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Updated: Jan 31, 2026

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Genome-wide differential DNA methylation in tropically adapted Creole cattle and their Iberian ancestors
N Sevane1, R Martínez2, M W Bruford1,3
1School of Biosciences, Cardiff University, Cathays Park, Cardiff, CF10 3AX, UK.
Abstract:
Enhancing climate resilience and sustainable production for animals in harsh environments are important goals for the livestock industry given the predicted impacts of climate change. Rapid adaptation to extreme climatic conditions has already been imposed on livestock species, including those exported after Columbus's arrival in the Americas. We compared the methylomes of two Creole cattle breeds living in tropical environments with their putative Spanish ancestors to understand the epigenetic mechanisms underlying rapid adaptation of a domestic species to a new and more physiologically challenging environment. Reduced representation bisulfite sequencing was used to assess differences in methylation in Creole and Spanish samples and revealed 334 differentially methylated regions using high stringency parameters (P-value <0.01, ≥4 CpGs within a distance of 200 bp, mean methylation difference >25%) annotated to 263 unique features. Gene ontology analysis revealed candidate genes involved in tropical adaptation processes, including genes differentially hyper- or hypomethylated above 80% in Creole samples displaying biological functions related to immune response (IRF6, PTGDR, FAM19A5, PGLYRP1), nervous system (GBX2, NKX2-8, RPGR), energy management (BTD), heat resistance (CYB561) and skin and coat attributes (LGR6). Our results entail that major environmental changes imposed on Creole cattle have had an impact on their methylomes measurable today, which affects genes implicated in important pathways for adaptation. Although further work is needed, this first characterization of methylation patterns driven by profound environmental change provides a valuable pointer for the identification of biomarkers of resilience for improved cattle performance and welfare under predicted climatic change models.
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