Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptome analysis of freshly sorted and expanded regulatory and conventional T cells

ABSTRACT: Transcriptome analysis of freshly sorted regulatory T cells (CD4+CD25+) and conventional T cells (CD4+CD25-) and of expansion cultures of regulatory T cells (CD4+CD25+CD45RA+) and conventional T cells (CD4+CD25-). Three biological replicates were performed of freshly sorted Treg and Tconv cells each. Four replicates of Treg expansion cultures sorted into CD45RA+/- subpopulations prior to RNA extraction were performed.

ORGANISM(S): Homo sapiens

SUBMITTER: Christian Schmidl

PROVIDER: E-GEOD-14232 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Lineage-specific DNA methylation in T cells correlates with histone methylation and enhancer activity.

Schmidl Christian C Klug Maja M Boeld Tina J TJ Andreesen Reinhard R Hoffmann Petra P Edinger Matthias M Rehli Michael M

Genome research 20090603 7

DNA methylation participates in establishing and maintaining chromatin structures and regulates gene transcription during mammalian development and cellular differentiation. With few exceptions, research thus far has focused on gene promoters, and little is known about the extent, functional relevance, and regulation of cell type-specific DNA methylation at promoter-distal sites. Here, we present a comprehensive analysis of differential DNA methylation in human conventional CD4(+) T cells (Tconv ...[more]

PMID: 19494038

Similar Datasets

Project description:We have previously developed an approach that fractionates genomic DNA fragments depending on their CpG density (methyl-CpG-immunoprecipitation, MCIp), and adapted this approach to identify regions that are differentially methylated in the two closely related regulatory T-cells (Treg cells) and conventional T-cells (Tconv cells). Because Treg cells naturally occur at a relatively low frequency, we used a previously established protocol to expand Treg cells from a stable naÃ¯ve Treg population that is characterized by the co-expression of CD4, CD25 and CD45RA. We separated gDNA of both expanded T cell lineages (Tregexp and Tconvexp) into unmethylated (CpG) and methylated pools (mCpG) using MCIp and compared cell type-specific differences in DNA methylation by co-hybridization of the two umethylated or the two methylated DNA subpopulations of Treg and Tconv, respectively, to these locus-wide custom tiling arrays. As enriched DNA-fragments from a cell type in the methylated fraction should be depleted in the unmethylated fraction, the signal intensities in CpG pool and mCpG pool hybridizations should complement themselves (âMirror-Imageâ approach) and thereby allow the identification of differentially methylated regions (DMR). Because we expected to find lineage-specific methylation differences with greater probability in regions associated with differential transcriptional activity, we limited our analysis to gene loci that showed cell type-specific gene expression in Treg versus Tconv cells plus a handful of control regions that were equally expressed in both cell types. The microarray used in this study covered 12 megabases of the human genome and contained 69 regions (with a median size of 100.000 kb) and 128 proximal promoter regions and 181 genes, which included a number of well known and functionally relevant genes like CD40LG, IFNG, FOXP3, IL2RA and CTLA4. Keywords: MCIp-on-chip; comparative genomic hybridization With MCIp gDNA from Treg or Tconv cells was separated into hypo- and hypermethylated pools. On each array, wheather the two hypomethylated fractions- one from Treg, the other from Tconv cells- or the two hypermethylated fractions were cohybridized. Two biological replicates.

Dataset Information

Transcriptome analysis of freshly sorted and expanded regulatory and conventional T cells

Publications

Lineage-specific DNA methylation in T cells correlates with histone methylation and enhancer activity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets