Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq using drop-based microfluidics

ABSTRACT: The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells. In this experiment we mixed 2 cell types (mES mEF) and then using single cell novel approach we could be able to find each cell (using its barcode) and assign it to mES of mEF and to produce mES and mEF aggregate bam files (converted to bed for GEO submission). 1152_RNA_RTprimers_Barcodes.txt: A list of all 1152 barcodes sequenced for Read2 fastq files.

ORGANISM(S): Mus musculus

SUBMITTER: oren ram

PROVIDER: E-GEOD-62050 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics.

Rotem Assaf A Ram Oren O Shoresh Noam N Sperling Ralph A RA Schnall-Levin Michael M Zhang Huidan H Basu Anindita A Bernstein Bradley E BE Weitz David A DA

PloS one 20150522 5

The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as container ...[more]

PMID: 26000628

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Project description:AtGenExpress: A multinational coordinated effort to uncover the transcriptome of the multicellular model organism Arabidopsis thaliana (Hybridisations done at NASC); The activity of genes and their encoded products can be regulated in several ways, but transcription is the primary level, since all other modes of regulation (RNA splicing, RNA and protein stability, etc.) are dependent on a gene being transcribed in the first place. The importance of transcriptional regulation has been underscored by the recent flood of global expression analyses, which have confirmed that transcriptional co-regulation of genes that act together is the norm, not the exception. Moreover, many studies suggest that evolutionary change is driven in large part by modifications of transcriptional programs. An essential first step toward deciphering the transcriptional code is to determine the expression pattern of all genes. With this goal in mind, an international effort to develop a gene expression atlas of Arabidopsis has been underway since fall 2003. This project, dubbed AtGenExpress, is funded by the DFG, and will provide the Arabidopsis community with access to a large set of Affymetrix microarray data. As part of this collaboration, we have generated expression data from 80 biologicaly different samples in triplicate. Series 2: Base line experiment for pathogen infection. Growth and infection conditions: Seeds will be stratified for 3 days at 4Â°C and sown on soil. Plants are grown at 22Â°C under a 8/16 hour light/dark regime in Percival growth chambers. All pathogen treatments will be performed on leaves of 5-weeks old plants. Bacterial infiltrations will be performed with 10-8 cfu/ml in 10 mM MgCl2. 5x105 spores of Phytophthora infestans in water will be applied to leaf surfaces. LPS (100 Âµg/ml), HrpZ (1 ÂµM), NPP1 (2 ÂµM) or flagellin (1 ÂµM flg22) will be applied in water. Experiments should be performed in triplicate at the time points indicated below. Experimenter name = Dierk Scheel , Frederic Brunner , Lore Westphal; Experimenter institute = AtGenExpress Experiment Overall Design: 18 samples were used in this experiment

Dataset Information

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq using drop-based microfluidics

Publications

High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based Microfluidics.

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