Ontology highlight
ABSTRACT:
PROVIDER: PRJNA836091 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We developed SCAN-seq2, a high-throughput and highly sensitive single-cell RNA sequencing method based on the TGS platform. Our study demonstrated that SCAN-seq2 improves upon the previous method, SCAN-seq, in terms of sensitivity and throughput. By using reference-guided assembly of single-cell data, we were able to identify thousands of novel full-length RNA isoforms, including cell type-specific expression patterns of pseudogenes. We also accurately determined V(D)J rearrangement events in T and B cells. Lastly, we found that treatment of HepG2 and Hela cells with the spliceosome inhibitor Isoginkgetin (IGG) resulted in a subpopulation of cells with distinct apoptosis features. Our study provides a promising new tool for single-cell transcriptome research. The source code for SCAN-seq2 data analysis pipelines is available at https://github.com/liuzhenyu-yyy/SCAN-seq2 .
2022-11-15 | GSE203561 | GEO
Project description:We report how methanol fixation influences transcriptome profile in single cell RNA-seq. We generatad Smart-seq2 data from two cell lines, and both live and fixed cells from each cell line were processed and analyzed to illustrate fixaiton effect.
2021-05-18 | GSE150993 | GEO
Project description:30 B-lymphoblastoid cell lines (LCLs) with genome-wide genotype data were treated with hydrocortisone (GR agonist) and CORT108297 (GR modulator), followed by RNA-seq to identify PGx-eQTLs. We then integrated GR chromatin immunoprecipitation-sequencing (ChIP-seq) to characterize the epigenetic function of PGx-eQTLs that interfere with GR response elements. We also applied a high-throughput enhancer assay (STARR-seq) using PGx-eQTL loci DNA sequences to “scan” for drug-dependent SNPs.
2022-11-16 | GSE185928 | GEO
Project description:Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with three-fold higher sensitivity, lower costs, and less hands-on time. We also implemented CEL-Seq2 on Fluidigm’s C1 system, thereby providing its first single-cell, on-chip barcoding method, and detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2’s increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use
2016-04-08 | GSE78779 | GEO
Project description:Creation of circulating cancer cell-lines and caracterisation of these cell-lines which will be collected before any treatment in patients with metastatic colon adenocarcinoma
| 2323696 | ecrin-mdr-crc
Project description:Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods and provides a framework for benchmarking further improvements of scRNA-seq protocols.
2016-09-09 | GSE75790 | GEO
Project description:Four Kcng4-cre;stop-YFP mouse retinas from two mice were dissected, dissociated and FACS sorted, and single cell RNA-seq libraries were generated for 384 single cells using Smart-seq2. Aligned bam files are generated for 383 samples as one failed to align. Four mouse retinas (labeled 1la, 1Ra, and 2la, 2Ra respective from the two mice) were used, and 96 single cells from each were processed using Smart-seq2. Total 384 cells Smart-seq2 analysis of P17 FACS sorted retinal cells from the Kcng4-cre;stop-YFP mice (Kcng4tm1.1(cre)Jrs mice [Duan et al., Cell 158, 793-807, 2015] crossed to the cre-dependent reporter Thy1-stop-YFP Line#1 [Buffelli et al., Nature 424, 430-434, 2003])
2016-08-25 | E-GEOD-81903 | biostudies-arrayexpress
Project description:Evolutionarily conserved SCAN domain-containing zinc finger transcription factors (ZSCAN) have been found in both the mouse and human genomes. Of which, Zscan4 is crucial for zygotic genome activation (ZGA) in preimplantation embryos, and induced pluripotent stem cell (iPSC) reprogramming. However, little is known about the mechanism of Zscan4 underlying these processes of cell fate control. Here we show that Zscan4f, a representative of ZSCAN proteins, is able to recruit Tet2 through its SCAN domain. The Zscan4f-Tet2 interaction promotes DNA demethylation and regulates the expression of target genes, particularly those encoding glycolytic enzymes and proteasome subunits. Disruption of the Zscan4f-Tet2 interaction impairs cellular metabolism, proteasome function, and ultimately compromises iPSC generation. These results identify Tet2 as a major cooperator for the function of Zscan4f, and suggest a common mechanism shared by SCAN family transcription factors to recruit TET DNA dioxygenases to regulate diverse cellular processes.
2019-11-13 | GSE140236 | GEO
Project description:This dataset consists of single-cell RNA-seq (Smart-seq2) data from 95 forward programmed cells derived from human induced pluripotent stem cells (hiPSCs). Cells conditionally expressing either ATOH1, ETV2 or NKX3-1 under the control of a tetracycline-response element (Tet-ON system) were co-cultured on Matrigel in 2 dimensions. Data was used to explore the forward-programming potential of these transcription factors (TFs) when cell lines with the capacity to differentiate in isolation are cultured together.
2020-07-21 | GSE154759 | GEO
Project description:Single-cell RNA-seq (Smart-Seq2) to profile of cardiac progenitor cells
2018-09-12 | GSE114279 | GEO