Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12859-020-03798-7
Title: MethHaplo: Combining allele-specific DNA methylation and SNPs for haplotype region identification
Authors: Zhou, Q.
Wang, Z.
Li, J.
Sung, W.-K. 
Li, G.
Keywords: Allele-specific DNA methylation
Allele-specific gene expression
CTCF
DNA methylation
SNP
Issue Date: 2020
Publisher: BioMed Central Ltd
Citation: Zhou, Q., Wang, Z., Li, J., Sung, W.-K., Li, G. (2020). MethHaplo: Combining allele-specific DNA methylation and SNPs for haplotype region identification. BMC Bioinformatics 21 (1) : 451. ScholarBank@NUS Repository. https://doi.org/10.1186/s12859-020-03798-7
Rights: Attribution 4.0 International
Abstract: Background: DNA methylation is an important epigenetic modification that plays a critical role in most eukaryotic organisms. Parental alleles in haploid genomes may exhibit different methylation patterns, which can lead to different phenotypes and even different therapeutic and drug responses to diseases. However, to our knowledge, no software is available for the identification of DNA methylation haplotype regions with combined allele-specific DNA methylation, single nucleotide polymorphisms (SNPs) and high-throughput chromosome conformation capture (Hi-C) data. Results: In this paper, we developed a new method, MethHaplo, that identify DNA methylation haplotype regions with allele-specific DNA methylation and SNPs from whole-genome bisulfite sequencing (WGBS) data. Our results showed that methylation haplotype regions were ten times longer than haplotypes with SNPs only. When we integrate WGBS and Hi-C data, MethHaplo could call even longer haplotypes. Conclusions: This study illustrates the usefulness of methylation haplotypes. By constructing methylation haplotypes for various cell lines, we provide a clearer picture of the effect of DNA methylation on gene expression, histone modification and three-dimensional chromosome structure at the haplotype level. Our method could benefit the study of parental inheritance-related disease and hybrid vigor in agriculture. © 2020 The Author(s).
Source Title: BMC Bioinformatics
URI: https://scholarbank.nus.edu.sg/handle/10635/199448
ISSN: 14712105
DOI: 10.1186/s12859-020-03798-7
Rights: Attribution 4.0 International
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