Abstract
Genetic polymorphisms can shape the global landscape of DNA methylation, by either changing substrates for DNA methyltransferases or altering the DNA binding affinity of cis-regulatory proteins. The interactions between CpG methylation and genetic polymorphisms have been previously investigated by methylation quantitative trait loci (mQTL) and allele-specific methylation (ASM) analysis. However, it remains unclear whether these approaches can effectively and comprehensively identify all genetic variants that contribute to the inter-individual variation of DNA methylation levels. Here we used three independent approaches to systematically investigate the influence of genetic polymorphisms on variability in DNA methylation by characterizing the methylation state of 96 whole blood samples in 52 parent-child trios from 22 nuclear pedigrees. We performed targeted bisulfite sequencing with padlock probes to quantify the absolute DNA methylation levels at a set of 411,800 CpG sites in the human genome. With mid-parent offspring analysis (MPO), we identified 10,593 CpG sites that exhibited heritable methylation patterns, among which 70.1% were SNPs directly present in methylated CpG dinucleotides. We determined the mQTL analysis identified 49.9% of heritable CpG sites for which regulation occurred in a distal cis-regulatory manner, and that ASM analysis was only able to identify 5%. Finally, we identified hundreds of clusters in the human genome for which the degree of variation of CpG methylation, as opposed to whether or not CpG sites were methylated, was associated with genetic polymorphisms, supporting a recent hypothesis on the genetic influence of phenotypic plasticity. These results show that cis-regulatory SNPs identified by mQTL do not comprise the full extent of heritable CpG methylation, and that ASM appears overall unreliable. Overall, the extent of genome-methylome interactions is well beyond what is detectible with the commonly used mQTL and ASM approaches, and is likely to include effects on plasticity.
Highlights
DNA methylation represents an important layer of epigenetic regulation on the transcriptional activity of the human genome and plays a crucial role in genomic imprinting, embryonic development and determination of cell type
While several samples came from individuals with schizophrenia, the sample size here was too small to perform any significant association tests between disease state and either genetic or methylation factors; we focused on treating methylation itself as a quantitative trait and investigating its relation to individual genetic variants
Association mapping of molecular phenotypes such as gene expression, DNA methylation, or chromatin accessibility as quantitative traits has revealed how genetic variants contribute to inter-individual variability and provided additional insights into the modulation of disease susceptibility [1,20,31,32,33,34]
Summary
DNA methylation represents an important layer of epigenetic regulation on the transcriptional activity of the human genome and plays a crucial role in genomic imprinting, embryonic development and determination of cell type. Accumulating evidence suggests that DNA methylation patterns, rather than being similar within members of the same species, vary from one individual to another [1,2,3] due to both genetic and environmental factors [4,5]. This variability could potentially explain why certain phenotypic outcomes manifest differently across individuals of the same species, including in terms of the susceptibility to and treatability of many human diseases [6,7]. We performed mQTL and ASM analysis on the same samples, and investigated the capability of each method to identify the genetic contribution to inter-sample methylation variability
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