The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.
Retina is composed of a heterogeneous population of cell types, each with a unique biological function. Even if the same type of cells, due to genetic heterogeneity will lead to cell function differences. In the past, traditional molecular biological methods cannot resolve variations in their functional roles that arise from these differences, and some cells are difficult to define due to the lack of specific molecular markers or the scarcity of numbers, which hindered the understanding and research of these cells. With the development of biotechnology, single-cell RNA sequencing can analyze and resolve differences in single-cell transcriptome expression profiles, characterize intracellular population heterogeneity, identify new and rare cell subtypes, and more definitely define the characteristics of each cell type. It clarifies the origin, function, and variations in cell phenotypes. Other attributes include pinpointing both disease-related characteristics of cell subtypes and specific differential gene expression patterns, to deepen our understanding of the causes and progression of diseases, as well as to aid clinical diagnosis and targeted therapy.
Single-cell transcriptome sequencing (scRNA-seq) can resolve the expression characteristics of cells in tissues with single-cell precision, enabling researchers to quantify cellular heterogeneity within populations with higher resolution, revealing potentially heterogeneous cell populations and the dynamics of complex tissues. However, the presence of a large number of technical zeros in scRNA-seq data will have an impact on downstream analysis of cell clustering, differential genes, cell annotation, and pseudotime, hindering the discovery of meaningful biological signals. The main idea to solve this problem is to make use of the potential correlation between cells and genes, and to impute the technical zeros through the observed data. Based on this, this paper reviewed the basic methods of imputing technical zeros in the scRNA-seq data and discussed the advantages and disadvantages of the existing methods. Finally, recommendations and perspectives on the use and development of the method were provided.
Non-small cell lung cancer (NSCLC) is one of the most common types of cancer in the world and is an important cause for cancer death. Although the application of immunotherapy in recent years has greatly improved the prognosis of NSCLC, there are still huge challenges in the treatment of NSCLC. The immune microenvironment plays an important role in the process of NSCLC development, infiltration and metastasis, and they can interact and influence each other, forming a vicious circle. Notably, single-cell RNA sequencing enables high-resolution analysis of individual cells and is of great value in revealing cell types, cell evolution trajectories, molecular mechanisms of cell differentiation, and intercellular regulation within the immune microenvironment. Single-cell RNA sequencing is expected to uncover more promising immunotherapies. This article reviews the important researches and latest achievements of single-cell RNA sequencing in the immune microenvironment of NSCLC, and aims to explore the significance of applying single-cell RNA sequencing to analyze the immune microenvironment of NSCLC.
ObjectiveTo explore the key genes and potential molecular mechanisms of liver and lymph node metastases relevant to duodenal neuroendocrine tumors (DNET). MethodsThe tissues of paracancerous duodenal epithelial, primary lesion, liver metastasis lesion, and lymph node metastasis lesion of a rare DNET accompanied by liver and lymph node metastases were sequenced and analyzed. The differentially expressed genes (DEGs) were screened for different tissues and the functional enrichment analysis was performed. ResultsThe tissues of paracancerous duodenal epithelial was used as the control, a total of 2 053 DEGs expressed only in the liver metastases lesion tissues and 742 DEGs expressed only in the lymph node metastases lesion tissues were screened out, and the top 5 genes expressed in the liver metastases lesion tissues were ORM1, C4BPA, AHSG, C9, and LBP, which in the lymph node metastases lesion tissues were ABHD12B, AC100850.1, HOXC9, AC083967.1, and HOXC8. Kyoto Encyclopedia of Genes and Genomes enrichment analysis found that the DEGs were mainly enriched in the phosphatidylinosiol 3 kinase / protein kinase B pathway, mitogen-activated protein kinase pathway, human papillomavirus infection, etc. ConclusionMultiple DEGs and pathways in metastatic lesions are found in this patient with DNET accompanied by liver metastasis and lymph node metastasis, which provides a new direction for treatment and prophylaxis of DNET.
Single cell RNA sequencing technique provides a strong technical support for the analysis of cell heterogeneity in biological tissues, and has been widely used in biomedical research. In recent years, considerable scRNA-seq data have been accumulated in the research of ocular fundus diseases. The ocular fundus is abundant for the network of vessel and neuron, which leads to the complicated pathogenesis of fundus diseases. Through single cell RNA sequencing technique, the expression of thousands of genes of certain cell types or even subtypes can be obtained in the disease environment. Single cell RNA sequencing technique accurately reveals the pathogenic cell types and pathogenic mechanisms of ocular fundus diseases such as neovascular retinopathy, which provides a theoretical basis for the birth of new diagnosis and treatment targets. The construction of multi-omics single-cell database of ocular fundus diseases will enable high-quality data to be further explored and provide an analysis platform for ophthalmic researchers.
ObjectiveTo understand the single-cell RNA sequencing (scRNA-seq) and its research progress in the tumor microenvironment (TME) of breast cancer, in order to provide new ideas and directions for the research and treatment of breast cancer. MethodThe development of scRNA-seq technology and its related research literature in breast cancer TME at home and abroad in recent years was reviewed. ResultsThe scRNA-seq was a quantum technology in high-throughput sequencing of mRNA at the cellular level, and had become a powerful tool for studying cellular heterogeneity when tissue samples were fewer. While capturing rare cell types, it was expected to accurately describe the complex structure of the TME of breast cancer. ConclusionsAfter decades of development, scRNA-seq has been widely used in tumor research. Breast cancer is a malignant tumor with high heterogeneity. The application of scRNA-seq in breast cancer research can better understand its tumor heterogeneity and TME, and then promote development of personalized diagnosis and treatment.
Diabetic retinopathy (DR) is one of the main causes of vision loss and irreversible blindness in the working-age population, closely regarded as the destruction of the retinal neurovascular unit (NVU). As an important component of the NVU, retinal microglia (RMG) plays a vital role in the progression of DR. In recent years, single-cell RNA sequencing (scRNA-seq) technology has emerged as an important tool in transcriptomic analysis. This latest method reveals the heterogeneity and complexity of RNA transcriptional profiles within individual cells, as well as the composition of different cell types and functions. Utilizing scRNA-seq technology, researchers have further revealed the role of RMG in the occurrence and development of DR, discovering phenotypic heterogeneity, regional heterogeneity, and cell-to-cell communication in RMG. It is anticipated that in the future, more omics technologies and multi-omics correlation analysis methods will be applied to DR and even other ophthalmic diseases, exploring potential diagnostic and therapeutic targets, providing different perspectives for the clinical diagnosis, treatment, and scientific research of DR, and truly promoting clinical translation through technological innovation, thereby benefiting patients with DR diseases.
Objective This study aimed to analyze the differences between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without. Additionally, it seeked to explore the potential correlation between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of Traditional Chinese Medicine (TCM) syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and liver, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and spleen, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of Traditional Chinese Medicine (TCM) syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there were significant differences in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of Traditional Chinese Medicine (TCM) syndrome elements and the species abundance and composition of salivary microbiota between patients with pulmonary nodules and healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.