Designing epigenetic clocks for wildlife research

The potential applications of epigenetic clocks are expanding in wildlife conservation and management. The pace at which they are being adopted highlights the need for field-specific design best practices. Epigenetic clocks were originally developed for human studies, presenting challenges for their adoption in wildlife research. Most notably, the estimated ages of sampled wildlife can be unreliable, and sampling restrictions limit the number and variety of available samples, which can reduce the accuracy of epigenetic clocks for wildlife. In this article, we present a detailed workflow for designing, validating, and applying wildlife epigenetic clocks in a way that accounts for sampling constraints. We provide recommendations for two main applications of wildlife epigenetic clocks: estimating unknown ages and assessing cumulative biological aging. Our simulations and analyses, applied to an extensive polar bear dataset from across the Canadian Arctic, demonstrate that accurate epigenet..., We compiled an extensive DNA methylation dataset from polar bears across the Canadian Arctic to assess whether sampling biases, data pre-processing, and validation influence wildlife clock performance. Our dataset includes DNA from 10 distinct subpopulations, each with different proportions of blood, skin, and muscle tissue, from male and female bears, and representing ages across the typical lifespan of a wild polar bear from age 0 to 30.
Scripts for processing the data are available from the GitHub repository https://github.com/ljnewediuk/how_to_clocks.git., # Designing epigenetic clocks for wildlife research

Dataset DOI: [10.5061/dryad.rxwdbrvmw](10.5061/dryad.rxwdbrvmw)

## Description of the data and file structure

The data include sample sheets, raw idat files, and quality-control information that can be used to process the DNA methylation data into a suitable format for developing epigenetic clocks.

### Files and variables

#### File: low\_qc\_positions.csv

**Description:** Low-quality detection p-values (high values indicate quality issues) for screening samples.

##### Variables

* position: chip position
* chip.ID.loc: chip IDs corresponding to the name of the position (corresponds to chip.ID_stripe columns from the sample sheets)
* detection_p: detection p-value; > 0.05 is high
* batch_no: Identifier ranging from 1-8

#### File: full\_sibs.txt

**Description:** Individual sample IDs (corresponding to sampleId in sample sheets) with siblings in the dataset. These individuals are normally excluded from clock design because of pot...,