The oxytocin receptor (OXTR) has garnered increasing attention for its role in regulating both mature behaviors and brain development. It has been established that OXTR mediates a range of effects that are region-specific or period-specific. However, the current studies of OXTR expression patterns in mice only provide limited help due to limitations in resolution. Therefore, our objective was to generate a comprehensive, high-resolution spatiotemporal expression map of Oxtr mRNA across the entire developing mouse brain. We applied RNAscope in situ hybridization to investigate the spatiotemporal expression pattern of Oxtr in the brains of male mice at six distinct postnatal developmental stages (P7, P14, P21, P28, P42, P56). We provide detailed descriptions of Oxtr expression patterns in key brain regions, including the cortex, basal forebrain, hippocampus, and amygdaloid complex, with a focus on the precise localization of Oxtr⁺ cells and the variance of expression between different neurons. Furthermore, we identified some neuronal populations with high Oxtr expression levels that have been little studied, including glutamatergic neurons in the ventral dentate gyrus, Vgat⁺Oxtr⁺ cells in the basal forebrain, and GABAergic neurons in layers 4/5 of the cortex. Our study provides a novel perspective for understanding the distribution of Oxtr and encourages further investigations into its functions.
Animals ; Receptors, Oxytocin/metabolism* ; Male ; Brain/growth & development* ; Mice ; Mice, Inbred C57BL ; Neurons/metabolism* ; Single-Cell Analysis ; Gene Expression Regulation, Developmental ; RNA, Messenger/metabolism* ; Animals, Newborn

The regulatory processes in developmental biology research are significantly influenced by long non-coding RNAs (lncRNAs). However, the dynamics of lncRNA expression during human tooth development remain poorly understood. In this research, we examined the lncRNAs present in the dental epithelium (DE) and dental mesenchyme (DM) at the late bud, cap, and early bell stages of human fetal tooth development through bulk RNA sequencing. Developmental regulators co-expressed with neighboring lncRNAs were significantly enriched in odontogenesis. Specific lncRNAs expressed in the DE and DM, such as PANCR, MIR205HG, DLX6-AS1, and DNM3OS, were identified through a combination of bulk RNA sequencing and single-cell analysis. Further subcluster analysis revealed lncRNAs specifically expressed in important regions of the tooth germ, such as the inner enamel epithelium and coronal dental papilla (CDP). Functionally, we demonstrated that CDP-specific DLX6-AS1 enhanced odontoblastic differentiation in human tooth germ mesenchymal cells and dental pulp stem cells. These findings suggest that lncRNAs could serve as valuable cell markers for tooth development and potential therapeutic targets for tooth regeneration.
Humans ; RNA, Long Noncoding/metabolism* ; Odontogenesis/genetics* ; Tooth Germ/embryology* ; Cell Differentiation ; Gene Expression Regulation, Developmental ; Mesoderm/metabolism* ; Tooth/embryology* ; Gene Expression Profiling ; Sequence Analysis, RNA ; Dental Pulp/cytology*

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*

Dysregulated RNA splicing is a well-recognized characteristic of colorectal cancer (CRC); however, its intricacies remain obscure, partly due to challenges in profiling full-length transcript variants at the single-cell level. Here, we employ high-depth long-read scRNA-seq to define the full-length transcriptome of colorectal epithelial cells in 12 CRC patients, revealing extensive isoform diversities and splicing alterations. Cancer cells exhibited increased transcript complexity, with widespread 3'-UTR shortening and reduced intron retention. Distinct splicing regulation patterns were observed between intrinsic-consensus molecular subtypes (iCMS), with iCMS3 displaying even higher splicing factor activities and more pronounced 3'-UTR shortening. Furthermore, we revealed substantial shifts in isoform usage that result in alterations of protein sequences from the same gene with distinct carcinogenic effects during tumorigenesis of CRC. Allele-specific expression analysis revealed dominant mutant allele expression in key oncogenes and tumor suppressors. Moreover, mutated PPIG was linked to widespread splicing dysregulation, and functional validation experiments confirmed its critical role in modulating RNA splicing and tumor-associated processes. Our findings highlight the transcriptomic plasticity in CRC and suggest novel candidate targets for splicing-based therapeutic strategies.
Humans ; Colorectal Neoplasms/metabolism* ; RNA Isoforms/metabolism* ; Single-Cell Analysis ; RNA Splicing ; Gene Expression Regulation, Neoplastic ; RNA, Neoplasm/metabolism* ; Transcriptome

