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Updated: Jun 9, 2025

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
DNA methylation analysis to differentiate reference, breed, and parent-of-origin effects in the bovine pangenome era
Callum MacPhillamy1, Tong Chen1, Stefan Hiendleder1,2
1The Davies Research Centre, School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy SA 5371, Australia.
Background:
Most DNA methylation studies have used a single reference genome with little attention paid to the bias introduced due to the reference chosen. Reference genome artifacts and genetic variation, including single nucleotide polymorphisms (SNPs) and structural variants (SVs), can lead to differences in methylation sites (CpGs) between individuals of the same species. We analyzed whole-genome bisulfite sequencing data from the fetal liver of Angus (Bos taurus taurus), Brahman (Bos taurus indicus), and reciprocally crossed samples. Using reference genomes for each breed from the Bovine Pangenome Consortium, we investigated the influence of reference genome choice on the breed and parent-of-origin effects in methylome analyses.
Results:
Our findings revealed that ∼75% of CpG sites were shared between Angus and Brahman, ∼5% were breed specific, and ∼20% were unresolved. We demonstrated up to ∼2% quantification bias in global methylation when an incorrect reference genome was used. Furthermore, we found that SNPs impacted CpGs 13 times more than other autosomal sites (P < $5 \times {10}^{ - 324}$) and SVs contained 1.18 times (P < $5 \times {10}^{ - 324}$) more CpGs than non-SVs. We found a poor overlap between differentially methylated regions (DMRs) and differentially expressed genes (DEGs) and suggest that DMRs may be impacting enhancers that target these DEGs. DMRs overlapped with imprinted genes, of which 1, DGAT1, which is important for fat metabolism and weight gain, was found in the breed-specific and sire-of-origin comparisons.
Conclusions:
This work demonstrates the need to consider reference genome effects to explore genetic and epigenetic differences accurately and identify DMRs involved in controlling certain genes.
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