling the development of an effective method for their isolation, elucidating their unique cell surface structure, and identifying LyEC genes that undergo changes during liver damage. The development of IL7 antibodies for detecting it in human liver specimens will further advance our understanding of the liver lymphatic system in the future.

CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data.

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations, especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservations. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations, and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks, and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice, zebrafish, and chick, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify conserved cell types even in evolutionarily distant species. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature for identifying conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations, and intercellular interactions, providing insights into the cellular and molecular mechanisms of species evolution.

Single-cell analysis defines LGALS1 + fibroblasts that promote proliferation and migration of intrahepatic cholangiocarcinoma.

The incidence rate of intrahepatic cholangiocarcinoma (ICC), which has a poor prognosis, is rapidly increasing. To investigate the intratumor heterogeneity of ICC, we analyzed single-cell RNA sequencing data from the primary tumor and adjacent normal tissues of 14 treatment-naïve patients. We identified ten major cell types, along with 45 subclusters of cells. Notably, we identified a fibroblast cluster, Fibroblast_LUM+, which was preferably enriched in tumor tissues and actively interacted with cholangiocytes. LGALS1 was verified as a marker gene of Fibroblast_LUM+, contributing to the malignant phenotype of ICC. The higher amount of LGALS1 + fibroblasts were associated with poorer overall survival in ICC patients. LGALS1 + fibroblasts activated the proliferation and migration of tumor cells by upregulating the expression levels of CCR2, ADAM15, and ß-integrin. Silencing LGALS1 in cancer-associated fibroblasts (CAFs) suppressed CAF-augmented tumor cell migration and invasion in vitro as well as tumor formation in vivo, suggesting that blockade of LGALS1 serves as a potential therapeutic approach for ICC. Taken together, our single-cell analysis provides insight into the interaction between malignant cells and specific subtypes of fibroblasts. Our work will further the understanding of the intratumor heterogeneity of ICC and provide novel strategies for the treatment of ICC by targeting fibroblasts in the tumor microenvironment.

Phylogeny and species delimitation of ciliates in the genus Spirostomum (Class, Heterotrichea) using single-cell transcriptomes.

Ciliates are single-celled microbial eukaryotes that diverged from other eukaryotic lineages over a billion years ago. The extensive evolutionary timespan of ciliate has led to enormous genetic and phenotypic changes, contributing significantly to their high level of diversity. Recent analyses based on molecular data have revealed numerous cases of cryptic species complexes in different ciliate lineages, demonstrating the need for a robust approach to delimit species boundaries and elucidate phylogenetic relationships. Heterotrich ciliate species of the genus Spirostomum are abundant in freshwater and brackish environments and are commonly used as biological indicators for assessing water quality. However, some Spirostomum species are difficult to identify due to a lack of distinguishable morphological characteristics, and the existence of cryptic species in this genus remains largely unexplored. Previous phylogenetic studies have focused on only a few loci, namely the ribosomal RNA genes, alpha-tubulin, and mitochondrial CO1. In this study, we obtained single-cell transcriptome of 25 Spirostomum species populations (representing six morphospecies) sampled from South Korea and the USA, and used concatenation- and coalescent-based methods for species tree inference and delimitation. Phylogenomic analysis of 37 Spirostomum populations and 265 protein-coding genes provided a robustious insight into the evolutionary relationships among Spirostomum species and confirmed that species with moniliform and compact macronucleus each form a distinct monophyletic lineage. Furthermore, the multispecies coalescent (MSC) model suggests that there are at least nine cryptic species in the Spirostomum genus, three in S. minus, two in S. ambiguum, S. subtilis, and S. teres each. Overall, our fine sampling of closely related Spirostomum populations and wide scRNA-seq allowed us to demonstrate the hidden crypticity of species within the genus Spirostomum, and to resolve and provide much stronger support than hitherto to the phylogeny of this important ciliate genus.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes.

Background: Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights. Methods: Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels. Results: Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-ß), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased. Conclusion: Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

CAraCAl: CAMML with the integration of chromatin accessibility.

BACKGROUND: A vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically "open" for expression. RESULTS: To leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity. CONCLUSIONS: We found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.

Single-cell RNA sequencing of human oocytes reveals a differential transcriptomic profile associated with agar-like zona pellucida.

