Abstract
Cytosine methylation patterns have not yet been thoroughly studied in horses. Here, we profile n = 333 samples from 42 horse tissue types at loci that are highly conserved between mammalian species using a custom array (HorvathMammalMethylChip40). Using the blood and liver tissues from horses, we develop five epigenetic aging clocks: a multi-tissue clock, a blood clock, a liver clock and two dual-species clocks that apply to both horses and humans. In addition, using blood methylation data from three additional equid species (plains zebra, Grevy’s zebras and Somali asses), we develop another clock that applies across all equid species. Castration does not significantly impact the epigenetic aging rate of blood or liver samples from horses. Methylation and RNA data from the same tissues define the relationship between methylation and RNA expression across horse tissues. We expect that the multi-tissue atlas will become a valuable resource.
Highlights
Cytosine methylation patterns have not yet been thoroughly studied in horses
The multi-tissue atlas involved 42 different tissues from N = 2 mares used in the equine Functional Annotation of Animal Genomes (FAANG) initiative[25]
A critical step toward crossing the species barrier was the employment of a mammalian DNA methylation array[41], which led to the acquisition of the most comprehensive epigenetic dataset of domestic horses far
Summary
Cytosine methylation patterns have not yet been thoroughly studied in horses. Here, we profile n = 333 samples from 42 horse tissue types at loci that are highly conserved between mammalian species using a custom array (HorvathMammalMethylChip[40]). Using the blood and liver tissues from horses, we develop five epigenetic aging clocks: a multi-tissue clock, a blood clock, a liver clock and two dual-species clocks that apply to both horses and humans. With the technical development of methylation arrays that profile large numbers of individual CpG positions in the genome, an opportunity arose to develop a highly accurate age-estimator for all human tissues[4,5,6]. The human pan-tissue clock combines the weighted average of methylation levels of 353 CpGs into an age estimate referred to as DNAm age or epigenetic age[7]. To study the relationship between expression levels (mRNA) and methylation across tissue types, we generated DNA methylation profiles from across 42 horse tissues for which RNA-seq profiles were available
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