Similar Datasets
Project description:The development of digestion tract is critical for proper digestion of food and absorbance of nutrient for an individual. It includes the spatial segregation into esophagus, stomach, small and large intestine. The temporal-spatial gene expression profiles of human digestion tract in vivo have never been analyzed at single-cell resolution.Here we analyzed esophagus, stomach, small intestine (SI) and large intestine (LI) from multiple human embryos between 6 and 25 weeks of gestation by single cell RNA-seq analyses.We firstly identified 51 clusters of different types of cells using t- Distributed Stochastic Neighbor Embedding (t-SNE) analysis.Moreover,cell type of each organ were identified according to the known marker genes and new cell types were further analyzed.The dynamic change of each cell type were tracked during the human embryonic digestive tract development.We found HOX family geens paly different roles in the regulation of digestion tract developemnt. In addition, Hedgehog,TGFβ and BMP signaling pathway are essential for SI and LI development in human fetal. The function of nutrient digestion and absorption was increased as the SI development in human fetal.Finally, we demonstrated that the immune system was established at late stage of human fetal and verified the immune-like cells,such as T cell, B cells and macrophage. In summary, by using single cell RNA seq technique, we identified the waves of signaling pathways and critical cell types for the human digestion tract development.
2018-04-05 | GSE95630 | GEO
Project description:Here, using a modified STRT-seq protocol, we analyzed the large intestine (LI) from two adults.In detail, the total 1891 single cells were picked from two adults LI. After the same rigorous filtration as fetal, 1463 individual cells were used for subsequent analysis. We identified 18 cell types including all main cell types existed in intestine such as enterocyte, goblet cell, enteroendocrine, Paneth cell, stem cell and immune cell. Take advantage of single cell RNA sequencing, we found that there were subtypes existed in some cell types. Subsequently, combined with our previous fetal data, we investigate the transcriptomic similarity and difference between human from fetal to adult. The transcriptome feature and development process from fetal to adult were revealed for the first time at single-cell resolution.
2018-04-05 | GSE103154 | GEO
Project description:Tracing the temporal-spatial transcriptomic landscapes of the human fetal digestive tract by single cell RNA-seq analysis
| PRJNA400600 | ENA
Project description:Ginseng, including Asian ginseng (Panax ginseng C. A. Meyer) and American ginseng (P. quinquefolius L.), is one of the most important medicinal herbs in Asia and North America, but significantly understudied. This study sequenced and characterized the transcriptomes and expression profiles of genes expressed in 14 tissues and four different aged roots of Asian ginseng. A total of 265.2 million 100-bp clean reads were generated using the high-throughput sequencing platform HiSeq 2000, representing >8.3x of the 3.2-Gb ginseng genome. From the sequences, 248,993 unigenes were assembled for whole plant, 61,912-113,456 unigenes for each tissue and 54,444-65,412 unigenes for different year-old roots. We comprehensively analyzed the unigene sets and gene expression profiles. We found that the number of genes allocated to each functional category is stable across tissues or developmental stages, while the expression profiles of different genes of a gene family or involved in ginsenoside biosynthesis dramatically diversified spatially and temporally. These results provide an overall insight into the spatial and temporal transcriptome dynamics and landscapes of Asian ginseng, and comprehensive resources for advanced research and breeding of ginseng and related species.
| S-EPMC4675998 | biostudies-literature
Project description:The nuclear factor ?-light-chain enhancer of activated B cells (NF-?B) transcription factor pathway is activated in response to diverse microbial stimuli to regulate expression of genes involved in immune responses and tissue homeostasis. However, the temporal and spatial activation of NF-?B in response to microbial signals have not been determined in whole living organisms, and the molecular and cellular details of these responses are not well understood. We used in vivo imaging and molecular approaches to analyze NF-?B activation in response to the commensal microbiota in transparent gnotobiotic zebrafish.We used DNA microarrays, in situ hybridization, and quantitative reverse transcription polymerase chain reaction analyses to study the effects of the commensal microbiota on gene expression in gnotobiotic zebrafish. Zebrafish PAC2 and ZFL cells were used to study the NF-?B signaling pathway in response to bacterial stimuli. We generated transgenic zebrafish that express enhanced green fluorescent protein under transcriptional control of NF-?B, and used them to study patterns of NF-?B activation during development and microbial colonization.Bacterial stimulation induced canonical activation of the NF-?B pathway in zebrafish cells. Colonization of germ-free transgenic zebrafish with a commensal microbiota activated NF-?B and led to up-regulation of its target genes in intestinal and extraintestinal tissues of the digestive tract. Colonization with the bacterium Pseudomonas aeruginosa was sufficient to activate NF-?B, and this activation required a functional flagellar apparatus.In zebrafish, transcriptional activity of NF-?B is spatially and temporally regulated by specific microbial factors. The observed patterns of NF-?B-dependent responses to microbial colonization indicate that cells in the gastrointestinal tract respond robustly to the microbial environment.
