Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tissue-of-origin mapping from plasma DNA
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE79279 | GEO | 2017/02/19
SECONDARY ACCESSION(S): PRJNA315380
REPOSITORIES: GEO
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Project description:Adjacent CpG sites in mammalian genomes can be co-methylated owing to the processivity of methyltransferases or demethylases, yet discordant methylation patterns have also been observed, which are related to stochastic or uncoordinated molecular processes. We focused on a systematic search and investigation of regions in the full human genome that show highly coordinated methylation. We defined 147,888 blocks of tightly coupled CpG sites, called methylation haplotype blocks, after analysis of 61 whole-genome bisulfite sequencing data sets and validation with 101 reduced-representation bisulfite sequencing data sets and 637 methylation array data sets. Using a metric called methylation haplotype load, we performed tissue-specific methylation analysis at the block level. Subsets of informative blocks were further identified for deconvolution of heterogeneous samples. Finally, using methylation haplotypes we demonstrated quantitative estimation of tumor load and tissue-of-origin mapping in the circulating cell-free DNA of 59 patients with lung or colorectal cancer.
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Project description:Adjacent CpG sites in mammalian genomes tend to be co-methylated due to the processivity of enzymes responsible for adding or removing the methyl group. Yet discordant methylation patterns have also be observed, and found to be related to stochastic or uncoordinated molecular processes. Here we focused on a systematic search and investigation of regions in the human genome that exhibit highly coordinated methylation. By examining the co-methylation patterns of multiple adjacent CpG sites, termed methylation haplotypes, in single bisulfite sequencing reads, we applied a greedy-searching strategy to defined blocks of tightly coupled CpG sites, called Methylation Haplotype Blocks (MHBs), based on 53 sets of whole genome bisulfite sequencing (WGBS) data, including 43 published sets from human adult tissues, ESC and in vitro differentiated cell lines, as well as 10 sets from human adult tissues generated in this study. The MHBs were then further validated with 101 sets of RRBS ENCODE data, and 637 sets of Illumina 450k methylation array data from TCGA tumor and normal samples. Globally, MHBs are enriched in but only partially overlap with several well-known genomic features, including CpG islands, promoters, enhancers and VMRs. To perform quantitative analysis of the MHBs, we defined a metric called Methylation Haplotype Load (MHL), which is covered both average methylation level and methylation complexity and therefore more informative than average methylation level or Shannon entropy. Using a feature selection strategy, we identified a set of tissue-specific MHBs that cluster by developmental germ-layers. Interestingly, examination of these MHBs revealed two distinct mechanisms for fate commitment during development: epigenetic silencing of pluripotent genes, such as NANOG, for mesoderm induction; and epigenetic induction (or de-suppression) of lineage-specific factors for ectoderm commitment.
2017-02-19 | GSE79277 | GEO
Project description:Adjacent CpG sites in mammalian genomes tend to be co-methylated due to the processivity of enzymes responsible for adding or removing the methyl group. Yet discordant methylation patterns have also be observed, and found to be related to stochastic or uncoordinated molecular processes. Here we focused on a systematic search and investigation of regions in the human genome that exhibit highly coordinated methylation. By examining the co-methylation patterns of multiple adjacent CpG sites, termed methylation haplotypes, in single bisulfite sequencing reads, we applied a greedy-searching strategy to defined blocks of tightly coupled CpG sites, called Methylation Haplotype Blocks (MHBs), based on 53 sets of whole genome bisulfite sequencing (WGBS) data, including 43 published sets from human adult tissues, ESC and in vitro differentiated cell lines, as well as 10 sets from human adult tissues generated in this study. The MHBs were then further validated with 101 sets of RRBS ENCODE data, and 637 sets of Illumina 450k methylation array data from TCGA tumor and normal samples. Globally, MHBs are enriched in but only partially overlap with several well-known genomic features, including CpG islands, promoters, enhancers and VMRs. To perform quantitative analysis of the MHBs, we defined a metric called Methylation Haplotype Load (MHL), which is covered both average methylation level and methylation complexity and therefore more informative than average methylation level or Shannon entropy. Using a feature selection strategy, we identified a set of tissue-specific MHBs that cluster by developmental germ-layers. Interestingly, examination of these MHBs revealed two distinct mechanisms for fate commitment during development: epigenetic silencing of pluripotent genes, such as NANOG, for mesoderm induction; and epigenetic induction (or de-suppression) of lineage-specific factors for ectoderm commitment.
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Project description:Adjacent CpG sites in mammalian genomes tend to be co-methylated due to the processivity of enzymes responsible for adding or removing the methyl group. Yet discordant methylation patterns have also be observed, and found to be related to stochastic or uncoordinated molecular processes. Here we focused on a systematic search and investigation of regions in the human genome that exhibit highly coordinated methylation. By examining the co-methylation patterns of multiple adjacent CpG sites, termed methylation haplotypes, in single bisulfite sequencing reads, we applied a greedy-searching strategy to defined blocks of tightly coupled CpG sites, called Methylation Haplotype Blocks (MHBs), based on 53 sets of whole genome bisulfite sequencing (WGBS) data, including 43 published sets from human adult tissues, ESC and in vitro differentiated cell lines, as well as 10 sets from human adult tissues generated in this study. The MHBs were then further validated with 101 sets of RRBS ENCODE data, and 637 sets of Illumina 450k methylation array data from TCGA tumor and normal samples. Globally, MHBs are enriched in but only partially overlap with several well-known genomic features, including CpG islands, promoters, enhancers and VMRs. To perform quantitative analysis of the MHBs, we defined a metric called Methylation Haplotype Load (MHL), which is covered both average methylation level and methylation complexity and therefore more informative than average methylation level or Shannon entropy. Using a feature selection strategy, we identified a set of tissue-specific MHBs that cluster by developmental germ-layers. Interestingly, examination of these MHBs revealed two distinct mechanisms for fate commitment during development: epigenetic silencing of pluripotent genes, such as NANOG, for mesoderm induction; and epigenetic induction (or de-suppression) of lineage-specific factors for ectoderm commitment.
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