Similar Datasets
Project description:We sought to determine the mRNA transcriptome of all major human pancreatic endocrine and exocrine cell subtypes, including human alpha, beta, duct and acinar cells. In addition, we identified the cell type-specific distribution of transcription factors, signalling ligands and their receptors.Islet samples from healthy human donors were enzymatically dispersed to single cells and labelled with cell type-specific surface-reactive antibodies. Live endocrine and exocrine cell subpopulations were isolated by FACS and gene expression analyses were performed using microarray analysis and quantitative RT-PCR. Computational tools were used to evaluate receptor-ligand representation in these populations.Analysis of the transcriptomes of alpha, beta, large duct, small duct and acinar cells revealed previously unrecognised gene expression patterns in these cell types, including transcriptional regulators HOPX and HDAC9 in the human beta cell population. The abundance of some regulatory proteins was different from that reported in mouse tissue. For example, v-maf musculoaponeurotic fibrosarcoma oncogene homologue B (avian) (MAFB) was detected at equal levels in adult human alpha and beta cells, but is absent from adult mouse beta cells. Analysis of ligand-receptor interactions suggested that EPH receptor-ephrin communication between exocrine and endocrine cells contributes to pancreatic function.This is the first comprehensive analysis of the transcriptomes of human exocrine and endocrine pancreatic cell types-including beta cells-and provides a useful resource for diabetes research. In addition, paracrine signalling pathways within the pancreas are shown. These results will help guide efforts to specify human beta cell fate by embryonic stem cell or induced pluripotent stem cell differentiation or genetic reprogramming.
| S-EPMC3880150 | biostudies-literature
Project description:Various abnormalities of transcriptional regulation revealed by RNA sequencing (RNA-seq) have been reported in cancers. However, strategies to integrate multi-modal information from RNA-seq, which would help uncover more disease mechanisms, are still limited. Here, we present PipeOne, a cross-platform one-stop analysis workflow for large-scale transcriptome data. It was developed based on Nextflow, a reproducible workflow management system. PipeOne is composed of three modules, data processing and feature matrices construction, disease feature prioritization, and disease subtyping. It first integrates eight different tools to extract different information from RNA-seq data, and then used random forest algorithm to study and stratify patients according to evidences from multiple-modal information. Its application in five cancers (colon, liver, kidney, stomach, or thyroid; total samples n = 2024) identified various dysregulated key features (such as PVT1 expression and ABI3BP alternative splicing) and pathways (especially liver and kidney dysfunction) shared by multiple cancers. Furthermore, we demonstrated clinically-relevant patient subtypes in four of five cancers, with most subtypes characterized by distinct driver somatic mutations, such as TP53, TTN, BRAF, HRAS, MET, KMT2D, and KMT2C mutations. Importantly, these subtyping results were frequently contributed by dysregulated biological processes, such as ribosome biogenesis, RNA binding, and mitochondria functions. PipeOne is efficient and accurate in studying different cancer types to reveal the specificity and cross-cancer contributing factors of each cancer.It could be easily applied to other diseases and is available at GitHub.
| S-EPMC8701385 | biostudies-literature
Project description:Profiling the transcriptome, spliceome, and methylome of developing soybean nodules reveals insights into their associations that may configure transcriptome complexity and proteome diversity
2020-05-22 | GSE135971 | GEO
Project description:Profiling the transcriptome, spliceome, and methylome of developing soybean nodules reveals insights into their associations that may configure transcriptome complexity and proteome diversity
2020-05-22 | GSE135969 | GEO
Project description:BACKGROUND:Larval developmental patterns are extremely varied both between and within phyla, however the genetic mechanisms leading to this diversification are poorly understood. We assembled and compared the developmental transcriptomes for two sea biscuit species (Echinodermata: Echinoidea) with differing patterns of larval development, to provide a resource for investigating the evolution of alternate life cycles. One species (Clypeaster subdepressus) develops via an obligately feeding larva which metamorphoses 3-4 weeks after fertilization; the other (Clypeaster rosaceus) develops via a rare, intermediate larval type-facultative feeding- and can develop through metamorphosis entirely based on egg provisioning in under one week. RESULTS:Overall, the two transcriptomes are highly similar, containing largely orthologous contigs with similar functional annotation. However, we found distinct differences in gene expression patterns between the two species. Larvae from C. rosaceus, the facultative planktotroph, turned genes on at earlier stages and had less differentiation in gene expression between larval stages, whereas, C. subdepressus showed a higher degree of stage-specific gene expression. CONCLUSION:This study is the first genetic analysis of a species with facultatively feeding larvae. Our results are consistent with known developmental differences between the larval types and raise the question of whether earlier onset of developmental genes is a key step in the evolution of a reduced larval period. By publishing a transcriptome for this rare, intermediate, larval type, this study adds developmental breadth to the current genetic resources, which will provide a valuable tool for future research on echinoderm development as well as studies on the evolution of development in general.
| S-EPMC5960215 | biostudies-literature
Project description:Understanding the tumor microenvironment is important to efficiently identify appropriate patients for immunotherapies in a variety of cancers. Here, we presented the tumor microenvironmental analysis of 2,033 cancer samples across 7 cancer types: colon adenocarcinoma, skin cutaneous melanoma, kidney renal papillary cell carcinoma, sarcoma, pancreatic adenocarcinoma, glioblastoma multiforme, and pheochromocytoma / paraganglioma from The Cancer Genome Atlas cohort. Unsupervised hierarchical clustering based on the gene expression profiles separated the cancer samples into two distinct clusters, and characterized those into immune-competent and immune-deficient subtypes using the estimated abundances of infiltrated immune and stromal cells. We demonstrated differential tumor microenvironmental characteristics of immune-competent subtypes across 7 cancer types, particularly immunosuppressive tumor microenvironment features in kidney renal papillary cell carcinoma with significant poorer survival rates and immune-supportive features in sarcoma and skin cutaneous melanoma. Additionally, differential genomic instability patterns between the subtypes were found across the cancer types, and discovered that immune-competent subtypes in most of cancer types had significantly higher immune checkpoint gene expressions. Overall, this study suggests that our subtyping approach based on transcriptomic data could contribute to precise prediction of immune checkpoint inhibitor responses in a wide range of cancer types.
| S-EPMC7293350 | biostudies-literature
Project description:Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.
| S-EPMC6306246 | biostudies-literature
Project description:Pancreatic islets of Langerhans contain several specialized endocrine cell types, which are commonly identified by the expression of single marker genes. However, the established marker genes cannot capture the complete spectrum of cellular heterogeneity in human pancreatic islets, and existing bulk transcriptome datasets provide averages across several cell populations. To dissect the cellular composition of the human pancreatic islet and to establish transcriptomes for all major cell types, we performed single-cell RNA sequencing on 70 cells sorted from human primary tissue. We used this dataset to validate previously described marker genes at the single-cell level and to identify specifically expressed transcription factors for all islet cell subtypes. All data are available for browsing and download, thus establishing a useful resource of single-cell expression profiles for endocrine cells in human pancreatic islets.
| S-EPMC4784001 | biostudies-literature
Project description:The zebrafish intestine and liver, as in other vertebrates, are derived from the endoderm. Great effort has been devoted to deciphering the molecular mechanisms controlling the specification and development of the zebrafish intestine and liver; however, genome-wide comparison of the transcriptomes between these two organs at the larval stage remains unexplored. There is a lack of extensive identification of feature genes marking specific cell types in the zebrafish intestine and liver at 5 days post-fertilization, when the larval fish starts food intake. In this report, through RNA sequencing and single-cell RNA sequencing of intestines and livers separately dissected from wild-type zebrafish larvae at 5 days post-fertilization, together with the experimental validation of 47 genes through RNA whole-mount in situ hybridization, we identified not only distinctive transcriptomes for the larval intestine and liver, but also a considerable number of feature genes for marking the intestinal bulb, mid-intestine and hindgut, and for marking hepatocytes and cholangiocytes. Meanwhile, we identified 135 intestine- and 97 liver-enriched transcription factor genes in zebrafish larvae at 5 days post-fertilization. Our findings provide rich molecular and cellular resources for studying cell patterning and specification during the early development of the zebrafish intestine and liver.
| S-EPMC9600436 | biostudies-literature
Project description:Prolonged exposure to weak (~1 ?T) extremely-low-frequency (ELF, 50/60 Hz) magnetic fields has been associated with an increased risk of childhood leukaemia. One of the few biophysical mechanisms that might account for this link involves short-lived chemical reaction intermediates known as radical pairs. In this report, we use spin dynamics simulations to derive an upper bound of 10 parts per million on the effect of a 1 ?T ELF magnetic field on the yield of a radical pair reaction. By comparing this figure with the corresponding effects of changes in the strength of the Earth's magnetic field, we conclude that if exposure to such weak 50/60 Hz magnetic fields has any effect on human biology, and results from a radical pair mechanism, then the risk should be no greater than travelling a few kilometres towards or away from the geomagnetic north or south pole.
| S-EPMC6417859 | biostudies-literature