Single cell RNA sequencing of Chromium isolated NGP cells
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ABSTRACT:
PROVIDER: PRJNA605373 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Technological advances in transcriptome sequencing of single cells provided an unprecedented view on tissue composition and cellular heterogeneity. While several studies have compared different single cell RNA-seq methods with respect to data quality and their ability to distinguish cellular subpopulations, none of these comparative studies investigated the heterogeneity of the cellular transcriptional response upon a chemical perturbation. In this study, we evaluated the transcriptional response of NGP neuroblastoma cells upon nutlin-3 treatment using the C1, ddSeq and Chromium single cell systems. These systems and library preparation methods are representative for the wide variety of platforms, ranging from microfluids chips to droplet-based systems and from full transcript sequencing to 3’ end sequencing. In parallel, we used bulk RNA-seq for molecular characterization of the transcriptional response. Two complementary metrics to evaluate performance were applied: the first is the number and identification of differentially expressed genes as robustly assessed by two statistical models, and the second is enrichment analysis of biological signals, which is independent of sample size or number of cells evaluated. Where relevant, we downsampled sequencing library size, selected cell subpopulations based on specific RNA abundance features, or created pseudobulk samples to make the data more comparable. While the C1 detects the highest number of genes per cell and better resembles bulk RNA-seq, the Chromium identifies most differentially expressed genes, albeit still substantially fewer than bulk RNA-seq. Gene set enrichment analyses reveals that detection of the most abundant genes in single cell RNA-seq experiments is sufficient for molecular phenotyping. Finally, single cell RNA-seq reveals a heterogeneous response of NGP cells upon nutlin-3 treatment, pinpointing putative late-responders or resistant cells, hidden in bulk RNA-seq experiments.
2021-12-31 | GSE144929 | GEO
Project description:single cell polyA+ and total RNA-seq data was generated for NGP, SK-N-BE-2C and SHSY5Y-MYCN-TR cells
2019-01-01 | GSE119936 | GEO
Project description:SMARTer single cell total RNA sequencing [NGP]
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Project description:Technological advances in transcriptome sequencing of single cells provided an unprecedented view on tissue composition and cellular heterogeneity. While several studies have compared different single cell RNA-seq methods with respect to data quality and their ability to distinguish cellular subpopulations, none of these comparative studies investigated the heterogeneity of the cellular transcriptional response upon a chemical perturbation. In this study, we evaluated the transcriptional response of NGP neuroblastoma cells upon nutlin-3 treatment using the C1, ddSeq and Chromium single cell systems. These systems and library preparation methods are representative for the wide variety of platforms, ranging from microfluids chips to droplet-based systems and from full transcript sequencing to 3’ end sequencing. In parallel, we used bulk RNA-seq for molecular characterization of the transcriptional response. Two complementary metrics to evaluate performance were applied: the first is the number and identification of differentially expressed genes as robustly assessed by two statistical models, and the second is enrichment analysis of biological signals, which is independent of sample size or number of cells evaluated. Where relevant, we downsampled sequencing library size, selected cell subpopulations based on specific RNA abundance features, or created pseudobulk samples to make the data more comparable. While the C1 detects the highest number of genes per cell and better resembles bulk RNA-seq, the Chromium identifies most differentially expressed genes, albeit still substantially fewer than bulk RNA-seq. Gene set enrichment analyses reveals that detection of the most abundant genes in single cell RNA-seq experiments is sufficient for molecular phenotyping. Finally, single cell RNA-seq reveals a heterogeneous response of NGP cells upon nutlin-3 treatment, pinpointing putative late-responders or resistant cells, hidden in bulk RNA-seq experiments.
2021-12-31 | GSE144930 | GEO
Project description:In this study, we assess technical differences between commonly used single-cell RNA-Sequencing (scRNA-Seq) methods. In this dataset, we assess the RNA detection rates using high-throughput 10x Genomics Chromium system. We mix equal volume of Control Brain RNA (3ul; FirstChoice Total Brain RNA; #AM7962) and ERCC spikes (3ul 1:4 dilution; #4456653) to make a '2x Control RNA+ERCC' master mix. The '2x Control RNA+ERCC' master mix is diluted with equal volume nuclease-free water to make '1x Control RNA+ERCC' master mix. 3ul of '1x Control RNA+ERCC' master mix is added to Chromium single cell suspension and processed as per Chromium guidelines. The sample-data relationship format (SDRF) file for this submission contains only a high-level representation of the sample, library and run information per flow cell, and not per cell. For meta-data at the level of individual cells, please refer to the supplementary file called single_cells_list.txt, which is included as part of this ArrayExpress submission.
2017-03-08 | E-MTAB-5480 | biostudies-arrayexpress
Project description:We performed gene expression profiling by Affymetrix primeview array in both NGP CRISPR control cells and NGP ALK(LF655del) cells.
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Project description:PBMC Fixation and Processing for Chromium Single-Cell RNA Sequencing
| PRJNA449292 | ENA
Project description:Background: Interest in single-cell whole transcriptome analysis is growing rapidly, especially for profiling rare or heterogeneous populations of cells. In almost all reported works, investigators have used live cells which represent several inconveniences and limitations. Some recent cell fixation methods did not work with most primary cells including immune cells. Methods: The methanol-fixation and new processing method was introduced to preserve PBMCs for single-cell RNA sequencing (scRNA-Seq) analysis on 10X Chromium platform. Results: When methanol fixation protocol was broken up into three steps, we found that PBMC RNA was degraded during rehydration with PBS, not at cell fixation and up to three-month storage steps. Resuspension but not rehydration in 3X saline sodium citrate (SSC) buffer instead of PBS preserved PBMC RNA integrity and prevented RNA leakage. Diluted SSC buffer did not interfere with full-length cDNA synthesis. The methanol-fixed PBMCs resuspended in 3X SSC were successfully implemented into 10X Chromium standard scRNA-seq workflows with no elevated low quality cells and cell doublets. The fixation process did not alter the single-cell transcriptional profiles and gene expression levels. Major subpopulations classified by marker genes could be identified in fixed PBMCs at a similar proportion as in live PBMCs. This new fixation processing protocol was validated in CD8+ T cell and several other cell types. Conclusions: We expect that the methanol-based cell fixation procedure presented here will substantially enable complex experimental design with primary cells at single cell resolution.
2018-07-25 | GSE112845 | GEO
Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from Oncorhynchus mykiss B cells isolated from blood.
2021-05-10 | GSE158102 | GEO
Project description:We isolated cells from human antral follicles of various stages and sources and subjected them to 10x Chromium single cell sequencing
2021-03-06 | GSE146512 | GEO