BACKGROUND: Agar-like zona pellucida (ZP) is the most common type of abnormal ZP, and is one of the causes of low fertility or infertility. However, the molecular mechanism of agar-like ZP is unclear. Single-cell RNA-sequencing (scRNA-seq) analysis was used to assess the cellular and molecular landscape of oocytes with agar-like ZP. METHODS: Human metaphase I (MI) oocytes were collected from four patients with agar-like ZP and four healthy donors. Total RNA was isolated, cDNA was synthesized, and libraries were generated and subsequently sequenced on a HiSeq 2500 instrument. The scRNA-seq data were analyzed with R software. RESULTS: We identified 1320 genes that were differentially expressed between agar-like ZP oocytes and healthy donor oocytes. Gene Ontology term enrichment results showed that the genes downregulated in agar-like ZP oocytes were significantly related to extracellular matrix organization, while the genes upregulated in agar-like ZP oocytes were significantly related to the regulation of response to DNA damage stimulus. The Kyoto Encyclopedia of Genes and Genomes enrichment results showed that genes were enriched in the ECM-receptor interaction pathway and focal adhesion pathway. Other signaling pathways important in oocyte development were also enriched, such as PI3K-Akt. Differential expression analysis identified UBC, TLR4, RELA, ANXA5, CAV1, KPNA2, CCNA2, ACTA2, FYN and ITGB3 as genetic markers of oocytes with agar-like ZP. CONCLUSIONS: Our findings suggest that agar-like ZP oocytes exhibit significant downregulation of genes involved in the ECM-receptor interaction signaling pathway and focal adhesion pathway, which could lead to aberrant ZP formation, while the upregulated genes were significantly related to regulation of the response to DNA damage stimulus. Agar-like ZP formation may interfere with the normal exchange of signals between oocytes and perivitelline granulosa cells, thereby preventing cumulus cells from participating in oocyte DNA damage repair and causing MI arrest.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research.

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

ScnML models single-cell transcriptome to predict spinal cord neuronal cell status.

Injuries to the spinal cord nervous system often result in permanent loss of sensory, motor, and autonomic functions. Accurately identifying the cellular state of spinal cord nerves is extremely important and could facilitate the development of new therapeutic and rehabilitative strategies. Existing experimental techniques for identifying the development of spinal cord nerves are both labor-intensive and costly. In this study, we developed a machine learning predictor, ScnML, for predicting subpopulations of spinal cord nerve cells as well as identifying marker genes. The prediction performance of ScnML was evaluated on the training dataset with an accuracy of 94.33%. Based on XGBoost, ScnML on the test dataset achieved 94.08% 94.24%, 94.26%, and 94.24% accuracies with precision, recall, and F1-measure scores, respectively. Importantly, ScnML identified new significant genes through model interpretation and biological landscape analysis. ScnML can be a powerful tool for predicting the status of spinal cord neuronal cells, revealing potential specific biomarkers quickly and efficiently, and providing crucial insights for precision medicine and rehabilitation recovery.

Circadian Rhythm Disruption in Hepatocellular Carcinoma Investigated by Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data.

Circadian rhythms are essential regulators of a multitude of physiological and behavioral processes, such as the metabolism and function of the liver. Circadian rhythms are crucial to liver homeostasis, as the liver is a key metabolic organ accountable for the systemic equilibrium of the body. Circadian rhythm disruption alone is sufficient to cause liver cancer through the maintenance of hepatic metabolic disorder. Although there is evidence linking CRD to hepatocarcinogenesis, the precise cellular and molecular mechanisms that underlie the circadian crosstalk that leads to hepatocellular carcinoma remain unknown. The expression of CRD-related genes in HCC was investigated in this study via bulk RNA transcriptomic analysis and single-cell sequencing. Dysregulated CRD-related genes are predominantly found in hepatocytes and fibroblasts, according to the findings. By using a combination of single-cell RNA sequencing and bulk RNA sequencing analyses, the dysregulated CRD-related genes ADAMTS13, BIRC5, IGFBP3, MARCO, MT2A, NNMT, and PGLYRP2 were identified. The survival analysis using the Kaplan-Meier method revealed a significant correlation between the expression levels of BIRC5 and IGFBP3 and the survival of patients diagnosed with HCC.