\"Omics\" typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell\'s metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.

The prognosis for patients with colorectal cancer (CRC) remains worse than expected due to metastasis, recurrence, and resistance to chemotherapy. Colorectal cancer stem cells (CRCSCs) play a vital role in tumor metastasis, recurrence, and chemotherapy resistance. However, there are currently no prognostic markers based on CRCSCs-related genes available for clinical use. In this study, single-cell transcriptome sequencing was employed to distinguish cancer stem cells (CSCs) in the CRC microenvironment and analyze their properties at the single-cell level. Subsequently, data from TCGA and GEO databases were utilized to develop a prognostic risk model for CRCSCs-related genes and validate its diagnostic performance. Additionally, functional enrichment, immune response, and chemotherapeutic drug sensitivity of the relevant genes in the risk model were investigated. Lastly, the key gene RPS17 in the risk model was identified as a potential prognostic marker and therapeutic target for further comprehensive studies. Our findings provide new insights into the prognostic treatment of CRC and offer novel perspectives for a systematic and comprehensive understanding of CRC development.

This study aimed to investigate differences in testicular tissue morphology, gene expression, and marker genes between sexually immature (1-year-old) and sexually mature (10-year-old) Mongolian horses. The purposes of our research were to provide insights into the reproductive physiology of male Mongolian horses and to identify potential markers for sexual maturity. The methods we applied included the transcriptomic profiling of testicular cells using single-cell sequencing techniques. Our results revealed significant differences in tissue morphology and gene expression patterns between the two age groups. Specifically, 25 cell clusters and 10 cell types were identified, including spermatogonial and somatic cells. Differential gene expression analysis highlighted distinct patterns related to cellular infrastructure in sexually immature horses and spermatogenesis in sexually mature horses. Marker genes specific to each stage were also identified, including APOA1, AMH, TAC3, INHA, SPARC, and SOX9 for the sexually immature stage, and PRM1, PRM2, LOC100051500, PRSS37, HMGB4, and H1-9 for the sexually mature stage. These findings contribute to a deeper understanding of testicular development and spermatogenesis in Mongolian horses and have potential applications in equine reproductive biology and breeding programs. In conclusion, this study provides valuable insights into the molecular mechanisms underlying sexual maturity in Mongolian horses.

Glioblastoma (GBM), a prevalent malignant neoplasm within the neuro-oncological domain, has been a subject of considerable scrutiny. Macrophages, serving as the principal immunological constituents, profoundly infiltrate the microenvironment of GBM. However, investigations elucidating the intricate immunological mechanisms governing macrophage involvement in GBM at the single-cell level remain notably limited.
We conducted a comprehensive investigation employing single-cell analysis, aiming to redefine the intricate cellular landscape within both the core and peripheral regions of GBM tumors. Our analytical focus extended to the profound study of macrophages, elucidating their roles within the context of oxidative stress, intercellular information exchange, and cellular trajectories concerning GBM and its assorted subpopulations. We pursued the identification of GBM prognostic genes intricately associated with macrophages. Utilizing experimental research to investigate the relevance of MANBA in the context of GBM.
Our investigations have illuminated the central role of macrophages in the intricate interplay among various subpopulations within the GBM microenvironment. Notably, we observed a pronounced intensity of oxidative stress responses within macrophages when compared to their GBM counterparts in other subpopulations. Moreover, macrophages orchestrated intricate cellular communication networks, facilitated by the SPP1-CD44 axis, both internally and with neighboring subpopulations. These findings collectively suggest the potential for macrophage polarization from an M1 to an M2 phenotype, contributing to immune suppression within the tumor microenvironment. Furthermore, our exploration unearthed GBM prognostic genes closely associated with macrophages, most notably MANBA and TCF12. Remarkably, MANBA appears to participate in the modulation of neuroimmune functionality by exerting inhibitory effects on M1-polarized macrophages, thereby fostering tumor progression. To bolster these assertions, experimental validations unequivocally affirmed the promotional impact of MANBA on GBM, elucidated through its capacity to curb cell proliferation, invasiveness, and metastatic potential.
These revelations represent a pivotal step towards unraveling the intricate immunological mechanisms governing the interactions between macrophages and diverse subpopulations within the GBM milieu. Furthermore, they lay the foundation for the development of an innovative GBM prognostic model, with MANBA at its epicenter, and underscore the potential for novel immunotherapeutic targets in the ongoing pursuit of enhanced treatment modalities for this formidable malignancy.

