Examining the extent of environmental contributions toward DNA methylation and phenotypic variation

Pacht, Emory; Murdoch, Brenda M.; McKay, Stephanie

doi:10.1093/af/vfab056

Cited by 8 publications

(4 citation statements)

References 30 publications

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“…Age‐related decline in the accuracy of traditional ageing methods is common in all three study species (Foley et al., 2021; Harshyne et al., 1998; Stevens & Houston, 1989; Storm et al., 2014). External factors such as disease (e.g., Bobak et al., 2022), inbreeding (Larison et al., 2021) and stress (Pacht et al., 2021; Zannas et al., 2015) can also influence biological ageing in the form of DNAm and could also be contributing uncertainty to the model.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic clocks, sex markers and age‐class diagnostics in three harvested large mammals

Czajka,

Northrup,

Jones

et al. 2024

Molecular Ecology Resources

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The development of epigenetic clocks, or the DNA methylation‐based inference of age, is an emerging tool for ageing in free ranging populations. In this study, we developed epigenetic clocks for three species of large mammals that are the focus of extensive management throughout their range in North America: white‐tailed deer, black bear and mountain goat. We quantified differential DNA methylation patterns at over 30,000 cytosine‐guanine sites (CpGs) from tissue samples of all three species (black bear n = 49; white‐tailed deer n = 47; mountain goat n = 45). We used a penalized regression model (elastic net) to build explanatory (black bear r = .95; white‐tailed deer r = .99; mountain goat r = .97) and robust (black bear Median Absolute Error or MAE = 1.33; white‐tailed deer MAE = 0.29; mountain goat MAE = 0.61) models of age or clocks. We also characterized individual CpG sites within each species that demonstrated clear differences in methylation levels between age classes and sex, which can be used to develop a suite of accessible diagnostic markers. This tool has the potential to contribute to wildlife monitoring by providing easily obtainable representations of age structure in managed populations.

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Section: Discussionmentioning

confidence: 99%

Epigenetic clocks, sex markers and age‐class diagnostics in three harvested large mammals

Czajka,

Northrup,

Jones

et al. 2024

Molecular Ecology Resources

View full text Add to dashboard Cite

show abstract

“…Age-related decline in the accuracy of traditional aging methods is common in all three study species (Stevens & Houston, 1989;Harshyne et al, 1998;Storm et al, 2014;Foley et al, 2021). External factors like disease (e.g., Bobak et al, 2022), inbreeding (Larison et al, 2021) and stress (Zannas et al, 2015;Pacht et al, 2021) can also influence biological aging in the form of DNAm and could also be contributing uncertainty to the model.…”

Section: Discussionmentioning

confidence: 99%

“…The majority of non-human epigenetic aging studies have focused on captive model species, leading to a gap in knowledge of wild populations of large mammals (Tangili et al, 2023). Environmental factors such as diet and stress can impact DNA methylation and aging rates (Tangili et al, 2023; Pacht et al, 2021), so the results from captive species might not be generalizable to wild populations, which experience more environmental variability (Tangili et al, 2023). In addition, large and small mammals are known to exhibit vastly different life histories and aging rates, potentially impacting the rate of DNAm (Austad, 1997; Tangili et al, 2023) and likely increasing the variance of the universal DNA methylation clock.…”

Section: Discussionmentioning

confidence: 99%

“…The copyright holder for this preprint this version posted November 23, 2023. ; https://doi.org/10. 1101/2023.11.22.568330 doi: bioRxiv preprint rates (Tangili et al, 2023;Pacht et al, 2021), so the results from captive species might not be generalizable to wild populations, which experience more environmental variability (Tangili et al, 2023). In addition, large and small mammals are known to exhibit vastly different life histories and aging rates, potentially impacting the rate of DNAm (Austad, 1997;Tangili et al, 2023) and likely increasing the variance of the universal DNA methylation clock.…”

Section: Discussionmentioning

confidence: 99%

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Epigenetic clocks, sex markers, and age-class diagnostics in three harvested large mammals

Czajka,

Northrup,

Jones

et al. 2023

Preprint

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The development of epigenetic clocks, or the DNA methylation-based inference of age, is an emerging tool for ageing in free ranging populations. In this study, we developed epigenetic clocks for three species of large mammals that are the focus of extensive management throughout their range: white-tailed deer, black bear, and mountain goat. We quantified differential DNA methylation patterns at over 30,000 cytosine-guanine sites (CpGs) from tissue samples (N=141) of all three species. We used a penalized regression model (elastic net) to build highly explanatory (black bearr= 0.95; white-tailed deerr= 0.99; mountain goatr= 0.97) and robust (black bear Median Absolute Error or MAE = 1.33; white-tailed deer MAE = 0.29; mountain goat MAE = 0.61) models of age (clocks). We also characterized individual CpG sites within each species that demonstrated clear differences in methylation levels between age classes and sex, which can be used to develop a suite of accessible diagnostic markers. Our results demonstrate promising tools for the large-scale estimation of age in wild animals, which have the potential to contribute to wildlife monitoring by providing easily obtainable representations of age structure in managed populations.

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Epigenetics in Aquaculture

Piferrer¹

2023

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Examining the extent of environmental contributions toward DNA methylation and phenotypic variation

Cited by 8 publications

References 30 publications

Epigenetic clocks, sex markers and age‐class diagnostics in three harvested large mammals

Epigenetic clocks, sex markers and age‐class diagnostics in three harvested large mammals

Epigenetic clocks, sex markers, and age-class diagnostics in three harvested large mammals

Epigenetics in Aquaculture

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