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Bibliometric analysis of research on neurodegenerative diseases and single-cell RNA sequencing: Opportunities and challenges.
Neurodegeneration, characterized by the progressive deterioration in neuronal structure or function, presents an elusive mechanism. The use of single-cell RNA sequencing (scRNA-seq) technology in the clinic is becoming increasingly prevalent in recent decades. This technology offers unparalleled cell-level insights into neurodegenerative diseases, establishing itself as a potent tool for elucidating these diseases underlying mechanisms. Here, we made a deep investigation for scRNA-seq research in neurodegenerative diseases using bibliometric analysis from 2009 to 2022. We observed a robust upward trajectory in the number of publications on this subject. The United States stood out as the principal contributor to this expanding field. Specifically, the University of California System exhibited notable research prowess in this field. Alzheimer disease and Parkinson disease were the diseases most frequently investigated. Key research hotspots include the creation of a molecular brain atlas and identification of vulnerable neuronal subpopulations and potential therapeutic targets at the transcriptomic level.
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Mining single-cell data for cell type-disease associations.
A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and time points. To better understand the associations between cell types and diseases, we leveraged previously developed tools to construct a standardized analysis pipeline and systematically explored associations across four single-cell datasets, spanning a range of tissue types, cell types and developmental time periods. We utilized a set of existing tools to identify co-expression modules and temporal patterns per cell type and then investigated these modules for known disease and phenotype enrichments. Our pipeline reveals known and novel putative cell type-disease associations across all investigated datasets. In addition, we found that automatically discovered gene co-expression modules and temporal clusters are enriched for drug targets, suggesting that our analysis could be used to identify novel therapeutic targets.
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Comprehensive Single-Cell Transcriptomic Atlas of the Mouse Pons and Medulla.
The pons and medulla, key regions of the hindbrain within the brainstem, regulate a wide range of complex behaviors, ranging from motor control to autonomic regulation and reflexes. As the central hub of neural projections and gut-to-brain communication, the cellular diversity that supports these functions remains ambiguous. To address this, we integrated eight single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) datasets from mouse brains. We constructed a large-scale single-cell atlas encompassing 318,522 single cells from different sub-regions of the pons and medulla. Using a rigorous metadata standardization and annotation approach, we identified 45 cell types that span major populations and exhibit subtype-specific variability. We observed high diversity among neuronal populations, while non-neuronal cells were dominated by glial and vascular cells, each with unique transcriptional profiles. This atlas serves as the foundational resource for exploring region-specific cellular diversity in the pons and medulla, enabling comparative analyses for future studies.
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A Cellular Anatomy of the Normal Adult Human Prostate and Prostatic Urethra.
A comprehensive cellular anatomy of normal human prostate is essential for solving the cellular origins of benign prostatic hyperplasia and prostate cancer. The tools used to analyze the contribution of individual cell types are not robust. We provide a cellular atlas of the young adult human prostate and prostatic urethra using an iterative process of single-cell RNA sequencing (scRNA-seq) and flow cytometry on ∼98,000 cells taken from different anatomical regions. Immunohistochemistry with newly derived cell type-specific markers revealed the distribution of each epithelial and stromal cell type on whole mounts, revising our understanding of zonal anatomy. Based on discovered cell surface markers, flow cytometry antibody panels were designed to improve the purification of each cell type, with each gate confirmed by scRNA-seq. The molecular classification, anatomical distribution, and purification tools for each cell type in the human prostate create a powerful resource for experimental design in human prostate disease.
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Transposable element sequence fragments incorporated into coding and noncoding transcripts modulate the transcriptome of human pluripotent stem cells.
Transposable elements (TEs) occupy nearly 40% of mammalian genomes and, whilst most are fragmentary and no longer capable of transposition, they can nevertheless contribute to cell function. TEs within genes transcribed by RNA polymerase II can be copied as parts of primary transcripts; however, their full contribution to mature transcript sequences remains unresolved. Here, using long and short read (LR and SR) RNA sequencing data, we show that 26% of coding and 65% of noncoding transcripts in human pluripotent stem cells (hPSCs) contain TE-derived sequences. Different TE families are incorporated into RNAs in unique patterns, with consequences to transcript structure and function. The presence of TE sequences within a transcript is correlated with TE-type specific changes in its subcellular distribution, alterations in steady-state levels and half-life, and differential association with RNA Binding Proteins (RBPs). We identify hPSC-specific incorporation of endogenous retroviruses (ERVs) and LINE:L1 into protein-coding mRNAs, which generate TE sequence-derived peptides. Finally, single cell RNA-seq reveals that hPSCs express ERV-containing transcripts, whilst differentiating subpopulations lack ERVs and express SINE and LINE-containing transcripts. Overall, our comprehensive analysis demonstrates that the incorporation of TE sequences into the RNAs of hPSCs is more widespread and has a greater impact than previously appreciated.
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Single-Nucleotide RNA Maps for the Two Major Nosocomial Pathogens Enterococcus faecalis and Enterococcus faecium.
Enterococcus faecalis and faecium are two major representative clinical strains of the Enterococcus genus and are sadly notorious to be part of the top agents responsible for nosocomial infections. Despite their critical implication in worldwide public healthcare, essential and available resources such as deep transcriptome annotations remain poor, which also limits our understanding of post-transcriptional control small regulatory RNA (sRNA) functions in these bacteria. Here, using the dRNA-seq technique in combination with ANNOgesic analysis, we successfully mapped and annotated transcription start sites (TSS) of both E. faecalis V583 and E. faecium AUS0004 at single nucleotide resolution. Analyzing bacteria in late exponential phase, we capture ~40% (E. faecalis) and 43% (E. faecium) of the annotated protein-coding genes, determine 5' and 3' UTR (untranslated region) length, and detect instances of leaderless mRNAs. The transcriptome maps revealed sRNA candidates in both bacteria, some found in previous studies and new ones. Expression of candidate sRNAs is being confirmed under biologically relevant environmental conditions. This comprehensive global TSS mapping atlas provides a valuable resource for RNA biology and gene expression analysis in the Enterococci. It can be accessed online at www.helmholtz-hiri.de/en/datasets/enterococcus through an instance of the genomic viewer JBrowse.
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Single-cell epigenetics and multiomics analysis in kidney research.
The rapid evolution of single-cell sequencing technologies has significantly advanced our knowledge of cellular heterogeneity and the underlying molecular basis in healthy and diseased kidneys. While single-cell transcriptomic analysis excels in characterizing cell states in the heterogeneous population, the complex regulatory mechanisms governing the gene expressions are difficult to decipher using transcriptomic data alone. Single-cell sequencing technology has recently extended to include epigenome and other modalities, allowing single-cell multiomics analysis. Especially, the integrative analysis of epigenome and transcriptome dissects the cell-specific, gene-regulatory mechanisms driving cellular heterogeneity. An increasing number of single-cell multimodal atlases are being generated in nephrology research, offering novel insights into cellular diversity and the underpinning epigenetic regulation. This ongoing paradigm shift in kidney research accelerates the identification of new biomarkers and potential therapeutic targets, promoting clinical translation. In this era of transformative nephrology research, the basic knowledge of single-cell sequencing analysis and multiomics approach is valuable not only for basic science researchers but for all nephrologists. This review overview single-cell analysis, with a focus on emerging epigenomic and multiomics approaches and their application to kidney research.
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Single-cell RNA sequencing in the context of neuropathic pain: progress, challenges, and prospects.
Neuropathic pain, characterized by persistent or intermittent spontaneous pain as well as some unpleasant abnormal sensations, is one of the most prevalent health problems in the world. Ectopic nerve activity, central and peripheral nociceptive sensitization and many other potential mechanisms may participate in neuropathic pain. The complexity and ambiguity of neuropathic pain mechanisms result in difficulties in pain management, and existing treatment plans provide less-than-satisfactory relief. In recent years, single-cell RNA sequencing (scRNA-seq) has been increasingly applied and has become a powerful means for biological researchers to explore the complexity of neurobiology. This technique can be used to perform unbiased, high-throughput and high-resolution transcriptional analyses of neuropathic pain-associated cells, improving the understanding of neuropathic pain mechanisms and enabling individualized pain management. To date, scRNA-seq has been preliminarily used in neuropathic pain research for applications such as compiling a dorsal root ganglion atlas, identifying new cell types and discovering gene regulatory networks associated with neuropathic pain. Although scRNA-seq is a relatively new technique in the neuropathic pain field, there have been several studies based on animal models. However, because of the various differences between animals and humans, more attention should be given to translational medicine research. With the aid of scRNA-seq, researchers can further explore the mechanism of neuropathic pain to improve the clinical understanding of the diagnosis, treatment and management of neuropathic pain.
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Single-Cell and Bulk RNA Sequencing Reveal Malignant Epithelial Cell Heterogeneity and Prognosis Signatures in Gastric Carcinoma.
Gastric carcinoma (GC) heterogeneity represents a major barrier to accurate diagnosis and treatment. Here, we established a comprehensive single-cell transcriptional atlas to identify the cellular heterogeneity in malignant epithelial cells of GC using single-cell RNA sequencing (scRNA-seq). A total of 49,994 cells from nine patients with paired primary tumor and normal tissues were analyzed by multiple strategies. This study focused on the malignant epithelial cells, which were divided into three subtypes, including pit mucous cells, chief cells, and gastric and intestinal cells. The trajectory analysis results suggest that the differentiation of the three subtypes could be from the pit mucous cells to the chief cells and then to the gastric and intestinal cells. Lauren's histopathology of GC might originate from various subtypes of malignant epithelial cells. The functional enrichment analysis results show that the three subtypes focused on different biological processes (BP) and pathways related to tumor development. In addition, we generated and validated the prognostic signatures for predicting the OS in GC patients by combining the scRNA-seq and bulk RNA sequencing (bulk RNA-seq) datasets. Overall, our study provides a resource for understanding the heterogeneity of GC that will contribute to accurate diagnosis and prognosis.
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Time series single-cell transcriptional atlases reveal cell fate differentiation driven by light in Arabidopsis seedlings.
Light serves as the energy source for plants as well as a signal for growth and development during their whole life cycle. Seedling de-etiolation is the most dramatic manifestation of light-regulated plant development processes, as massive reprogramming of the plant transcriptome occurs at this time. Although several studies have reported about organ-specific development and expression induced by light, a systematic analysis of cell-type-specific differentiation and the associated transcriptional regulation is still lacking. Here we obtained single-cell transcriptional atlases for etiolated, de-etiolating and light-grown Arabidopsis thaliana seedlings. Informative cells from shoot and root tissues were grouped into 48 different cell clusters and finely annotated using multiple markers. With the determination of comprehensive developmental trajectories, we demonstrate light modulation of cell fate determination during guard cell specialization and vasculature development. Comparison of expression atlases between wild type and the pifq mutant indicates that phytochrome-interacting factors (PIFs) are involved in distinct developmental processes in endodermal and stomatal lineage cells via controlling cell-type-specific expression of target genes. These results provide information concerning the light signalling networks at the cell-type resolution, improving our understanding of how light regulates plant development at the cell-type and genome-wide levels. The obtained information could serve as a valuable resource for comprehensively investigating the molecular mechanism of cell development and differentiation in response to light.