HEK293 cells 100 cell RNAseq profiling on Ion Proton
ABSTRACT: Five libraries from 100 HEK293 cells each were prepared using a Smartseq based custom library preparation approach with unique molecular identifiers. One batch of 2 replicates (A) and one batch of 3 replicates (B) were prepared from different cell cultures. Libraries were sequenced on an Ion Proton HEK293 cell (100 cells) 5' selective RNAseq profiling, N4H4 unique molecular identifiers, 2 replicates (A) and 3 replicates (B)
Project description:Three libraries from 100 HEK293 cells each were prepared using a Smartseq based custom library preparation approach with unique molecular identifiers. Libraries were sequenced on a Illumina NextSeq 500 HEK293 cell (100 cells) 5' selective RNAseq profiling, N4H4 unique molecular identifiers, 3 replicates
Project description:We have applied a recently developed, highly accurate and sensitive single-cell RNA-seq method (STRT/C1) to perform a molecular census of two regions of the mouse cerebral cortex: the somatosensory cortex and hippocampus CA1. We isolated cells fresh from somatosensory cortex (S1) and hippocampus CA1 area of juvenile (P22 - P32) CD1 mice, 33 males and 34 females. Cells were collected without selection, except that 116 cells were obtained by FACS from 5HT3a-BACEGFP transgenic mice. A total of 76 Fluidigm C1 runs were performed, each attempting 96 cell captures and resulting in 3005 high-quality single-cell cDNAs, containing Unique Molecular Identifiers allowing counting of individual mRNA molecules, even after PCR amplification.
Project description:Purpose: We applied cDNA molecule counting using unique molecular identifiers combined with high-throughput sequencing to study the transcriptome of individual mouse embryonic stem cells, with spike-in controls to monitor technical performance. We further examined transcriptional noise in the embryonic stem cells. One 96-well plate of single-stranded cDNA libraries generated from 96 single R1 mouse embryonic stem cells sequenced on two lanes, and one 96-well plate of the same libraries further amplified by 9 PCR cycles sequenced on one lane.
Project description:Understanding cell type identity in complex tissues or organisms requires integration of each cell's expression profile with its spatial location within the tissue under study. We developed a high-throughput method that combines in vitro single-cell RNA-sequencing with a gene expression atlas to map single cells back to their location within the tissue of interest. We used the developing brain of a marine annelid, Platynereis dumerilii that is an important model system for studying bilaterian brain evolution, to benchmark our approach. To generate the single-cell mRNA-sequencing data, P. dumerilii larval brains were dissociated, followed by cell capture, cDNA synthesis and amplification on the C1 Single-Cell Auto Prep IFC for 10-17 um cells (Fluidigm). Sequencing libraries were produced using Nexera XT DNA kit (Illumina). In total, we sequenced 213 samples, of which 129 correspond to single, alive cells (as judged by visual inspection of the captured cells) with the remainder consisting of a variety of single dead cells (n=18), wells containing extracellular matrix contaminants (n=8) or multiple cells (n=17), as well as a negative controls where no cells were observed (n=41). For this dataset, we achieved ~90% success rate for the spatial mapping of the single-cell RNA-seq data to P. dumerilii brain atlas. NOTE: 72 additional samples were added on 13th December 2014.
Project description:We used microfluidic single cell RNA-seq on mixed e16.5 mouse lung cells in order to determine the potential cell types present based on differential transcriptional profiles of the entire population using minimal cell selection bias. whole lung mouse e16.5 cells were pooled and loaded onto the Fluidigm C1 device. microwells that contained intact single cells were recorded, the labchip was processed for the generation of cDNA from each cell, and cDNA generated from each accepted well was used to generate amplified and barcoded DNA library that was loaded into an Iluumina HiSeq machine for HTS analysis.
Project description:Single-cell expression profiling by RNA-Seq promises to exploit cell-to-cell variation in gene expression to reveal regulatory circuitry governing cell differentiation and other biological processes. Here, we describe Monocle, a novel unsupervised algorithm for ordering cells by progress through differentiation that dramatically increases temporal resolution of expression measurements. This reordering unmasks switch-like changes in expression of key regulatory factors, reveals sequentially organized waves of gene regulation, and exposes regulators of cell differentiation. A functional screen confirms that a number of these regulators dramatically alter the efficiency of myoblast differentiation, demonstrating that single-cell expression analysis with Monocle can uncover new regulators even in well-studied systems. We selected primary human myoblasts as a model system of cell differentiation to investigate whether ordering cells by progress revealed new regulators of the process. We sequenced RNA-Seq libraries from each of several hundred cells taken over a time-course of serum-induced differentiation. Please note that this dataset is a single-cell RNA-Seq data set, and each cell comes from a capture plate. Thus, each well of the plate was scored and flagged with several QC criteria prior to library construction, which are provided as sample characteristics; CONTROL indicates that this library is a off-chip tube control library constructed from RNA of approximately 250 cells and 'DEBRIS' indicates that the well contained visible debris (and may or may not include a cell). Libraries marked DEBRIS thus cannot be confirmed to come from a single cell.
Project description:Pluripotent stem cells (PSCs) are capable of dynamic interconversion between distinct substates, but the regulatory circuits specifying these states and enabling transitions between them are not well understood. We set out to address this issue and map the landscape of gene expression variability in PSCs by single-cell expression profiling of PSCs under different chemical and genetic perturbations. We find that signaling factors and developmental regulators show highly variable expression in PSCs, with expression states for some variable genes heritable through multiple cell divisions. Expression variability and population heterogeneity can be influenced by perturbation of signaling pathways and chromatin regulators. Strikingly, either removal of mature miRNAs or pharmacologic blockage of external signaling pathways drives PSCs into a low-noise ground state characterized by a reconfigured pluripotency regulatory network, increased self-renewal efficiency, and a distinct chromatin state, an effect mediated by the action of opposing miRNA families on the c-myc / Lin28 / let-7 axis. These findings illuminate the causes of transcriptional heterogeneity in PSCs and their consequences for cellular decision-making. Single-cell RNA-Seq on 183 individual v6.5 mouse embryonic stem cells (mESCs) cultured in serum+LIF media, 94 v6.5 mESCs cultured in 2i+LIF media ('ground state' conditions), and 84 Dgcr8 -/- mESCs (constructed in a v6.5 background), that lack mature miRNAs due to knockout of a miRNA processing factor, cultured in serum+LIF. ChIP-Seq for RNA polymerase II, H3K4me3, H3K27me3, H3K27ac, H3K9me3, and H3K36me3 on the three populations of mESCs profiled by single-cell RNA-Seq. Single-cell RNA-Seq on 54 individual nestin-positive neural precursor cells derived from v6.5 mESCs.
Project description:For unbiased, whole-organism wide cell type profiling, we randomly sampled cells from dissociated Platynereis larvae. To generate the single-cell mRNA-sequencing data, P. dumerilii larvae were dissociated, followed by cell capture, cDNA synthesis and amplification on the C1 Single-Cell Auto Prep IFCs for 5-10 um or 10-17 um cells (Fluidigm). Sequencing libraries were produced using Nexera XT DNA kit (Illumina). In total, we sequenced 596 samples, of which 373 correspond to single, alive cells that passed the quality check criteria. Part of this dataset was previously published (ArrayExpress accession number E-MTAB-2865). Here, we publish additional 383 sequenced cells.