Evidence That Three Classes of Methylomes Specific for Stem, Somatic and Transformed Cells Are Set by Three Independent Mechanisms (Methyl-Seq)

Whole genome-bisulfite sequencing has revealed that methylomes differ dramatically in a cell type-specific manner. However, the global mechanisms of maintenance of DNA methylation patterns and their functional consequences are not clear. Using a combination of novel haplotype-resolved methylomes and publicly available data, we show that three distinct classes of methylomes that differ by the proportion of partially and highly methylated domains are characteristic of stem and progenitor, somatic and transformed cells. We provide evidence that three mechanisms can account for most of the differences between these three classes of methylomes. The first, protection of promoters and cis-acting regulatory elements from DNA methylation by DNA-binding proteins, keeps regulatory elements unmethylated. The second, DNA replication-associated maintenance of DNA methylation, is highly efficient in stem cells, moderately efficient in somatic cells, and very inefficient in transformed cells, and sets variable basal levels of methylation characteristic of the partially methylated domains of each cell type. The third, transcriptional elongation-associated gene-body DNA methylation is responsible for the formation of highly methylated domains in somatic and transformed cells. We show that partitioning of the genome into partially and highly methylated domains is associated with different mechanisms of gene silencing. A methylome analysis was performed on self-generated data from basophilic erythroblasts (“BasoE”, as described in detail below, with raw data files included), as well as from previously published cell lines and primary tissues (only processed data included here): Processed methylation calls were downloaded and filtered to include only CpG dinucleotides with at least 10x read coverage on the autosomes for the following cell lines: H1 hESC (from ftp://ftpuser3:[e-mail]/mc/h1_c_basecalls.tar.gz, based on GSE16256), IMR90 (from ftp://ftpuser3:[e-mail]/mc/imr90_c_basecalls.tar.gz, based on GSE16256), HepG2 (from https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSM1204463&format=file&file=GSM1204463_BiSeq_cpgMethylation_BioSam_1500_HepG2_304072.BiSeq.bed, based on GSM1204463), hematopoietic stem/progenitor cells (HSPC; from http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/FractionalMethylation_bigwig/E050_WGBS_FractionalMethylation.bigwig and http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/ReadCoverage_bigwig/E050_WGBS_ReadCoverage.bigwig, based on GSM916052), ganglionic neurospheres (GNeurosphere, from http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/FractionalMethylation_bigwig/E054_WGBS_FractionalMethylation.bigwig and http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/ReadCoverage_bigwig/E054_WGBS_ReadCoverage.bigwig, based on GSM1127055), pancreas (from http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/FractionalMethylation_bigwig/E098_WGBS_FractionalMethylation.bigwig and http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/ReadCoverage_bigwig/E098_WGBS_ReadCoverage.bigwig, based on GSM983651), and adult liver from http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/FractionalMethylation_bigwig/E066_WGBS_FractionalMethylation.bigwig and http://egg2.wustl.edu/roadmap/data/byDataType/dnamethylation/WGBS/ReadCoverage_bigwig/E066_WGBS_ReadCoverage.bigwig, based on GSM1058027). For K562 cells, raw data was retrieved from ftp://ftp-trace.ncbi.nlm.nih.gov/sra/sra-instant/reads/ByExp/sra/SRX/SRX840/SRX840166/SRR1754892/SRR1754892.sra (GSM1583563) and processed using Bismarck, followed by filtering on HCG loci with at least 10x coverage.