Open Access Research

Adult monozygotic twins discordant for intra-uterine growth have indistinguishable genome-wide DNA methylation profiles

Nicole YP Souren123*, Pavlo Lutsik1, Gilles Gasparoni1, Sascha Tierling1, Jasmin Gries1, Matthias Riemenschneider4, Jean-Pierre Fryns5, Catherine Derom5, Maurice P Zeegers236 and Jörn Walter1*

Author Affiliations

1 Laboratory of EpiGenetics, FR 8.3 Life Sciences, Saarland University, Saarbrücken, 66123, Saarland, Germany

2 Department of Genetics and Cell Biology, Maastricht University, Maastricht, 6200 MD, Limburg, The Netherlands

3 Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University, Maastricht, 6200 MD, Limburg, The Netherlands

4 Department of Psychiatry and Psychotherapy, Saarland University Hospital, Homburg, 66424, Saarland, Germany

5 Department of Human Genetics, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, B-3000, Vlaams-Brabant, Belgium

6 Unit of Urologic and Genetic Epidemiology, Department of Public Health and Epidemiology, University of Birmingham, Birmingham, B15 2TT, West Midlands, UK

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Genome Biology 2013, 14:R44  doi:10.1186/gb-2013-14-5-r44

Published: 26 May 2013

Additional files

Additional file 1:

Supplemental methods, tables and figures. Supplemental methods include Infinium HumanMethylation450 data pre-processing, adjustment for cell type heterogeneity, and association analysis and candidate selection. Table S1: DNA methylation profiles used to create the cell-type reference data set. Table S2: cell type-specific quantitative markers used as explanatory variables in heterogeneity adjustment. Table S3: characteristics of the 45 CpG sites that are significantly differentially methylated between the heavy and light co-twins identified using the Infinium HumanMethylation450 BeadChip. Table S4: distribution of the samples across the bead chips, detected CpGs and the corresponding call rate per sample. Table S5: reaction conditions and primer sequences of the bisulfite-PCRs. Table S6: reaction conditions and primer sequences of the SIRPH analysis. Table S7: statistical power of the twin study. Figure S1: pair-wise correlations for each pair of samples, calculated from approximately 480,000 CpGs. Figure S2: sample-independent Infinium methylation controls. Figure S3: sample-dependent Infinium methylation controls. Figure S4: pair-wise correlations for each pair of samples, including the reference dataset for whole-blood and buccal (27k), calculated from approximately 25,978 CpGs. Figure S5: mixing experiment with KG1a and K562 cells profiled on the Infinium HumanMethylation450 BeadChip. Figure S6: distribution of the correlation coefficients of the methylation values of the approximately 480,000 CpGs to the methylation values of the PTPN7 CpG (cg18384097). Figure S7: pair-wise correlations for each pair of samples after adjusting for cell type composition using the PTPN7 CpG (cg18384097). Figure S8: examples of methylation profiles generated using the deep bisulfite sequencing data of the APPL2, PPARGC1B, PHKG2 and PTPN7 amplicons. Figure S9: correlation plots in which the (unadjusted) Infinium 450K data of the validated CpGs are plotted against the (unadjusted) deep bisulfite sequencing (DBS) data for every sample separately. Figure S10: box-plot of the correlation coefficients calculated between the Infinium 450K data and the deep bisulfite sequencing (DBS) data of the validated CpGs for every individual sample. Figure S11: correlation plots of the (unadjusted) Infinium 450K data and the (unadjusted) deep bisulfite sequencing (DBS) data of the 17 discordant MZ twin pairs for each validated CpG separately. Figure S12: continuation of Figure S11. Figure S13: box-plot of the intra-pair differences in β-values of the 64 SNPs present on the Infinium HumanMethylation450 BeadChip before and after normalisation using internal controls and background subtraction by the GenomeStudio software.

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