MethHaplo

MethHaplo identifies DNA methylation haplotype regions by integrating allele-specific DNA methylation and single nucleotide polymorphism (SNP) data from whole-genome bisulfite sequencing (WGBS) to enable haplotype-level analysis of epigenetic variation affecting gene expression, histone modification, and three-dimensional chromosome structure.


Key Features:

  • Integration of Epigenetic and Genetic Data: Combines allele-specific DNA methylation patterns with SNPs from WGBS to identify methylation haplotypes and recover longer haplotypes than SNPs alone.
  • Incorporation of Hi-C Data: Integrates high-throughput chromosome conformation capture (Hi-C) data to extend identified haplotype regions and relate methylation haplotypes to three-dimensional chromatin organization.
  • Methylation Haplotype Construction across Cell Lines: Constructs detailed methylation haplotypes across various cell lines to support analyses of parental inheritance-related diseases, hybrid vigor in agriculture, and associations with therapeutic responses and disease mechanisms.

Scientific Applications:

  • Genetic Research: Aids understanding of the genetic basis of complex traits and diseases by identifying longer haplotype regions linking SNPs and methylation.
  • Epigenomics: Illuminates the role of DNA methylation in gene regulation and epigenetic modification at the haplotype level.
  • Chromatin Architecture Studies: Enables analysis of how methylation haplotypes correlate with three-dimensional chromatin organization using Hi-C integration.
  • Disease Research: Supports investigation of parental inheritance-related diseases and therapeutic response mechanisms through haplotype-resolved methylation patterns.
  • Agricultural Genetics: Facilitates study of hybrid vigor and epigenetic contributions to phenotypic outcomes in agricultural species.

Methodology:

Combines allele-specific DNA methylation calls with SNP information derived from WGBS and can optionally incorporate Hi-C data to identify extended DNA methylation haplotype regions.

Topics

Details

Tool Type:
command-line tool
Programming Languages:
C, C++, Perl, Shell, Python
Added:
1/18/2021
Last Updated:
2/22/2021

Operations

Publications

Zhou Q, Wang Z, Li J, Sung W, Li G. MethHaplo: combining allele-specific DNA methylation and SNPs for haplotype region identification. BMC Bioinformatics. 2020;21(1). doi:10.1186/s12859-020-03798-7. PMID:33045983. PMCID:PMC7552496.

PMID: 33045983
PMCID: PMC7552496
Funding: - National Natural Science Foundation of China: 31771402, 31970590 - Fundamental Research Funds for the Central Universities: 2662017PY116 - National Key Research and Development Program of China: 2018YFC1604000

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