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.
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.
Project description:Human pluripotent stem cells (hPSCs) offer a unique cellular model to study lineage specifications of the primary germ layers during human development. We profiled single-cell RNA-seq (scRNA-seq) on four lineage-specific progenitor cells derived from hESCs. Our scRNA-seq analyses revealed each type of progenitors display various extend of heterogeneity. Specifically, definitive endoderm cells (DECs) not only show a greater degree of heterogeneity, but are also enriched in metabolic signatures. Followed by detailed temporal scRNA-seq profiling along DEC differentiation, we reconstructed a differentiation trajectory using a novel statistical pipeline named Wave-Crest. Wave-Crest further identifies candidate regulators during the transitioning phase from Brachyury (T)+ mesendoderm towards CXCR4+ DEC state. To functionally test identified novel regulators; we generated a live cell monitoring system, a T-2A-EGFP knock-in reporter cell line via CRISPR/CAS9. We demonstrated that, among the top candidate genes, KLF8 plays a pivotal role modulating mesendoderm to DEC differentiation. In this submission, 1810 raw fastq files are provided; 212 are re-analysis from GSE64016. Four expected count matrices are provided - 1) 1018 single cells from snapshot progenitors; 2) 758 single cells from time couse profiling; 3) 19 bulk RNA-seq sample from snapshot progenitors; 4) 15 bulk RNA-seq sample from time course profiling. Total 1018 single cells from snapshot progenitors and 758 single cells from time couse profiling. Matchd population bulk RNA-seq samples for both the progenitors snapshot (19 samples) and time course profiling (15 samples) also included in this submission. These data set are used to detect the transitioning phase from mesendoderm to definitive endoderm.
Project description:During development, the amniote organizer, Hensen’s node, contributes cells to the developing axis in head-to-tail direction. However, some cells remain resident in the node and it has been suggested that these resident cells are stem cells. This study aimed to characterise single resident cells and their environment within the node. Using the chick as an amniote model, we generated transcriptomes of single resident cells (scRNA-seq of GFP cells that remained resident till stage-HH8 following a GFP-donor homotopic transplant into a non-GFP host) and of six node sub-regions (bulk RNA-seq of GFP-transgenic stage-HH8 node, but otherwise un-manipulated embryos). We also obtained transcriptomes of single cells with resident behaviour that would normally never enter the node, but were made to do so (scRNA-seq of cells that remained resident till HH8 following a GFP-donor heterotopic/heterochronic transplant into a non-GFP host).
Project description:Energy metabolism and extracellular matrix function are closely connected to orchestrate and maintain tissue organization, but the crosstalk is poorly understood. Here, we used scRNA-seq analysis to uncover the importance of respiration for extracellular matrix homeostasis in mature cartilage. Genetic inhibition of respiration in cartilage results in the expansion of a central area of 1-month-old mouse femur head cartilage showing disorganized chondrocytes and increased deposition of extracellular matrix material. scRNA-seq analysis identified a cluster-specific decrease in mitochondrial DNA-encoded respiratory chain genes and a unique regulation of extracellular matrix-related genes in nonarticular chondrocyte clusters. These changes were associated with alterations in extracellular matrix composition, a shift in the collagen/non-collagen protein content and an increase of collagen crosslinking and ECM stiffness. The results demonstrate, based on findings of the scRNA-seq analysis, that respiration is a key factor contributing to ECM integrity and mechanostability in cartilage and presumably also in many other tissues.