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Updated: Nov 4, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Optimal sample size for calibrating DNA methylation age estimators.

Benjamin Mayne¹, Oliver Berry¹, Simon Jarman²

¹Environomics Future Science Platform, Indian Ocean Marine Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Crawley, WA, Australia.

Molecular Ecology Resources

|May 30, 2021

Summary

This summary is machine-generated.

Determining wildlife age accurately is crucial for conservation. This study recommends a minimum of 70, ideally 134+, individuals for calibrating DNA methylation age estimation models in wild animals.

Keywords:

DNA methylation age estimation epigenetic clock sample size wildlife

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Area of Science:

Wildlife biology
Genetics
Conservation science

Background:

Age is critical for wildlife management, impacting extinction risk, invasive species control, and sustainable harvesting.
DNA methylation analysis offers a method for vertebrate age determination.
Obtaining wild animals with known ages for calibrating epigenetic clocks is challenging.

Purpose of the Study:

To determine the optimal sample size for developing accurate epigenetic age estimation models.
To assess the extrapolation capabilities of age estimation models beyond the calibration age range.

Main Methods:

Utilized Monte Carlo simulations to model age estimation using elastic net regression on cytosine-phosphate-guanine methylation data.
Investigated the impact of sample size on model accuracy and precision.

Main Results:

A minimum of 70 individuals is recommended for model calibration.
An ideal sample size of 134 or more individuals ensures accurate and precise age estimation models.
Provided insights into the extrapolation limits of developed age models.

Conclusions:

The study offers guidance on designing robust epigenetic age estimation models for wildlife.
Findings assist researchers in evaluating model adequacy for critical population assessments.
Optimizing sample size is key for reliable wildlife age determination using DNA methylation.