| S-EPMC3164861 | biostudies-literature
Project description:Macroautophagy/autophagy has been demonstrated to play an essential role in embryonic development. However, the role of autophagy during human fetal digestive tract development has not been investigated. Here, by using over 5,000 human embryonic digestive tract cells ranging from 6 weeks to 25 weeks, we explored the dynamic expression of autophagy-related genes at single-cell resolution, and found that the transcriptional activity of autophagy-related genes boosted remarkably and specifically in the early (between 6 and 9 weeks) stages. Interestingly, the small intestine cells at 9 weeks showed the most significant enrichment of autophagy-related genes than any other stages. In summary, our results for the first time revealed that autophagy may play an essential role in the development of the digestive tract, especially for the small intestine, in early human embryos. Abbreviations: GI: gastrointestinal; S-Intes: small intestine; t-SNE: t-distributed stochastic neighbor embedding.
| S-EPMC6844499 | biostudies-literature
Project description:The progress made in directed differentiation of stem cells has shown that understanding human pancreas development can provide cues for generating unlimited amounts of insulin-producing beta cells for transplantation therapy in diabetes. However, current differentiation protocols have not been successful in reproducibly generating functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single cell RNA sequencing with spatial transcriptomics at multiple developmental timepoints and revealed distinct temporal-spatial gene cascades in the developing human pancreas.
2022-12-21 | GSE197317 | GEO
Project description:ProposeLaryngeal chondrosarcoma is a rare non-epithelial malignant tumor. At present, the cell type composition and molecular mechanism of laryngeal chondrosarcoma have not been systematically studied.MethodsThis study focused on the histopathological and imaging features of a rare primary laryngeal chondrosarcoma in a 74-year-old male. The tumor and its paracancerous cartilage tissue were single-cell sequenced and analyzed and a total of 5455 single cells were obtained. Immunohistochemical levels were also verified.ResultsIn total five cell types were identified, including chondrocytes, myeloid cells, fibroblasts, lymphocytes, and endothelial cells. We carried out further subgroup analysis, focusing on the classification and differentiation of chondrocytes, functional enrichment analysis, and cellular communication analysis of all cell types, and explored the tumor microenvironment (TME) of laryngeal chondrosarcoma. Immunohistochemistry revealed the SLAMF9 gene was specifically expressed in non-immune cells of chondrosarcoma, but was barely expressed in the normal cartilage tissues adjacent to chondrosarcomas.ConclusionThis single-cell sequencing approach provides clues for deciphering the potential mechanisms of tumor heterogeneity and TME composition in laryngeal chondrosarcoma, and represents an important step towards the treatment of laryngeal chondrosarcoma.
| S-EPMC8688141 | biostudies-literature
Project description:Single-cell RNAseq (scRNAseq) and paired VDJ analysis and spatial transcriptomics, we create the first comprehensive cell atlas of the healthy developing, paediatric and adult human gut, including 347,980 cells from up to 10 distinct anatomical sites. We use this data to trace the cellular composition of the gut throughout life, define novel cell markers and cell-cell interactions. We find four neuronal cell populations in the developing enteric nervous system, with expression patterns indicative of irritable bowel syndrome and Hirschsprung’s disease, and identify key cell players and communication networks initiating lymphoid structure formation in early human development.
2021-04-30 | E-MTAB-10386 | biostudies-arrayexpress
Project description:Single-cell technologies have revealed the complexity of the tumour immune microenvironment with unparalleled resolution1-9. Most clinical strategies rely on histopathological stratification of tumour subtypes, yet the spatial context of single-cell phenotypes within these stratified subgroups is poorly understood. Here we apply imaging mass cytometry to characterize the tumour and immunological landscape of samples from 416 patients with lung adenocarcinoma across five histological patterns. We resolve more than 1.6 million cells, enabling spatial analysis of immune lineages and activation states with distinct clinical correlates, including survival. Using deep learning, we can predict with high accuracy those patients who will progress after surgery using a single 1-mm2 tumour core, which could be informative for clinical management following surgical resection. Our dataset represents a valuable resource for the non-small cell lung cancer research community and exemplifies the utility of spatial resolution within single-cell analyses. This study also highlights how artificial intelligence can improve our understanding of microenvironmental features that underlie cancer progression and may influence future clinical practice.
| S-EPMC9931585 | biostudies-literature