Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Vascular fate in misidentified pluripotent-derived blood-brain-barrier endothelial cells rescued by transcriptional reprogramming.

ABSTRACT: A single-cell suspension was loaded into the Bio-Rad ddSEQ Single-Cell Isolator on which cells were isolated, lysed and barcoded in droplets. Droplets were then disrupted and cDNA was pooled for second strand synthesis. Libraries were generated with direct tagmentation followed by 3’ enrichment and sample indexing using Illumina Nextera library prep kit. Pooled libraries were sequenced on the Illumina NextSeq500 sequencer. Sequencing data were primarily analyzed using the SureCell RNA Single-Cell App in Illumina BaseSpace Sequence Hub.

ORGANISM(S): Homo sapiens

PROVIDER: GSE138025 | GEO | 2019/12/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Paired human colon and tumor biopsies

Project description:Paired human colon and tumor biopsies were obtained and made into single cell suspensions. Cells were encapsulated into droplets and libraries prepared using the 10X Genomics platform and libraries sequenced on an Illumina NextSeq

2022-02-21 | GSE196964 | GEO

ATAC-seq of E9.5 WT and Smyd1-KO mouse hearts

Project description:Purpose: The goal of this study is to identify the differential cardiac chromatin accessibility between WT and Smyd1 null (Smyd1-KO) hearts at E9.5 using ATAC-seq. Methods: Four hearts at E9.5 were pooled per genotype per replicate, and were then dissociated into single cells. 40,000 viable cells were taken for were lysed to isolate nuclei, which were treated with Tn5 transposase (Nextera DNA Sample Prep Kit, Illumina) to isolate DNA. Fragmented DNA was then amplified using bar-coded PCR primers and libraries were seuqenced. Results: 25851 differential peaks (2-fold change) were identified between E9.5 WT and Smyd1-KO hearts.

2024-04-18 | GSE260690 | GEO

ATAC-seq of E10.5 WT and Chd4-CMko mouse hearts

Project description:Purpose: The goal of this study is to identify the differential cardiac chromatin accessibility between WT and cardiomyocyte conditional knockout (Chd4-CMko) hearts at E10.5 using ATAC-seq. Methods: Three hearts at E10.5 were pooled per genotype per replicate, and were then dissociated into single cells. 40,000 viable cells were taken for were lysed to isolate nuclei, which were treated with Tn5 transposase (Nextera DNA Sample Prep Kit, Illumina) to isolate DNA. Fragmented DNA was then amplified using bar-coded PCR primers and libraries were seuqenced. Results: 15736 differential peaks (2-fold change) were identified between E10.5 WT and Chd4-CMko hearts.

2024-04-18 | GSE260689 | GEO

Single-cell RNA sequencing data for a mixed population of K562 cells and THP-1 cells, encoded with combinatorial DNA barcodes.

Project description:Microdroplet-based co-culturing assays dissect a complex multi-cellular interactions into individual cell-cell interaction events in a highly parallelized manner. To integrate single-cell sequencing approaches into such in-droplet multicellular co-culturing assays, we demonstrate a chemistry approach for encoding the identity of droplets to their belonging cells. K562 cells and THP-1 cells were encapsulated in water-in-oil droplets, where they were labeled with DNA barcodes encoding the identity of individual droplets. Then cells were released from droplets for pooled single-cell RNA sequencing. cDNA and DNA barcodes were sequenced in separate sequencing libraries. Experiments were carried out in duplicate.

2023-06-27 | E-MTAB-12819 | biostudies-arrayexpress

TIM-3 restrains anti-tumour immunity by regulating inflammasome activation.

Project description:Droplet-based massively parallel single-cell RNA sequencing (scRNAseq) was performed by encapsulating sorted live CD45+ tumour-infiltrating cells into droplets and libraries were prepared using Chromium Single Cell 5′ Reagent Kits v2 according to the manufacturer’s protocol (10X Genomics). The generated scRNA-seq libraries were sequenced using an Illumina HiSeq2500.

2021-06-08 | GSE151914 | GEO

UGDH knockdown in MDA-MB-231

Project description:Transcriptome profiling (RNA-Seq) to evaluate the connection the metabolic enzyme UGDH on gene expression. The RNA libraries were prepared and sequenced at University of Houston Seq-N-Edit Core per protocols. Total libraries were prepared with Ovation® Universal Plus mRNA-Seq (NuGen) using 200 ng input RNA. The size selection for libraries were performed using SPRIselect beads (Beckman Coulter) and purity of the libraries were analyzed using the High Sensitivity DNA chip on Bioanalyzer 2100 (Agilent). The prepared libraries pooled and sequenced using NextSeq 500 (Illumina), generating ~15 million 2×76 bp paired-end reads per samples. The RNA-seq raw fastq data were processed with RNA-Seq Express app within the Illumina BaseSpace app suite (www.basespace.illumina.com), which performed alignment with STAR aligner, assignment of aligned reads to genes, and differential gene expression with DESeq2 Analysis was performed comparing controls (shNT) against individual knockdowns (shU1 or shU2). Then, results from both analyses were compared for the intersection to identify commonly altered genes.

