Project description:We've developed a new Method to Analyze RNA following Intracellular Sorting (MARIS) allowing us to carry out gene expression studies on cells sorted based on intracellular immunoflourescence. The purpose of this study is to determine the degree of bias that MARIS introduces on gene expression. We report RNA-seq gene expression data from human embryonic stem cells differentiated to a stage in which insulin-expressing cells are present. Gene expression data using RNA isolated from live cells is compared to gene expression data using RNA isolated from MARIS processed cells (fixed, permeabilized, antibody stained and mock sorted) to determine the degree of correlation in gene expression between these two biologically identical samples. Human embryonic stem cells are differentiated to a stage in which insulin-expressing cells are present and split into two biologically identical samples. RNA is immediately isolated from one sample using the RNeasy protocol (live sample). RNA is isolated from the second sample following MARIS (processed sample) with all cells collected after the sort in order to keep the cell type composition between the live and processed samples the same.
Project description:We've developed a new Method to Analyze RNA following Intracellular Sorting (MARIS) allowing us to carry out gene expression studies on cells sorted based on intracellular immunoflourescence. The purpose of this study is to determine the degree of bias that MARIS introduces on gene expression. We report Illumina microarray gene expression data from human embryonic stem cells differentiated to a stage in which insulin-expressing cells are present. Gene expression data using RNA isolated from live cells is compared to gene expression data using RNA isolated from MARIS processed cells (fixed, permeabilized, antibody stained and mock sorted) to determine the degree of correlation in gene expression between these two biologically identical samples. Human embryonic stem cells are differentiated to a stage in which insulin-expressing cells are present and split into two biologically identical samples. RNA is immediately isolated from one sample using the RNAeasy protocol (live sample). RNA is isolated from the second sample following MARIS (processed sample) with all cells collected after the sort in order to keep the cell type composition between the live and processed samples the same.
Project description:Human pluripotent stem cells (hPSCs) have the potential to generate any human cell type, and one widely recognized goal is to make pancreatic β cells. To this end, comparisons between differentiated cell types produced in vitro and their in vivo counterparts are essential to validate hPSC-derived cells. Genome-wide transcriptional analysis of sorted insulin-expressing (INS(+)) cells derived from three independent hPSC lines, human fetal pancreata, and adult human islets points to two major conclusions: (i) Different hPSC lines produce highly similar INS(+) cells and (ii) hPSC-derived INS(+) (hPSC-INS(+)) cells more closely resemble human fetal β cells than adult β cells. This study provides a direct comparison of transcriptional programs between pure hPSC-INS(+) cells and true β cells and provides a catalog of genes whose manipulation may convert hPSC-INS(+) cells into functional β cells RNA is isolated and processed using MARIS from the following samples: H1 human embryonic stem cells (hESCs) in duplicate, HUES8 hESCs in duplicate, human induced pluripotent stem cells (hiPSCs) in duplicate, H1 cells differentiated to a stage in which insulin-expressing cells are present (stage 6) in duplicate, HUES8 cells differentiated to stage 6 in duplicate, hiPSCs differentiated to stage 6, insulin-expressing cells sorted from H1 cells differentiated to stage 6 in duplicate, insulin-expressing cells sorted from HUES8 cells differentiated to stage 6 in duplicate, insulin-expressing cells sorted from hiPSCs differentiated to stage 6 in duplicate, human week 16 fetal pancreata in duplicate, insulin-expressing cells sorted from human week 16 fetal pancreata in triplicate, adult human pancreatic islets in triplicate, and insulin-expressing cells sorted from adult human pancreatic islets in triplicate.
