1. Combined analysis of DNA-methylation and transcription profiles in different immune cells identifies hot spots of gene regulation by DNA methylation Marc Bonin 1, Stephan Flemming 2, Stefan Günther 2, Andreas Grützkau 3, Thomas Häupl 1 1 Department of Rheumatology and Clinical Immunology, Charité University Hospital, Berlin, Germany, 2 Institute of Pharmaceutical Sciences, University of Freiburg, Germany, 3 German Arthritis Research Center, Berlin, Germany Marc Bonin Department of Rheumatology and Clinical Immunology Charité University Hospital Charitéplatz 1 D-10117 Berlin Germany Tel: +49(0) 30 450 513 296 Fax: +49(0) 30 450 513 968 E-Mail:marc.bonin@charite.de Web: www.charite-bioinformatik.de In order to test these CpG sites for possible functional effects, we assumed that cell type specific gene expression in different immune cells like T-cells and monocytes are influenced and maintained by DNA methylation. Background: Objective: Methods: Results: Conclusion: www.charite-bioinformatik.de Cells from 4 healthy donors were sorted by FACS technology for naive and memory T-cells (CD4m, CD4n, CD8m, Cd8n), B-cells (CD19m, CD19n), NK-cells (CD56), monocytes (CD14), and granulocytes (CD15). Genome-wide DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip platform. Analysis of data was performed using Genome-Studio (Illumina). Gene expression data were collected from Affymetrix HG-U133Plus 2.0 transcriptomes analysed in the BioRetis database. Mapping of CpG sites with genes was performed using the ensemble genome assembly GRCh37 genomic location map. The number of differentially expressed genes or methylated CpG sites were highest between very different cell types like CD14 monocytes and CD4 T-cells (4624 genes; 19261 sites) and lower between naive and memory cells of the same lymphocyte subtype (CD4: 638 genes; 9412 sites). There was a tendency towards more methylation in memory (CD4m: 5433 sites ≈ 2694 genes) compared to naive cells (CD4n: 3979 sites ≈ 2258 genes) for more than 2-fold change while the overall change was dominated by a decrease from naive to memory status. Overlap of differential expression with corresponding changes in methylation was found in only 629 (279) of 1951 increased (2673 decreased) expressed genes for CD14 versus CD4 comparison and 57 (53) of 332 (306) genes for CD4m versus CD4n cells. Of all CpG sites annotated to these identified genes, only about 10% were concordant with expression. These CpG site were within or immediately upstream of the annotated start of the gene with a maximum distance of ≈1500 nucleotides, indicating that overlap with the promoter site is most likely. A common sequence motif around these CpG sites was not immediately detectable but requires more detailed analysis. Microarray based comparative analysis of transcriptional and epigenetic differences suggests a detailed picture of methylation associated gene regulation and enables to generate an epigenetic map of relevant CpG site for genes expressed and regulated in immune cell types. As many of the microarray based suspected CpG sites of a defined gene did not match with differential gene expression, epigenetic profiling with microarrays has to be interpreted carefully. Methylation of DNA may contribute to the regulation of gene expression. Chip technology enables to analyse for methylation of CpG sites but requires a pre- selection of potential hot spots. Such a selection of potential sites is represented on the HumanMethylation450 array (Illumina). However, it is still necessary to validate, experimentally, which CpG selection is functionally relevant. Contacts: Figure 3 Increased DNA methylation in CD4+ naive cells compared to CD14+ monocytes when focussing on monocyte (CD14+) but not naive T-cell (CD4+) related genes: distribution of methylation frequency for A) all CpG sites; B) 629 genes with increased expression in CD14+ compared to CD4+ cells; C) 50 top candidates with increased expression in CD14+ cells. all629top 50 Figure 1 Human Methylation450 BeadChip n=5344 n=3979 CD4 memory CD4 naive Figure 2 n=178378 n=307198 Comparison of naive and memory CD4+ T-cells revealed a shift from : 1) methylated CpG in naive to unmethylated CpG in memory T-cell genes (total n=307198 sites; >2-fold change n=3979) 2) unmethylated CPG in naive to methylated CpG in memory T-cell genes (total n=178378 sites, >2-fold change n=5344) Figure 4 % methylation in CD4 cells% methylation in CD14 cells nucleotides upstream of gene start % methylation in CD14 cells nucleotides upstream of gene start distance and methylation for CpGs of individual genes Methylation of CpGs in CD14+ monocytes and CD4+ naive T-cells for the top 10 genes increased in CD14+ but not CD4+ cells. X-axis: nucleotides upstream of the gene start; Y-axis: percentage of methylation. The closer the CpG to the start of the gene, the lower the methylation level in actively transcriped genes. Only a minor fraction of all CpGs measured for a defined gene are indicative for activation or silencing of the corresponding gene.