pubmed.ncbi.nlm.nih.gov

DNA methylation profiling of human chromosomes 6, 20 and 22 - PubMed

  • ️Invalid Date

Comparative Study

DNA methylation profiling of human chromosomes 6, 20 and 22

Florian Eckhardt et al. Nat Genet. 2006 Dec.

Abstract

DNA methylation is the most stable type of epigenetic modification modulating the transcriptional plasticity of mammalian genomes. Using bisulfite DNA sequencing, we report high-resolution methylation profiles of human chromosomes 6, 20 and 22, providing a resource of about 1.9 million CpG methylation values derived from 12 different tissues. Analysis of six annotation categories showed that evolutionarily conserved regions are the predominant sites for differential DNA methylation and that a core region surrounding the transcriptional start site is an informative surrogate for promoter methylation. We find that 17% of the 873 analyzed genes are differentially methylated in their 5' UTRs and that about one-third of the differentially methylated 5' UTRs are inversely correlated with transcription. Despite the fact that our study controlled for factors reported to affect DNA methylation such as sex and age, we did not find any significant attributable effects. Our data suggest DNA methylation to be ontogenetically more stable than previously thought.

PubMed Disclaimer

Figures

Figure 1
Figure 1. Type and distribution of amplicons

In total, 2,524 amplicons were analyzed from 6 distinct categories: 43.7% for 5′-untranslated regions (5′-UTR), 22.5% for evolutionary conserved regions (ECR), 14.3% for intronic regions (Intronic), 13.3% for exonic regions (Exonic), 3.6% for Sp1 transcription factor binding sites (Sp1) and 2.6% for Other. Details of the selection criteria for each category are described in Materials and Methods.

Figure 2
Figure 2. 1 Mb region on chromosome 22q12.2, illustrating amplicon coverage in the context of gene and CpG island annotation

Examples of methylation profiles are shown for 8 amplicons and include examples of T-DMRs for genes of diverse functions (OSM, NP_0010001479.1, SMTN and RNF185) and examples of a hyper- (3rd profile from left) and an unmethylated (5th profile from left) CpG island. Rows represent different samples and are grouped according to tissue/cell type. Columns depict CpG sites and the corresponding methylation values are indicated by colour-code for each cell (blank cells indicate no data).

Figure 3
Figure 3

(a) Correlation between co-methylation and spatial distance. Orange dots represent CpG methylation values aggregated and averaged over 25,000 individual measurements. Grey dots represent CpG methylation values based on re-sampling of random CpG positions. Blue dots indicate CpG methylation values based on re-sampling of amplicon positions. At distances larger than 1,000 bp no correlation between CpG methylation and spatial distance is detectable. (b) Absolute methylation differences between cell types/tissues. Absolute methylation differences of matched CpGs were determined by pair wise comparison. Differences are colour coded from blue to red indicating a 5% to 20% difference in methylation, respectively.

Figure 3
Figure 3

(a) Correlation between co-methylation and spatial distance. Orange dots represent CpG methylation values aggregated and averaged over 25,000 individual measurements. Grey dots represent CpG methylation values based on re-sampling of random CpG positions. Blue dots indicate CpG methylation values based on re-sampling of amplicon positions. At distances larger than 1,000 bp no correlation between CpG methylation and spatial distance is detectable. (b) Absolute methylation differences between cell types/tissues. Absolute methylation differences of matched CpGs were determined by pair wise comparison. Differences are colour coded from blue to red indicating a 5% to 20% difference in methylation, respectively.

Figure 4
Figure 4. CpG methylation at transcription start sites (TSSs)

CpG methylation values were binned (each bin containing 1,000 values), averaged and plotted according to their relative distance to the TSS (orange dots). Blue dots represent bins containing Sp1 sites identified previously by Cawley et al.. Centered on the TSS, a symmetric core of about 1,000 bp is unmethylated.

