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sc-GEM

Methylation

Lih Feng Cheow
Microfluidics Systems Biology Lab, Institute of Molecular and Cell Biology
0.0
3

(...) Published on Rev A

  • supported ifcs:
    Open App IFC
  • number of ifc runs:
    10

Overview

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present Single Cell analysis of Genotype, Expression and Methylation (sc-GEM) to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. sc-GEM combines Single Cell Restriction Analysis of Methylation (SCRAM) assay with single cell RT-qPCR and single cell genotyping by next-generation-sequencing. This targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, is used to profile epigenetic variations within and between different cell types identified through genotyping and transcriptional profiling. This script has been updated to be compatible with all versions of the C1 Open App IFCs, including the redesigned medium 96 cell IFC.

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Protocol: sc-GEMDuration (H:M): 3:00

Cell Load

Sample Prep

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Tested Primary Cells or Cell Lines

Cell Name Cell Type Source
Human Fibroblast Cell line
Human Embryonic Stem Cell Cell line
Human Lung Adenocarcinoma Primary

Performance

Our results showed that sc-GEM is highly sensitive, has low incidence of dropouts in the DNA methylation assay, provides accurate relative quantification of gene expression, and has low levels of contamination, by virtue of automation). The methylation state of a single CpG site determined using sc-GEM was representative of the methylation state of the surrounding region of interest, and the ensemble average of single cell gene expression profiles matched well with bulk gene expression data. Single cell genotyping results with targeted next generation is highly concordant with Sanger Sequencing results.

Publications or Articles

Performance data

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