Complex Analysis of Single-Cell RNA Sequencing Data

Barcodes based on nucleic acid sequences: Applications and challenges (Review)

Cells are the fundamental structural and functional units of living organisms and the study of these entities has remained a central focus throughout the history of biological sciences. Traditional cell research techniques, including fluorescent protein tagging and microscopy, have provided preliminary insights into the lineage history and clonal relationships between progenitor and descendant cells. However, these techniques exhibit inherent limitations in tracking the full developmental trajectory of cells and elucidating their heterogeneity, including sensitivity, stability and barcode drift. In developmental biology, nucleic acid barcode technology has introduced an innovative approach to cell lineage tracing. By assigning unique barcodes to individual cells, researchers can accurately identify and trace the origin and differentiation pathways of cells at various developmental stages, thereby illuminating the dynamic processes underlying tissue development and organogenesis. In cancer research, nucleic acid barcoding has played a pivotal role in analyzing the clonal architecture of tumor cells, exploring their heterogeneity and resistance mechanisms and enhancing our understanding of cancer evolution and inter‑clonal interactions. Furthermore, nucleic acid barcodes play a crucial role in stem cell research, enabling the tracking of stem cells from diverse origins and their derived progeny. This has offered novel perspectives on the mechanisms of stem cell self‑renewal and differentiation. The present review presented a comprehensive examination of the principles, applications and challenges associated with nucleic acid barcode technology.

A systematic review of single-cell RNA sequencing applications and innovations

Bulk RNA sequencing is one type of RNA sequencing technique, as well as targeted RNA sequencing and whole transcriptome sequencing. It provides valuable insights into gene expression in specific cell populations or regions. However, these methods often miss the diversity of cells within complex tissues. This restriction is overcome by single-cell RNA sequencing, which records gene expression at the single-cell level. It offers a detailed picture of the diversity of cells. It is essential to study glucose homeostasis. It offers thorough explanations of cellular variation. Networks and Governance Dynamics The use of scRNA-seq in islet cells is reviewed in this study, along with sample preparation, sequencing, and computational analysis. It highlights advances in understanding cell types. Gene activity and cell interactions. Along with the challenges and limitations of scRNA-seq, this review highlights the importance of scRNA-seq in understanding complex biological processes and diseases. It is an essential resource for future research and method development in this field, which will help to build personalized treatment.

Therapeutic implications of endoplasmic reticulum stress gene CCL3 in cervical squamous cell carcinoma

This study investigated ERS-related gene expressions in CESC, identifying two molecular subtypes, P1 and P2, and constructing a precise prognostic model based on these subtypes. TCGA's whole-genome expression profiles were used to recognize these subtypes through the ConsensusClusterPlus method, further refining prognostic models with univariate and Lasso Cox regression analyses validated by the GSE39001 dataset. The study analyzed the expression distribution of ERS marker genes within T cell subgroups using scRNA-seq data (GSE168652), highlighting T cell diversity. The critical role of the CCL3 gene in prognostic models was examined explicitly in CD8 + T cells from healthy individuals and CESC patients. Elevated CCL3 levels were observed in patients' CD8 + T cells compared to healthy controls. Functional experiments involving CCL3 knockdown and overexpression in HeLa and SiHa CESC cell lines were conducted to investigate its impact on cell proliferation, migration, and invasion. These findings were subsequently validated in a nude mouse model. The results demonstrated that suppressing CCL3 inhibited cell proliferation, migration, and invasion significantly, while its overexpression promoted these processes. In the mouse model, CCL3 silencing reduced tumor growth and decreased Ki-67 labeling within the tumor tissues, indicating the therapeutic potential of targeting CCL3 in CESC treatment, possibly through CD8 + T cell regulation. This study contributes new prognostic assessment tools and personalized treatment options for CESC patients, paving the way for more targeted therapies in CESC by discovering the CCL3 gene, presenting significant clinical implications.

Gene expression regulation and polyadenylation in ulcerative colitis via long-chain RNA sequencing

BACKGROUND

Ulcerative colitis (UC) is an immune-mediated chronic intestinal disease, with a pathogenesis that remains incompletely understood. The purpose of this study is to analyze the difference of gene expression between UC patients and healthy controls using Oxford Nanopore Technology's long-read RNA sequencing (ONT-RNA-seq) and to explore how alternative polyadenylation (APA) site selection contributes to UC pathogenesis.

