AIMS: Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes. MATERIALS & METHODS: We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit. RESULTS: We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, β < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, β < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs. CONCLUSION: Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.
AIMS: Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes. MATERIALS & METHODS: We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit. RESULTS: We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, β < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, β < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs. CONCLUSION: Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.
Authors: Shusuke Numata; Tianzhang Ye; Thomas M Hyde; Xavier Guitart-Navarro; Ran Tao; Michael Wininger; Carlo Colantuoni; Daniel R Weinberger; Joel E Kleinman; Barbara K Lipska Journal: Am J Hum Genet Date: 2012-02-02 Impact factor: 11.025
Authors: Boris Novakovic; Lavinia Gordon; Nicholas C Wong; Ashley Moffett; Ursula Manuelpillai; Jeffrey M Craig; Andrew Sharkey; Richard Saffery Journal: Mol Hum Reprod Date: 2011-02-02 Impact factor: 4.025
Authors: Julia E Rager; Rebecca N Bauer; Loretta L Müller; Lisa Smeester; Johnny L Carson; Luisa E Brighton; Rebecca C Fry; Ilona Jaspers Journal: Am J Physiol Lung Cell Mol Physiol Date: 2013-07-05 Impact factor: 5.464
Authors: Joseph L McClay; Karolina A Aberg; Shaunna L Clark; Srilaxmi Nerella; Gaurav Kumar; Lin Y Xie; Alexandra D Hudson; Aki Harada; Christina M Hultman; Patrik K E Magnusson; Patrick F Sullivan; Edwin J C G Van Den Oord Journal: Hum Mol Genet Date: 2013-10-16 Impact factor: 6.150
Authors: Karolina A Aberg; Joseph L McClay; Srilaxmi Nerella; Lin Y Xie; Shaunna L Clark; Alexandra D Hudson; Jozsef Bukszár; Daniel Adkins; Christina M Hultman; Patrick F Sullivan; Patrik K E Magnusson; Edwin J C G van den Oord Journal: Epigenomics Date: 2012-12 Impact factor: 4.778