{"doi":"10.1101/gr.222885.117","title":"Genome-wide DNA methylation profiling using the methylation-dependent restriction enzyme LpnPI","abstract":"<jats:p>DNA methylation is a well-known epigenetic modification that plays a crucial role in gene regulation, but genome-wide analysis of DNA methylation remains technically challenging and costly. DNA methylation-dependent restriction enzymes can be used to restrict CpG methylation analysis to methylated regions of the genome only, which significantly reduces the required sequencing depth and simplifies subsequent bioinformatics analysis. Unfortunately, this approach has been hampered by complete digestion of DNA in CpG methylation-dense regions, resulting in fragments that are too small for accurate mapping. Here, we show that the activity of DNA methylation-dependent enzyme, LpnPI, is blocked by a fragment size smaller than 32 bp. This unique property prevents complete digestion of methylation-dense DNA and allows accurate genome-wide analysis of CpG methylation at single-nucleotide resolution. Methylated DNA sequencing (MeD-seq) of LpnPI digested fragments revealed highly reproducible genome-wide CpG methylation profiles for &gt;50% of all potentially methylated CpGs, at a sequencing depth less than one-tenth required for whole-genome bisulfite sequencing (WGBS). MeD-seq identified a high number of patient and tissue-specific differential methylated regions (DMRs) and revealed that patient-specific DMRs observed in both blood and buccal samples predict DNA methylation in other tissues and organs. We also observed highly variable DNA methylation at gene promoters on the inactive X Chromosome, indicating tissue-specific and interpatient-specific escape of X Chromosome inactivation. These findings highlight the potential of MeD-seq for high-throughput epigenetic profiling.</jats:p>","journal":"Genome Research","year":2018,"id":38064,"datarank":1.822342621538711,"base_score":4.605170185988092,"endowment":4.605170185988092,"self_citation_contribution":0.6907755278982138,"citation_network_contribution":1.1315670936404973,"self_endowment_contribution":0.6907755278982138,"citer_contribution":1.1315670936404973,"corpus_percentile":null,"corpus_rank":null,"citation_count":99,"citer_count":49,"citers_with_citation_signal":42,"citers_with_endowment":42,"datacite_reuse_total":17,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":189451,"name":"Joachim 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Boers","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":4.605170185988092,"endowment":4.605170185988092,"datacite_reuse_total":17,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"29222086","pmcid":"PMC5749185","openalex_id":"https://openalex.org/W2775229688","authors":[],"funders":[{"funder_name":"European Research Council","grant_id":"","title":null},{"funder_name":"NWO 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and DNA Methylation","Cancer-related gene regulation","RNA modifications and cancer","Biology","Medicine","Chromosomes, Human, X","CpG Islands","DNA Methylation","Deoxyribonuclease I","Epigenesis, Genetic","Female","Genome-Wide Association Study","Humans","X Chromosome Inactivation"],"mesh_terms":["Deoxyribonuclease I","Female","Humans","CpG Islands","DNA Methylation","Chromosomes, Human, X","Epigenesis, Genetic","X Chromosome Inactivation","Genome-Wide Association Study"],"keywords":["DNA methylation","Methylated DNA immunoprecipitation","Biology","Illumina Methylation Assay","Differentially methylated regions","CpG site","RNA-Directed DNA Methylation","Methylation","Bisulfite sequencing","Epigenetics","Genetics","Epigenomics","Epigenetics of physical exercise","Restriction enzyme","Genome","Molecular biology","DNA","Gene","Gene expression"],"sdg_mappings":[],"linked_datasets":[{"doi":"10.6084/m9.figshare.16841316.v1","title":"Additional file 5 of High-throughput and affordable 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