Figure 5
Figure 5. Global DNA methylation and age/sex

Differences of mean methylation were determined in three tissues (heart muscle, skeletal muscle, liver) for two age groups (group 1: 26 years, SD +/− 4 years and group 2: 68 years, SD +/− 8 years, red line), males/females (orange line) and two different primary cells (CD4+ lymphocytes, dermal fibroblasts, blue line). As control, tissues were re-sampled (10,000-fold) for both age groups and their mean methylation differences were calculated (grey area). The same control was carried out for sex-specific differences and similar results were obtained (data not shown). As positive control for sex-specific methylation, an X-chromosomal gene (ELK1) was used that displays the expected methylation difference of about 50% (green line). While the 7.1% difference between primary cells (blue line) is highly significant, the respective differences of 0.275% and 0.1% between age groups (red line) and sex (orange line) fall within the differential range observed for the control (grey area) and are therefore not significant.

Figure 6
Figure 6

(a) Relative proportion of putative T-DMRs. Normalized for the number of amplicons in each category, the proportion of T-DMRs was highest in ECRs, both intergenic and intragenic ECRs while T-DMRs located within 5′-UTRs have a lower frequency of occurrence (b) Correlation between 5′-UTR methylation and mRNA expression. Representative results are shown for 2 genes. Expression was determined for 43 genes and one positive control (ACTINB1) in 8 tissues/cell types using reverse transcriptase (RT) PCR. Total RNAs derived from mixed tissues and cell lines were used as positive control. Differential 5′-UTR methylation is inversely correlated with mRNA expression for OSM and SERPINB5 (for which the inverse correlation was previously known) but not for TBX18. The colour code depicts the degree of 5′-UTR methylation for each gene (yellow ≈ 0% methylation, green ≈ 50% and blue ≈ 100% methylation).

Figure 6
Figure 6

(a) Relative proportion of putative T-DMRs. Normalized for the number of amplicons in each category, the proportion of T-DMRs was highest in ECRs, both intergenic and intragenic ECRs while T-DMRs located within 5′-UTRs have a lower frequency of occurrence (b) Correlation between 5′-UTR methylation and mRNA expression. Representative results are shown for 2 genes. Expression was determined for 43 genes and one positive control (ACTINB1) in 8 tissues/cell types using reverse transcriptase (RT) PCR. Total RNAs derived from mixed tissues and cell lines were used as positive control. Differential 5′-UTR methylation is inversely correlated with mRNA expression for OSM and SERPINB5 (for which the inverse correlation was previously known) but not for TBX18. The colour code depicts the degree of 5′-UTR methylation for each gene (yellow ≈ 0% methylation, green ≈ 50% and blue ≈ 100% methylation).

Figure 7
Figure 7. Conservation of methylation between human/mouse orthologous amplicons

59 orthologous amplicons (37 ECRs (yellow) and 22 5′-UTRs (grey)) were analyzed in four tissues (skin, skeletal muscle, heart muscle and liver) from both species. The majority (69.4%) of ECR and 5′-UTR amplicons differed by less than 20% methylation, indicating significant conservation. Both, hyper- and unmethylated amplicons showed a similar degree of methylation conservation (data not shown).

Comment in

  • Toward a human epigenome.

    Brena RM, Huang TH, Plass C. Brena RM, et al. Nat Genet. 2006 Dec;38(12):1359-60. doi: 10.1038/ng1206-1359. Nat Genet. 2006. PMID: 17133218 No abstract available.

Similar articles

Cited by

References

    1. International Human Genome Sequencing Consortium Finishing the euchromatic sequence of the human genome. Nature. 2004;431:931–45. - PubMed
    1. International Human Genome Sequencing Consortium Initial sequencing and analysis of the human genome. Nature. 2001;409:860–921. - PubMed
    1. Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat. Genet. 2003;33:245–254. - PubMed
    1. Murrell A, Rakyan VK, Beck S. From genome to epigenome. Hum. Mol. Genet. 2005;14:R3–R10. - PubMed
    1. Jones PA, Martienssen RA. blueprint for a Human Epigenome Project: the AACR Human Epigenome Workshop. Cancer Res. 2005;65:11241–11246. - PubMed

Publication types

MeSH terms

Substances