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Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation.

ABSTRACT: Heterogeneity of DNA methylation status among alleles is observed in various cell types and is involved in epigenetic gene regulation and cancer biology. However, the individual methylation profile within each allele has not yet been examined at the whole-genome level. In the present study, we applied linkage disequilibrium analysis to the DNA methylation data obtained from whole-genome bisulfite sequencing studies in mouse germline and other types of cells. We found that the methylation status of 2 consecutive CpG sites showed deviation from equilibrium frequency toward concordant linkage (both methylated or both unmethylated) in germline cells. In the imprinting loci where methylation of constituent alleles is known, our analysis detected the deviation toward the concordant linkage as expected. In addition, we applied this analysis to the transitional zone between methylated and unmethylated regions and to the cells undergoing epigenetic reprogramming. In both cases, deviation to the concordant-linked alleles was conspicuous, indicating that the methylation pattern is not random but rather concordant within each allele. These results will provide the key to understanding the mechanism underlying allelic heterogeneity.

SUBMITTER: Saito D

PROVIDER: S-EPMC4844222 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation.

Saito Daisuke D Suyama Mikita M

Epigenetics 20150101 12

Heterogeneity of DNA methylation status among alleles is observed in various cell types and is involved in epigenetic gene regulation and cancer biology. However, the individual methylation profile within each allele has not yet been examined at the whole-genome level. In the present study, we applied linkage disequilibrium analysis to the DNA methylation data obtained from whole-genome bisulfite sequencing studies in mouse germline and other types of cells. We found that the methylation status ...[more]

PMID: 26575360

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Project description:BackgroundCompared to medium-density single nucleotide polymorphism (SNP) data, high-density SNP data contain abundant genetic variants and provide more information for the genetic evaluation of livestock, but it has been shown that they do not confer any advantage for genomic prediction and heritability estimation. One possible reason is the uneven distribution of the linkage disequilibrium (LD) along the genome, i.e., LD heterogeneity among regions. The aim of this study was to effectively use genome-wide SNP data for genomic prediction and heritability estimation by using models that control LD heterogeneity among regions.MethodsThe LD-adjusted kinship (LDAK) and LD-stratified multicomponent (LDS) models were used to control LD heterogeneity among regions and were compared with the classical model that has no such control. Simulated and real traits of 2000 dairy cattle individuals with imputed high-density (770K) SNP data were used. Five types of phenotypes were simulated, which were controlled by very strongly, strongly, moderately, weakly and very weakly tagged causal variants, respectively. The performances of the models with high- and medium-density (50K) panels were compared to verify that the models that controlled LD heterogeneity among regions were more effective with high-density data.ResultsCompared to the medium-density panel, the use of the high-density panel did not improve and even decreased prediction accuracies and heritability estimates from the classical model for both simulated and real traits. Compared to the classical model, LDS effectively improved the accuracy of genomic predictions and unbiasedness of heritability estimates, regardless of the genetic architecture of the trait. LDAK applies only to traits that are mainly controlled by weakly tagged causal variants, but is still less effective than LDS for this type of trait. Compared with the classical model, LDS improved prediction accuracy by about 13% for simulated phenotypes and by 0.3 to ~ 10.7% for real traits with the high-density panel, and by ~ 1% for simulated phenotypes and by - 0.1 to ~ 6.9% for real traits with the medium-density panel.ConclusionsGrouping SNPs based on regional LD to construct the LD-stratified multicomponent model can effectively eliminate the adverse effects of LD heterogeneity among regions, and greatly improve the efficiency of high-density SNP data for genomic prediction and heritability estimation.

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Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation.

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Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation.

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