# SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

## TL;DR

This paper introduces a new method to identify DNA methylation events that occur on only one allele using SNP data and MethylCap-seq.

## Contribution

A novel methodology combining MethylCap-seq and SNP data to detect monoallelic DNA methylation.

## Key findings

- Identified 80 genomic regions with monoallelic DNA methylation using 334 MethylCap-seq samples.
- 49 of these regions are in genic areas, with 25 linked to imprinting.
- Promoter regions were significantly enriched among the identified loci.

## Abstract

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post enrichment. Here, we present a new methodology that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Using the Hardy-Weinberg theorem for each SNP locus, it could be established whether the observed frequency of samples featured by biallelic methylation was lower than randomly expected. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation of the found loci was done using 14 whole-genome bisulfite sequencing data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, such as the ChIP-seq-based identification of monoallelic histone modifications.