METHODS

Colon tissue samples from UC and normal controls (NC) were collected, and total RNA was extracted and sequenced using ONT-RNA-seq technology. Various bioinformatics analyses were performed, including differential expression gene (DEG) analysis, functional enrichment analysis, APA site analysis, and prediction miRNAs and RNA binding proteins (RBPs) targets, to explore the molecular mechanism underlying UC.

RESULTS

ONT-RNA-seq analysis revealed that the expression levels of ACSF2, NPY, SLC26A3, BRINP3, and PKLPP2 were significantly lower in UC patients compared to the NC group, while the expression levels of CCL20, CCL21, CD55, IDO1, LCN2, NOS2, CCL11, OLFM4, ANXA1, REG1A, S100A9, SLPI, SPINK1, and AGR2 were significantly higher. Functional enrichment analysis showed that DEGs were closely related to immune and inflammatory responses, which in turn are related to many challenges in the diagnosis and treatment of UC. Mechanistically, APA site selection was found to contribute to the regulation of gene expression in UC, and some APA genes were identified as potential regulators of miRNAs and RBPs. Vene diagram revealed significant overlap between miRNA- and RBP-targeted genes and DEGs, suggesting that APA genes may modulate genes expression in UC through miRNA and RBP targeting. Additionally, five key APA genes--CD38, NCALD, SMIM31, GPX7, and SWAP70--were identified as potentially playing crucial role in UC pathogenesis.

CONCLUSIONS

This study provides new insights into the molecular mechanisms of UC through ONT-RNA-seq technology, especially in gene expression regulation and APA site selection.

Applications and emerging challenges of single-cell RNA sequencing technology in tumor drug discovery

Current therapeutic drugs are inadequate for curing tumors, highlighting the need for novel tumor drugs. The advancement of single-cell RNA sequencing (scRNA-seq) technology offers new opportunities for tumor drug discovery. This technology allows us to explore tumor heterogeneity and developmental mechanisms at the single-cell level. In this review, we outline the application of scRNA-seq in tumor drug discovery stages, including elucidating tumor mechanisms, identifying targets, screening drugs, and understanding drug action and resistance. We also discuss the challenges and future prospects of using scRNA-seq in drug development, providing a scientific foundation for advancing tumor therapies.

Single-Cell Transcriptome Decoding Umbilical Cord-Derived Mesenchymal Stem Cell Heterogeneity Reveals a Unique IL1R1HighPDGFRAHigh Ultroser-G-MSC With Osteogenesis and Chondrogenesis Signatures

The heterogeneity of human umbilical cord mesenchymal stem cells (hUC-MSCs) is culturing-dependent, resulting in functional non-uniformness. To achieve the best clinical benefit, a comprehensive understanding of the origin of the heterogeneity in different culture systems can identify functional subgroups to direct the precise application of hUC-MSCs. Here, we create a single-cell transcriptome atlas of hUC-MSC in different culture systems for the identification of a subgroup of Ultroser-G-MSCs with high osteogenic and chondrogenic potentials featured by high expressions of IL1R1 and PDGFRA. Further experimental validations surprisingly reveal that IL1R1highPDGFRAhigh Ultroser-G-MSCs possess advantages over "traditional" hUC-MSCs in the treatments of modeled osteoarthritis, leading to a cell-cell communication network centered in Clusters 0 and 2. Moreover, we found that Wnt5 signaling is the key pathway for the dynamic transformation of osteogenic and chondrogenic phenotypes in hUC-MSC. Overall, the present study paves the way for the clarification of heterogenetic nature of hUC-MSC in different culture systems for the selection of optimal MSC types to achieve the precision on clinical treatments.

