Research Article Identification of methylated regions with peak search based on Poisson model from massively parallel methylated DNA immunoprecipitation-sequencing data DNA methylation is one of the most important epigenetic modification types, which plays a critical role in gene expression. High efficient surveying of whole genome DNA methylation has been aims of many researchers for long. Recently, the rapidly developed massively parallel DNA-sequencing technologies open the floodgates to vast volumes of sequence data, enabling a paradigm shift in profiling the whole genome methylation. Here, we describe a strategy, combining methylated DNA immunoprecipitation sequencing with peak search to identify methylated regions on a whole-genome scale. Massively parallel methylated DNA immunoprecipitation sequencing combined with methylation DNA immunoprecipitation was adopted to obtain methylated DNA sequence data from human leukemia cell line K562, and the methylated regions were identified by peak search based on Poison model. From our result, 140 958 non-over- lapping methylated regions have been identified in the whole genome. Also, the cred- ibility of result has been proved by its strong correlation with bisulfite-sequencing data (Pearson R 2 5 0.92). It suggests that this method provides a reliable and high-throughput strategy for whole genome methylation identification. Keywords: K562 / Methylated DNA immunoprecipitation sequencing / Methylation / Peak search DOI 10.1002/elps.201000326 1 Introduction DNA methylation is a major epigenetic modification, which can be inherited through cell division [1]. In human, DNA methylation occurs predominantly at the cytosine within CpG dinucleotides by addition of a methyl group to the position 5 of cytosine pyrimidine ring, and it plays a critical role in gene expression, gene imprinting, X chromosome inactive and carcinogenesis [2–6]. However, how DNA methylation effects on gene expression, carcinogenesis and other biological events on a genome scale is still not well understood. Unbiased and cost-efficient whole-genome methylation survey strategies would then be a key to answer this question. Nowadays, three techniques of DNA treatment have been typically employed in DNA methylation detection, (i) bisulfite treatment, (ii) methylation-sensitive restriction enzyme treatment, (iii) methylated DNA enrichment. These techni- ques already had been combined with PCR, electrophoresis and microarray for methylation analysis for a long while [7–9]. Recently, many studies combining these techniques with next generation sequencing for large-scale methylation profiling have been reported [10–14]. Among those studies, bisulfite-sequencing, regarded as the most direct strategy for methylation analysis, could provide a single base solution of DNA methylation analysis [10]. However, bisulfite-sequen- cing requires a mass of sequencing throughput and high cost when being applied to large genome or multiple biological samples [15]. Methylation-sensitive restriction enzymes combined with next generation sequencing could work well in detecting methylation pattern of enzymes restriction recognition sites [11, 12]. But it would meet problems with regions where limited recognition sites were found. Besides, potentially incomplete digestion may cause false positives. The third technique, methylated DNA enrichment, has recently been reported to detect DNA methylation, which employs antibody against 5-methylcytosine or methyl- binding domain proteins to capture methylated DNA and Yao Yang 1,2 Wei Wang 1,2 Yanqiang Li 1,2 Jing Tu 1,2 Yunfei Bai 1,2 Pengfeng Xiao 1,2 Dingdong Zhang 1,3 Zuhong Lu 1,2,4 1 State Key Laboratory of Bioelectronics, Southeast University, Nanjing, P. R. China 2 School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China 3 School of Animal Science and Technology, Jinling Institute of Technology, Nanjing, P. R. China 4 Research Center for Learning Science, Southeast University, Nanjing, P. R. China Received June 17, 2010 Revised August 8, 2010 Accepted August 9, 2010 Abbreviations: ACTB, Beta-actin; CpG, Cytosine-phosphate- Guanine; CpGi, CpG island; FDR, false discovery rate; MeDIP, methylated DNA immunoprecipitation; TES, transcription end site; TSS, transcription start site Correspondence: Professor Zuhong Lu, State Key of Laboratory of Bioelectronics, Southeast University, Nanjing 210096, P. R. China E-mail: zhlu@seu.edu.cn Fax: 186-25-83793779 & 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.electrophoresis-journal.com Electrophoresis 2010, 31, 3537–3544 3537