Evaluating genome-wide DNA methylation changes in mice by Methylation Specific Digital Karyotyping

Abstract

Abstract Background The study of genome-wide DNA methylation changes has become more accessible with the development of various array-based technologies though when studying species other than human the choice of applications are limited and not always within reach. In this study, we adapted and tested the applicability of Methylation Specific Digital Karyotyping (MSDK), a non-array based method, for the prospective analysis of epigenetic changes after perinatal nutritional modifications in a mouse model of allergic airway disease. MSDK is a sequenced based method that allows a comprehensive and unbiased methylation profiling. The method generates 21 base pairs long sequence tags derived from specific locations in the genome. The resulting tag frequencies determine in a quantitative manner the methylation level of the corresponding loci. Results Genomic DNA from whole lung was isolated and subjected to MSDK analysis using the methylation-sensitive enzyme Not I as the mapping enzyme and Nla III as the fragmenting enzyme. In a pair wise comparison of the generated mouse MSDK libraries we identified 158 loci that are significantly differentially methylated (P-value = 0.05) after perinatal dietary changes in our mouse model. Quantitative methylation specific PCR and sequence analysis of bisulfate modified genomic DNA confirmed changes in methylation at specific loci. Differences in genomic MSDK tag counts for a selected set of genes, correlated well with changes in transcription levels as measured by real-time PCR. Furthermore serial analysis of gene expression profiling demonstrated a dramatic difference in expressed transcripts in mice exposed to perinatal nutritional changes. Conclusion The genome-wide methylation survey applied in this study allowed for an unbiased methylation profiling revealing subtle changes in DNA methylation in mice maternally exposed to dietary changes in methyl-donor content. The MSDK method is applicable for mouse models of complex human diseases in a mixed cell population and might be a valuable technology to determine whether environmental exposures can lead to epigenetic changes.