2018-08-21 | GSE118772 | GEO

SPANX control of Lamin A/C modulates nuclear architecture and promotes melanoma growth

Project description:Purpose: To investigate mechanisms underlying SPANX knockdown phenotypes, we monitored changes in gene expression profiles in A375 melanoma cells subjected to SPANX KD (RNA-Seq). Methods: RNASeq Libraries were prepared from isolated total RNA using the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina from Lexogen, (Vienna, Austria). Barcoded libraries were pooled and single end sequenced (1X75) on the Illumina NextSeq 500 using the High output V2.5 kit (Illumina Inc., San Diego CA). Raw data FASTQ files were generated by standstard illumina base calling pipeline and stored in illumina cloud service BaseSpace. Reads were aligned with the STASR aligner. Analyses of differentially expressed genes (DEGs) were subsequently performed using a negative binomial test method (edgeR)10 implemented using SARTools R Package Results: Of 609 genes deregulated by both shRNA, 454 were upregulated and 123 were downregulated. Networks associated with cell division were downregulated following SPANX KD, while those associated with 3-phosphoinositide biosynthesis were upregulated. Notably, IPA analysis identified the cell cycle as the primary pathway deregulated, and further analysis using the reactome database revealed that most of those genes were associated with the G1/S transition.

2020-12-31 | GSE141823 | GEO

Quantitative assessment of single-cell RNA sequencing methods

Project description:We generated single-cell transcriptomes from a large number of single cells using several commercially available platforms, in both microliter and nanoliter volumes, and compared performance between them. We benchmarked each method to conventional RNA-seq of the same sample using bulk total RNA, as well as to multiplexed qPCR, which is the current gold standard for quantitative single-cell gene expression analysis. In doing so, we were able to systematically evaluate the sensitivity, precision, and accuracy of various approaches to single-cell RNA-seq. Our results show that it is possible to use single-cell RNA-seq to perform quantitative transcriptome measurements of individual cells, that it is possible to obtain quantitative and accurate gene expression measurements with a relatively small number of sequencing reads, and that when such measurements are performed on large numbers of cells, one can recapitulate the bulk transcriptome complexity, and the distributions of gene expression levels found by single-cell qPCR. 109 single-cell human transcriptomes were analyzed in total; 96 using nanoliter volume sample processing on a microfluidic platform, Nextera library prep (biological replicates); 3 using the SMARTer cDNA synthesis kit, Nextera library prep (biological replicates); 3 using the Transplex cDNA synthesis kit, Nextera library prep (biological replicates); 7 using the Ovation Nugen cDNA synthesis kit (biological replicates) where 3 used Nextera library prep and 4 used NEBNext library prep. In addition, 4 bulk RNA samples were sequenced: bulk RNA generated using ~1 million pooled cells was used to make bulk libraries, 2 of which were made using SMARTer cDNA synthesis kit (technical replicates) and 2 made using Superscript RT kit with no amplification (technical replicates). All 4 bulk samples were made into libraries using Nextera.

2013-10-20 | E-GEOD-51254 | biostudies-arrayexpress

Gene expression pattern of single mES cells during cell cycle stages

Project description:In this study, we aimed to study the gene expression patterns at single cell level across the different cell cycle stages in mESC. We performed single cell RNA-Seq experiment on mESC that were stained with Hoechst 33342 and Flow cytometry sorted for G1, S and G2M stages of cell cycle. Single cell RNA-Seq was performed using Fluidigm C1 system and libraries were generated using Nextera XT (Illumina) kit.

2014-12-29 | E-MTAB-2805 | biostudies-arrayexpress

Single cell RNA-seq of 186 basal and luminal epithelial cells from the mammary gland of adult mice

Project description:Mammary glands of 8 adult (10 week-old) female mice were collected. Freshly sorted basal and luminal epithelial cells were submitted to a Fluidigm C1 System machine for single cell capture and cDNA synthesis. Cells were visualized under the microscope to ensure integrity of the captured single cells prior to cDNA preparation. Libraries were prepared using the Nextera XT kit and sequencing was carried out on an Illumina Hiseq 2000 to achieve 100bp paired-end reads.

2017-11-20 | GSE95432 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data