Project description:We used microfluidic single cell RNA-seq on 198 individual mouse lung epithelial cells at 4 different stages throughout development to measure the transcriptional states which define the developmental and cellular hierarchy of the distal mouse lung epithelium. We classified 80 cells comprising the distal lung epithelium at E18.5 into distinct populations using an unbiased genome-wide approach that did not require a priori knowledge of the underlying cell types or prior purification of cell types. This M-bM-^@M-^\reverse tissue engineeringM-bM-^@M-^] approach confirmed the basic outlines of the conventional model of cell type diversity in the distal lung and led to the discovery of a large number of novel transcriptional regulators and cell type markers that discriminate between the different populations. Moreover, we reconstructed the steps during maturation of bipotential progenitors into both alveolar lineages based on the presence of undifferentiated, differentiated as well as differentiation intermediate cells at the single time point E18.5. Finally, we followed Sftpc-positive cells throughout their lifecycle (E14.5, E16.5, E18.5, adult) and identified 7 gene sets that differentiate between the multipotential, bipotential, mature, as well as intermediate states of the AT2 lineage. 198 single-cell transcriptomes from mouse lung epithelium were analyzed in total, two 200-cell bulk control samples as well as one no-cell control; All single cell and control samples contain 92 external RNA spike-ins; For time point E18.5, three individual experiments were performed using 3 different pregnant mice (3 biological replicates): Replicate 1 (pooled sibling lungs) yielded 20 single cell transcriptomes, replicate 2 (one single embryonic lung) yielded 34 single cell transcriptomes and replicate 3 (pooled siibling lungs) yielded 26 single cell transcriptomes; In addition, a 200-cell bulk control sample was prepared for E18.5 replicate 1 and E18.5 replicate 3 experiments; A no-cell control sample was generated for the E18.5 replicate 1 experiment; For time point E14.5, one experiment (one pregnant mouse, pooled sibling lungs) was performed yielding 45 single cell transcriptomes; For time point E16.5, one experiment (one pregnant mouse, pooled sibling lungs) was performed yielding 27 single cell transcriptomes; For the adult time point, one 107 day old mouse was used and transcriptomes of 46 single cells were obtained; All single cell samples were processed on the microfluidic platform, 200-cell-bulk and no-cell control samples were processed in microliter volumes in PCR tubes.
Project description:In order to determine the transcriptomic profiles of PrE-induced cells following HDAC3 or Dax1 knock-out in SL(RA) differentiation conditions, RNA-seq was performed on Gata6+ or Nanog+ sort-selected cells. Profiles are contrasted with WT cells in the same differentiation conditions as well as to mock-sorted populations of the three genotypes in 2iLIF conditions.
Project description:We performed single-cell RNA-seq in order to characterize in high resolution the transcriptomic profiles, differentiation fates and heterogeneity of wild-type, HDAC3 or Dax1 knock-out cells in SL(RA) differentiation conditions.
Project description:A remarkable number of long non-coding RNA (lncRNA) species have been identified in mammalian cells, but the genomic origins of these molecules in individual cell types is poorly understood. As a prerequisite to studying the transcriptional regulation of lncRNAs, we conducted a comprehensive analysis of the genomic origins of lncRNAs expressed in embryonic stem cells (ESCs). Polyadenylated RNA and total RNA depleted of ribosomal content was used for preparation of two independent sequencing libraries
Project description:We performed a deep mass-spec analysis to determine DAP5 proteomic signature on human embryonic stem cells (hESCs) by evaluating the steady state proteins level on DAP5-KD and NT control cells.
Project description:Chromatin-associated RNAs have diverse roles in the nucleus. However, their mechanisms of action are poorly understood, in part due to the inability to identify proteins that specifically associate with chromatin-bound RNAs. Here, we address this problem for a subset of chromatin-associated RNAs that form R-loops—RNA-DNA hybrid structures that include a displaced strand of single-stranded DNA. R-loops generally form co-transcriptionally and have important roles in regulation of gene expression, immunoglobulin class switching, and other processes. However, unresolved R-loops can lead to DNA damage and chromosome instability. To identify factors that may bind and potentially regulate R-loop accumulation or mediate R-loop-dependent functions, we used a comparative immunoprecipitation/mass spectrometry approach, with and without RNA-protein crosslinking, to identify a stringent set of R-loop-binding proteins in mouse embryonic stem cells. We identified 365 R-loop-interacting proteins, which were highly enriched for proteins with predicted RNA-binding functions. We characterized several R-loop-interacting proteins of the DEAD-box family of RNA helicases and found that these proteins localize to the nucleolus and, to a lesser degree, the nucleus. Consistent with their localization patterns, we found that these helicases are required for ribosomal RNA processing and regulation of gene expression. Surprisingly, depletion of these helicases resulted in misregulation of highly overlapping sets of protein-coding genes, including many genes that function in differentiation and development. We conclude that R-loop-interacting DEAD-box helicases have non-redundant roles that are critical for maintaining the normal embryonic stem cell transcriptome.