Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single Cell RNA Sequencing Facilitates Quantitative Analysis of CD31+ endothelial cells at day4 of hESC hematopoietic differentiation

ABSTRACT: Single Cell RNA Sequencing Facilitates Quantitative Analysis of CD31+ endothelial cells at day4 of hESC hematopoietic differentiation

PROVIDER: PRJNA511860 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Single Cell RNA Sequencing Facilitates Quantitative Analysis of CD31+ endothelial cells at day4 of hESC hematopoietic differentiation

Project description:Purpose: The goals of this study are to investigate the cell fate desicion and molecular mechanism in CD31+ endothelial cells at the day4 of hematopoietic differentiation. Methods: mRNA profiles of Single CD31+ endothelial cell at day4 of hESC hematopoietic differentiation, were generated by deep sequencing using Illumina GAIIx. The sequence reads that passed quality filters were analyzed with CellRanger pipeline to align reads, generate feature-barcode matrices. Conclusions: We found that the fate of HE and Non-HE has been decided and separated at the emergence of endothelial precursor population during hPSC hematopoiesis.

2018-12-27 | GSE124365 | GEO

RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of human ESCs early hematopoietic differentiation

Project description:Purpose:hESCs hematopoietic differentiation recapitulates embryonic hematopoiesis in vivo and occurs through three main stages: mesoderm commitment, hemogenic endothelium (HE) formation and hematopoietic specification. The goal of this study are to increase the understanding of hESCs hematopoietic differentiation process and its regulatory mechanism. Methods: hESC samples were collected through flow cytometry sorting.mRNA profiles of this samples were generated by deep sequencing using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions: Compared with other three populations, 57 cell surface markers were highly enriched in CD31+CD34+ endothelial cells.

2018-12-19 | GSE124062 | GEO

RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of H1 derived CD31+ cells and H1 after HAND1-overexpression derived CD31+ cells at Day8 after human early hematopoietic differentiation .

Project description:Purpose: The goals of this study are to verify HAND1 overexpression is suffice to upregulate other MAGs in H1 cells during human early hematopoietic differentiation through comparing the transcriptome profilings in WT samples and HAND1-overexpressed samples collected at day 8 after hematopoietic differentiation. Methods: mRNA profiles of hESC samples collected at day 8 after hematopoiesis differentiation were generated by deep sequencing using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions: HAND1 overexpression is suffice to upregulate other MAGs during early hematopoietic differentiation of H1 cells.

2019-07-26 | GSE134906 | GEO

Project description:RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of H1 derived CD31+ cells and H1 after HAND1-overexpression derived CD31+ cells at Day8 after human early hematopoietic differentiation .

| PRJNA556720 | ENA

RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of H1, H1 derived APLNR+ cells, CD31+CD34+ cells and CD43+ cells during human early hematopoietic differentiation

Project description:Purpose: The goals of this study are to verify the dynamic changes of MAGs in H1 derived different population of cells during human early hematopoietic differentian. Methods: mRNA profiles of hESC samples collected from day 0 to day 8 after hematopoiesis differentiation were generated by deep sequencing using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions:MAGs showed convincingly dynamic expression during early hematopoietic differentiation of H1 cells

2019-07-26 | GSE134907 | GEO

RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of BC1, BC1 derived APLNR+ cells, CD31+CD34+ cells and CD43+ cells during human early hematopoietic differentiation

Project description:Purpose: The goals of this study are to verify the dynamic changes of MAGs in BC1 derived different population of cells during human early hematopoietic differentian. Methods: mRNA profiles of hESC samples collected from day 0 to day 8 after hematopoiesis differentiation were generated by deep sequencing using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions:MAGs showed convincingly dynamic expression during early hematopoietic differentiation of BC1 cells

2019-07-26 | GSE134905 | GEO

RNA Sequencing Facilitates Quantitative Analysis of Transcriptomes of human early hematopoietic differentiation

Project description:Purpose: The goals of this study are to identify key transcription factors governing differentiation through comparing thel transcriptome profilings in hESC samples collected from day 0 to day 4 after hematopoietic differentiation. Conclusions: 68 transcriptional factors were found up-regulated gradually and steadily during early hematopoietic differentiation of H1 hESCs. After 4 days of differentiation, the mRNA levels of all these factors increased by more than 10 folds.

2018-01-31 | GSE92241 | GEO

Whole-transcriptome analysis of endothelial-to-hematopoietic stem cell transition

Project description:Hematopoietic stem cells (HSCs) are generated via a natural transdifferentiation process known as endothelial-to-hematopoietic cell transition (EHT). Due to small numbers of embryonal arterial cells undergoing EHT and the paucity of markers to enrich for hemogenic endothelial cells, the genetic program driving HSC emergence is largely unknown. Here, we use a highly sensitive RNAseq method to examine the whole transcriptome of small numbers of enriched aortic HSCs (CD31+cKit+Ly6aGFP+), hemogenic endothelial cells (CD31+cKit-Ly6aGFP+) and endothelial cells (CD31+cKit-Ly6aGFP-). Comparison of mRNA profiles of endothelial cells, hemogenic endothelial cells, and hematopoietic stem cells generated by deep-sequencing of sorted populations from pool of embryos, in triplicate.

2014-12-14 | E-GEOD-63316 | biostudies-arrayexpress

Whole-transcriptome analysis of endothelial-to-hematopoietic stem cell transition

2014-12-14 | GSE63316 | GEO

Transcriptomes of CD31+CD34+HEPs with different expression of CD105 derived from human early hematopoietic differentiation by RNA Sequencing

Project description:Purpose: The goals of this study are to dessect the molecular signature of CD31+CD34+HEPs with different expression of CD105 ,and to explore the regulators such as signaling and transcription factors of CD105+ cells' generation. Methods: mRNA profiles of HEPs samples collected at day4 of hematopoietic differentiation were generated by deep sequencing using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions: The CD31+CD34+CD105-HEPs possess hematopoietic potential whereas the CD31+CD34+CD105+HEPs possess endothelial potential. In addition, the generation of CD105+cells were regulated by TGFbeta signaling and ETS1.

2018-12-15 | GSE123840 | 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