OBJECTIVES: Recent advancements in single-cell RNA sequencing (scRNA-seq) have revolutionized the study of cellular heterogeneity, particularly within the hematological system. However, accurately annotating cell types remains challenging due to the complexity of immune cells. To address this challenge, we develop a PAN-blood single-cell Data Annotator (scPANDA), which leverages a comprehensive 10-million-cell atlas to provide precise cell type annotation. METHODS: The atlas, constructed from data collected in 16 studies, incorporated rigorous quality control, preprocessing, and integration steps to ensure a high-quality reference for annotation. scPANDA utilizes a three-layer inference approach, progressively refining cell types from broad compartments to specific clusters. Iterative clustering and harmonization processes were employed to maintain cell type purity throughout the analysis. Furthermore, the performance of scPANDA was evaluated in three external datasets. RESULTS: The atlas was structured hierarchically, consisting of 16 compartments, 54 classes, 4,‍460 low-level clusters (pd_cc_cl_tfs), and 611 high-level clusters (pmid_cts). Robust performance of the tool was demonstrated in annotating diverse immune scRNA-seq datasets, analyzing immune-tumor coexisting clusters in renal cell carcinoma, and identifying conserved cell clusters across species. CONCLUSIONS scPANDA exemplifies effective reference mapping with a large-scale atlas, enhancing the accuracy and reliability of blood cell type identification.
Humans ; Single-Cell Analysis/methods* ; Sequence Analysis, RNA/methods* ; Blood Cells

Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.
Humans ; Single-Cell Analysis/methods* ; Tuberculosis/genetics* ; Sequence Analysis, RNA/methods* ; Transcriptome/genetics*

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Over the past decade, high-throughput RNA sequencing (RNA-seq) has vastly expanded our understanding of transcriptome dynamics in human physiology and disease. As a powerful tool for investigating systematic changes in RNA biology, RNA-seq has facilitated the discovery of novel functional RNA species. Mature RNA transcripts, which transmit genetic information from DNA to proteins, undergo intricate transcriptional and post-transcriptional regulation. This process allows a single gene to produce multiple RNA transcripts, each performing specific functions depending on the physiological or pathological context. Specific RNA transcripts (SRTs) are uniquely expressed in particular tissues or tumors and are closely associated with tissue-specific functions or disease states, particularly cancer. This review explores the generation of SRTs through key mechanisms, such as alternative splicing (AS), transcriptional regulation, polyadenylation (polyA), and the influence of transposable elements (TEs). We also examine their critical roles in normal tissue development and diseases, with an emphasis on their relevance to cancer. Furthermore, the potential applications of SRTs in diagnosing and treating diseases, especially malignancies, are discussed. By serving as diagnostic markers and therapeutic targets, SRTs hold significant promise in the development of personalized medicine and precision therapies. This review aims to provide new insights into the importance of SRTs in advancing the understanding and treatment of human diseases.
Humans ; Neoplasms/genetics* ; Alternative Splicing/genetics* ; RNA/genetics* ; Animals ; Sequence Analysis, RNA/methods* ; Polyadenylation/genetics*

Humans ; Consensus ; High-Throughput Nucleotide Sequencing/standards* ; Neoplasms/diagnosis* ; Quality Control ; Sequence Analysis, DNA/methods* ; Sequence Analysis, RNA/methods*

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis