Ontology highlight
ABSTRACT:
PROVIDER: PRJEB25265 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Demosponge Halisarca dujardini - transcriptome sequencing
| PRJEB11837 | ENA
Project description:Limno-terrestrial tardigrades enter a state called anhydrobiosis when exposed to desiccation, and acquire tolerance against various extreme environments. The anhydrobiotic tardigrade Hypsibius dujardini, is a non-pigmented tardigrade easy to culture and RNAi method have been established, therefore making it a model tardigrade for tardigrade molecular research. Previous genome assemblies of this tardigrade had increased size due to heterozygosity. Here, we have sequenced the genome of H. dujardini using single individual Illumina DNA-Seq data and PacBio long read data, and employed a heterozygosity aware assembly method to assemble a near-complete high quality genome. In order to annotate the genome with gene predictions, we conducted RNA-Sequencing of various stages of developmental, juvenile, adult, and anhydrobiotic stage H. dujardini and Ramazzottius varieornatus, a tardigrade capable of rapid anhydrobiosis entry, and used these data for gene prediction with BRAKER v1.9 or differential gene expression analysis of the active and anhydrobiotic stages.
2017-02-28 | GSE94295 | GEO
Project description:Identification and evaluation of specific molecular markers is of great importance for reliable diagnostics and outcome prediction of renal neoplasms Using the Affymetrix microarray, we established the gene expression signatures of normal kidneys and different types of renal tumors. Keywords: Several different biological groups, several samples per group
2008-09-25 | GSE11151 | GEO
Project description:Identification and evaluation of specific molecular markers is of great importance for reliable diagnostics and outcome prediction of renal neoplasms Using the Affymetrix microarray, we established the gene expression signatures of normal kidneys and different types of renal tumors. Keywords: Several different biological groups, several samples per group We analysed several arrays per specific type of renal tumor and normal kidney tissues. This dataset is part of the TransQST collection.
2008-09-25 | E-GEOD-11151 | biostudies-arrayexpress
Project description:Mouse retinal cell atlas: molecular identification of sixty-three amacrine cell types
| PRJNA629793 | ENA
Project description:The vertebrate retina uses diverse neuronal cell types arrayed into complex neural circuits to extract, process and relay information from the visual scene to the higher order processing centers of the brain. Amacrine cells, a diverse class of inhibitory interneurons, are thought to mediate the majority of the processing of the visual signal that occurs within the retina. Despite morphological characterization, the number of known molecular markers of amacrine cell types is still much smaller than the 26 morphological types that have been identified. Furthermore, it is not known how this diversity arises during development. Here, we have combined in vivo genetic labeling and single cell genome-wide expression profiling to: 1) Identify specific molecular types of amacrine cells; 2) Demonstrate the molecular diversity of the amacrine cell class. It is difficult to identify new markers of amacrine cells, due to the fact that they only comprise a small percentage of the total cells in the retina. Additionally, given that there are at least 26 distinct types of amacrine cells, population based approaches fail to achieve the precision necessary to discover markers of each type. To facilitate the identification of new markers for different amacrine cell classes and to more fully characterize the molecular signatures of these classes, we isolated single amacrine cells. To accomplish this goal, we introduced genetic reporters (pNdrg4::GFP or pSynapsin::GFP) into the developing retina (P0) by either in vivo or ex vivo electroporation. These reporters were observed to label morphologically distinct sets of amacrine cells at the different timepoints harvested in this study. Electroporated retinas were then dissociated at different time points and single retinal amacrine cells were isolated by virtue of their GFP expression and placed in tubes containing lysis buffer. Then, their mRNAs were reverse transcribed, and the resulting cDNAs were PCR amplified for 35 cycles. Labeled cDNA samples were hybridized to Affymetrix 430 2.0 microarrays and the data was normalized using MAS5.0 software.
2009-05-31 | E-GEOD-12601 | biostudies-arrayexpress
Project description:To understand organ (dys)function it is important to have a complete inventory of its cell types and the corresponding markers that unambiguously identify these cell types. This is a challenging task, in particular in human tissues, because unique cell-type markers are typically unavailable, necessitating the analysis of complex cell type mixtures. Transcriptome-wide studies on pancreatic tissue are typically done on pooled islet material. To overcome this challenge we sequenced the transcriptome of thousands of single pancreatic cells from deceased organ donors with and without type 2 diabetes (T2D) allowing in silico purification of the different cell types. We identified the major pancreatic cell types resulting in the identification of many new cell-type specific and T2D-specific markers. Additionally we observed several subpopulations within the canonical pancreatic cell types, which we validated in situ. This resource will be useful for developing a deeper understanding of pancreatic biology and diabetes mellitus.
2016-06-24 | GSE81076 | GEO
Project description:Identification of human CD4+ TEM and TEMRA cell-specific gene markers
| PRJNA396204 | ENA
Project description:To understand organ (dys)function it is important to have a complete inventory of its cell types and the corresponding markers that unambiguously identify these cell types. This is a challenging task, in particular in human tissues, because unique cell-type markers are typically unavailable, necessitating the analysis of complex cell type mixtures. Transcriptome-wide studies on pancreatic tissue are typically done on pooled islet material. To overcome this challenge we sequenced the transcriptome of thousands of single pancreatic cells from deceased organ donors with and without type 2 diabetes (T2D) allowing in silico purification of the different cell types. We identified the major pancreatic cell types resulting in the identification of many new cell-type specific and T2D-specific markers. Additionally we observed several subpopulations within the canonical pancreatic cell types, which we validated in situ. This resource will be useful for developing a deeper understanding of pancreatic biology and diabetes mellitus. Human cadaveric pancreata were used to extract islets of Langerhans, which were kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using CEL-seq or on cells stained for CD63, CD13, TGFBR3 or CD24 and CD44. The RaceID algorithm was used to identify clusters of cells corresponding to the major pancreatic cell types and to mine for novel cell type-specific genes as well as subpopulations within the known pancreatic cell types.
2016-06-24 | E-GEOD-81076 | biostudies-arrayexpress