UNASSIGNED: Single-cell RNA sequencing (scRNA-Seq) provides new perspectives and ideas to investigate the interactions between different cell types and organisms. By integrating scRNA-seq with new computational frameworks or specific technologies, better Alzheimer\'s disease (AD) treatments may be developed.
UNASSIGNED: The single-cell sequencing dataset GSE158234 was obtained from the GEO database. Preprocessing, quality control, dimensionality-reducing clustering, and annotation to identify cell types were performed on it. RNA-seq profiling dataset GSE238013 was used to determine the components of specific cell subpopulations in diverse samples. A set of genes included in the OMIM, Genecards, CTD, and DisGeNET databases were selected as highly plausible AD-related genes. Then, ROC curves were created to predict the diagnostic value using the significantly expressed genes in the KO group as hub genes. The genes mentioned above were mapped to the Coremine Medical database to forecast prospective therapeutic Chinese medicines, and a \"Chinese medicine-ingredient-target\" network was constructed to screen for potential therapeutic targets. The last step was to undertake Mendelian randomization research to determine the causal link between the critical gene IL1B and AD in the genome-wide association study.
UNASSIGNED: Using the scRNA-seq dataset, five unique cell clusters were discovered. These clusters were further subdivided into four distinct cell types using marker genes. The KO group showed a more substantial differential subgroup of macrophages than the WT group. By using the available datasets and PPI network analysis, 54 common genes were discovered. Four clusters were identified using the MCODE approach, and correlation analysis showed that seven genes in those four clusters had a significantly negative correlation with macrophages. Six genes in four sets had a significantly positive correlation. Five genes had different levels of expression in the WT and KO groups. The String database was used to identify the regulatory relationships between the four genes (IL10, CX3CR1, IL1B, and IL6) that were finally selected as AD hub genes. Screening identified potential traditional Chinese medicine to intervene in the transformation process of AD, including Radix Salviae, ginseng, Ganoderma, licorice, Coptidis Rhizoma, and Scutellariae Radix, in addition to promising therapeutic targets, such as PTGS1, PTGS2, and RXRA. Finally, it was shown that IL1B directly correlated with immune cell infiltration in AD. In inverse variance weighting, we found that IL1B was associated with a higher risk of AD, with an OR of 1.003 (95% CI = 1.001-1.006, p = 0.038).
UNASSIGNED: Our research combined network pharmacology and the scRNA-seq computational framework to uncover pertinent hub genes and prospective traditional Chinese medicine potential therapeutic targets for AD. These discoveries may aid in understanding the molecular processes behind AD genes and the development of novel medications to treat the condition.

The Ordos fine-wool sheep is a high-quality breed in China that produces superior natural textiles and raw materials such as wool and lamb meat. However, compared to the Australian Merino sheep, there is still a gap in terms of the wool fiber fineness and wool yield. The hair follicle is the main organ that controls the type of wool fiber, and the morphological changes in the secondary hair follicle are crucial in determining wool quality. However, the process and molecular mechanisms of hair follicle morphogenesis in Ordos fine-wool sheep are not yet clear. Therefore, analyzing the molecular mechanisms underlying the process of follicle formation is of great significance for improving the fiber diameter and wool production of Ordos fine-wool sheep. The differential expressed genes, APOD, POSTN, KRT5, and KRT15, which related to primary hair follicles and secondary hair follicles, were extracted from the dermal papillae. Based on pseudo-time analysis, the differentiation trajectories of dermal lineage cells and epidermal lineage cells in the Ordos fine-wool sheep were successfully constructed, providing a theoretical basis for breeding research in Ordos fine-wool sheep.

We used 10 × genomics single-cell transcriptome sequencing technology to reveal the tumor immune microenvironment characteristics of small cell lung cancer (SCLC) in a patient with malignant pleural effusion (MPE). A total of 8008 high-quality cells were finally obtained for subsequent bioinformatic analysis, which were divided into 10 cell clusters further identified as B cells, T cells, myeloid cells, NK cells, and cancer cells. Such SCLC related genes as NOTCH1, MYC, TSC22D1, SOX4, BLNK, YBX3, VIM, CD8A, CD8B, and KLF6 were expressed in different degrees during differentiation of T and B cells. Different ligands and receptors between T, B and tumor cells almost interact through MHC II, IL-16, galectin, and APP signaling pathway.

Breast cancer metastasis is a complex, multi-step process, with high cellular heterogeneity between primary and metastatic breast cancer, and more complex interactions between metastatic cancer cells and other cells in the tumor microenvironment. High-resolution single-cell transcriptome sequencing technology can visualize the heterogeneity of malignant and non-malignant cells in the tumor microenvironment in real time, especially combined with spatial transcriptome analysis, which can directly compare changes between different stages of metastatic samples. Therefore, this study takes single-cell analysis as the first perspective to deeply explore special or rare cell subpopulations related to breast cancer metastasis, systematically summarizes their functions, molecular features, and corresponding treatment strategies, which will contribute to accurately identify, understand, and target tumor metastasis-related driving events, provide a research basis for the mechanistic study of breast cancer metastasis, and provide new clues for its personalized precision treatment.

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Interferon-gamma (IFN-γ), commonly referred to as type II interferon, is a crucial cytokine that coordinates the tumor immune process and has received considerable attention in tumor immunotherapy research. Previous studies have discussed the role and mechanisms associated with IFN-γ in specific tumors or diseases, but the relevant role of IFN-γ in pan-cancer remains uncertain.
TCGA and GTEx RNA expression data and clinical data were downloaded. Additionally, we analyzed the role of IFN-γ on tumors by using a bioinformatic approach, which included the analysis of the correlation between IFN-γ in different tumors and expression, prognosis, functional status, TMB, MSI, immune cell infiltration, and TIDE. We also developed a PPI network for topological analysis of the network, identifying hub genes as those having a degree greater than IFN-γ levels.
IFN-γ was differentially expressed and predicted different survival statuses in a majority of tumor types in TCGA. Additionally, IFN-γ expression was strongly linked to factors like infiltration of T cells, immune checkpoints, immune-activating genes, immunosuppressive genes, chemokines, and chemokine receptors, as well as tumor purity, functional statuses, and prognostic value. Also, prognosis, CNV, and treatment response were all substantially correlated with IFN-γ-related gene expression. Particularly, the IFN-γ-related gene STAT1 exhibited the greatest percentage of SNVs and the largest percentage of SNPs in UCEC. Elevated expression levels of IFN-γ-related genes were found in a wide variety of tumor types, and this was shown to be positively linked to drug sensitivity for 20 different types of drugs.
IFN-γ is a good indicator of response to tumor immunotherapy and is likely to limit tumor progression, offering a novel approach for immunotherapy\'s future development.