CXCL14 in prostate cancer: complex interactions in the tumor microenvironment and future prospects

CXCL14 is a highly conserved chemokine expressed in various cell types, playing crucial roles in both physiological and pathological processes, including immune regulation and tumorigenesis. Recently, the role of CXCL14 in tumors has attracted considerable attention. However, previous pan-cancer studies have reported inconsistencies regarding the effects of CXCL14 on tumors, particularly concerning its expression levels in tumor tissues and its influence on various phenotypes of cancer cells. This variability is believed to stem from the context-dependent nature of CXCL14, as different sources of CXCL14 and its secretion within distinct tumor microenvironments may mediate diverse biological effects. Such phenomena have also been observed in prostate cancer research. Despite a foundational understanding of CXCL14 in prostate cancer, there remains a lack of comprehensive reviews summarizing the specific roles of this chemokine and systematically analyzing the reasons behind its complex effects. Therefore, this article aims to discuss the role of CXCL14 in the tumor microenvironment of prostate cancer and explore future research directions and potential applications.

Soft tissue sarcomas at the single-cell and spatial resolution: new markers and targets

Soft tissue sarcomas (STS) are heterogeneous and aggressive tumors, originating in connective tissues embryologically derived from the mesenchyme. Due to their rarity, crucial information about their biology is still lacking. In recent years, single-cell and spatial analyses have opened up new horizons in oncology, leading to the possibility of characterizing the internal architecture of the tumor at the single-cell and spatial levels. This review summarizes the first results acquired through these revolutionary methods for different types of STS. We discuss tumor cell populations and their evolution, interactions between tumor cells and the microenvironment, new prognostic markers, and clinically important targets. Finally, we examine the challenges presented by the single-cell and spatial omics of STS and the future perspectives in this field.

HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling

Single-cell DNA sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on a modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 17,000 cells.

Application and new findings of scRNA-seq and ST-seq in prostate cancer

Prostate cancer is a malignant tumor of the male urological system with the highest incidence rate in the world, which seriously threatens the life and health of middle-aged and elderly men. The progression of prostate cancer involves the interaction between tumor cells and tumor microenvironment. Understanding the mechanisms of prostate cancer pathogenesis and disease progression is important to guide diagnosis and therapy. The emergence of single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (ST-seq) technologies has brought breakthroughs in the study of prostate cancer. It makes up for the defects of traditional techniques such as fluorescence-activated cell sorting that are difficult to elucidate cell-specific gene expression. This review summarized the heterogeneity and functional changes of prostate cancer and tumor microenvironment revealed by scRNA-seq and ST-seq, aims to provide a reference for the optimal diagnosis and treatment of prostate cancer.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition

Cluster analysis, a pivotal step in single-cell sequencing data analysis, presents substantial opportunities to effectively unveil the molecular mechanisms underlying cellular heterogeneity and intercellular phenotypic variations. However, the inherent imperfections arise as different clustering algorithms yield diverse estimates of cluster numbers and cluster assignments. This study introduces Single Cell Consistent Clustering based on Spectral Matrix Decomposition (SCSMD), a comprehensive clustering approach that integrates the strengths of multiple methods to determine the optimal clustering scheme. Testing the performance of SCSMD across different distances and employing the bespoke evaluation metric, the methodological selection undergoes validation to ensure the optimal efficacy of the SCSMD. A consistent clustering test is conducted on 15 authentic scRNA-seq datasets. The application of SCSMD to human embryonic stem cell scRNA-seq data successfully identifies known cell types and delineates their developmental trajectories. Similarly, when applied to glioblastoma cells, SCSMD accurately detects pre-existing cell types and provides finer sub-division within one of the original clusters. The results affirm the robust performance of our SCSMD method in terms of both the number of clusters and cluster assignments. Moreover, we have broadened the application scope of SCSMD to encompass larger datasets, thereby furnishing additional evidence of its superiority. The findings suggest that SCSMD is poised for application to additional scRNA-seq datasets and for further downstream analyses.

Single-cell transcriptomic profiling of the neonatal oviduct and uterus reveals new insights into upper Müllerian duct regionalization

The upper Müllerian duct (MD) is patterned and specified into two morphologically and functionally distinct organs, the oviduct and uterus. It is known that this regionalization process is instructed by inductive signals from the adjacent mesenchyme. However, the interaction landscape between epithelium and mesenchyme during upper MD development remains largely unknown. Here, we performed single-cell transcriptomic profiling of mouse neonatal oviducts and uteri at the initiation of MD epithelial differentiation (postnatal day 3). We identified major cell types including epithelium, mesenchyme, pericytes, mesothelium, endothelium, and immune cells in both organs with established markers. Moreover, we uncovered region-specific epithelial and mesenchymal subpopulations and then deduced region-specific ligand-receptor pairs mediating mesenchymal-epithelial interactions along the craniocaudal axis. Unexpectedly, we discovered a mesenchymal subpopulation marked by neurofilaments with specific localizations at the mesometrial pole of both the neonatal oviduct and uterus. Lastly, we analyzed and revealed organ-specific signature genes of pericytes and mesothelial cells. Taken together, our study enriches our knowledge of upper MD development, and provides a manageable list of potential genes, pathways, and region-specific cell subtypes for future functional studies.

Single-cell and spatial RNA sequencing reveal the spatiotemporal trajectories of fruit senescence

The senescence of fruit is a complex physiological process, with various cell types within the pericarp, making it highly challenging to elucidate their individual roles in fruit senescence. In this study, a single-cell expression atlas of the pericarp of pitaya (Hylocereus undatus) is constructed, revealing exocarp and mesocarp cells undergoing the most significant changes during the fruit senescence process. Pseudotime analysis establishes cellular differentiation and gene expression trajectories during senescence. Early-stage oxidative stress imbalance is followed by the activation of resistance in exocarp cells, subsequently senescence-associated proteins accumulate in the mesocarp cells at late-stage senescence. The central role of the early response factor HuCMB1 is unveiled in the senescence regulatory network. This study provides a spatiotemporal perspective for a deeper understanding of the dynamic senescence process in plants.

Recommendations for detection, validation, and evaluation of RNA editing events in cardiovascular and neurological/neurodegenerative diseases

RNA editing, a common and potentially highly functional form of RNA modification, encompasses two different RNA modifications, namely adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. As inosines are interpreted as guanosines by the cellular machinery, both A-to-I and C-to-U editing change the nucleotide sequence of the RNA. Editing events in coding sequences have the potential to change the amino acid sequence of proteins, whereas editing events in noncoding RNAs can, for example, affect microRNA target binding. With advancing RNA sequencing technology, more RNA editing events are being discovered, studied, and reported. However, RNA editing events are still often overlooked or discarded as sequence read quality defects. With this position paper, we aim to provide guidelines and recommendations for the detection, validation, and follow-up experiments to study RNA editing, taking examples from the fields of cardiovascular and brain disease. We discuss all steps, from sample collection, storage, and preparation, to different strategies for RNA sequencing and editing-sensitive data analysis strategies, to validation and follow-up experiments, as well as potential pitfalls and gaps in the available technologies. This paper may be used as an experimental guideline for RNA editing studies in any disease context.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Single-cell transcriptomic profiling of the neonatal oviduct and uterus reveals new insights into upper Müllerian duct regionalization

The upper Müllerian duct (MD) is patterned and specified into two morphologically and functionally distinct organs, the oviduct and uterus. It is known that this regionalization process is instructed by inductive signals from the adjacent mesenchyme. However, the interaction landscape between epithelium and mesenchyme during upper MD development remains largely unknown. Here, we performed single-cell transcriptomic profiling of mouse neonatal oviducts and uteri at the initiation of MD epithelial differentiation (postnatal day 3). We identified major cell types including epithelium, mesenchyme, pericytes, mesothelium, endothelium, and immune cells in both organs with established markers. Moreover, we uncovered region-specific epithelial and mesenchymal subpopulations and then deduced region-specific ligand-receptor pairs mediating mesenchymal-epithelial interactions along the craniocaudal axis. Unexpectedly, we discovered a mesenchymal subpopulation marked by neurofilaments with specific localizations at the mesometrial pole of both the neonatal oviduct and uterus. Lastly, we analyzed and revealed organ-specific signature genes of pericytes and mesothelial cells. Taken together, our study enriches our knowledge of upper Müllerian duct development, and provides a manageable list of potential genes, pathways, and region-specific cell subtypes for future functional studies.