DNA Methylation Microarray for population genetics

Overview

CD Genomics offers advanced DNA Methylation Microarray services to uncover epigenetic variation across large populations. This method is ideal for population-scale studies aiming to investigate epigenetic diversity, population structure, environmentally induced changes, and transgenerational epigenetic inheritance. Leveraging optimised probe design and robust hybridisation chemistry, along with streamlined data processing pipelines, we deliver accurate and reproducible methylation data to support research in population genetics, evolutionary epigenomics, and environmental adaptation.

We support two widely used high-density array platforms to meet different study needs:

EPIC 935K arrays, covering over 935,000 CpG sites across promoters, enhancers, CpG islands, and gene bodies—ideal for comprehensive epigenome-wide association studies (EWAS) and regulatory region profiling.
Infinium 270K arrays, targeting a focused set of high-value CpG loci, are well-suited for cost-effective, high-throughput screening in large population cohorts.

What is DNA Methylation Microarray for population genetics?

DNA Methylation Microarray is a targeted, high-throughput platform that enables rapid and cost-effective detection of epigenetic variation—especially DNA methylation patterns—across large populations. This approach is particularly advantageous for population-scale studies, facilitating efficient exploration of epigenetic diversity, structure, and evolutionary dynamics. By capturing both environmentally responsive and potentially heritable methylation marks, DNA methylation microarrays support research in epigenetic regulation, environmental adaptation, transgenerational inheritance, and population-level responses to ecological pressures, providing a scalable and cost-effective solution for modern population epigenetics.

DNA Methylation Microarray for Population Genetics pipeline. (Sahoo, et al. 2024)

Sequencing Platforms

NextSeq 500

Illumina NovaSeq

PacBio Sequel II

Workflow of DNA Methylation Microarray for Population Genetics

Streamlined Workflow for DNA Methylation Microarray Services： Our DNA Methylation Microarray service is built on a refined and efficient workflow, designed for large-scale epigenetic studies. The standard pipeline includes:

Sample preparation: from DNA extraction to bisulfite conversion or methylation enrichment, depending on array type.
Fluorescent labelling and hybridisation: labelled DNA is hybridised to high-density methylation arrays for comprehensive CpG site interrogation.
Rigorous quality control: applied throughout to ensure signal consistency, data integrity, and cross-sample comparability.
Bioinformatics analysis: Advanced pipelines are used to deliver accurate, reproducible methylation data tailored for population-scale research.

This platform is ideal for applications such as population epigenetics, environmental response profiling, and epigenome-wide association studies (EWAS).

To ensure optimal performance, we recommend that clients follow standardised sample preservation protocols and share relevant study design details (e.g. population structure, exposure context) before project initiation.Our experienced team provides full support—from choosing the appropriate array platform (e.g. 270K or 935K), to optimising labelling strategies and interpreting population-level methylation profiles—ensuring robust and insightful outcomes.

Data Analysis

Data analysis of DNA Methylation Microarray for Population Genetics. (Peterson, et al. 2014)

Why CD Genomics

Cutting-edge Methylation Microarray Technology: Leverage high-density DNA methylation arrays and optimised enrichment or bisulfite protocols to efficiently profile methylation variation across diverse species and large population cohorts.
Cost-effective, High-throughput Epigenotyping: Achieve accurate, scalable, and affordable DNA methylation profiling tailored for population-scale studies—ideal for applications in population epigenetics, environmental response research, and developmental biology.
Robust Bioinformatics Pipeline: Our expert bioinformatics team provides standardised and customizable pipelines for methylation calling, differential methylation analysis, epigenetic diversity assessment, clustering, and integrative multi-omics studies.
Extensive Experience in Population-scale Epigenetics: With years of experience in methylation microarrays and epigenomic data analysis, our team supports every stage of your project—from experimental design to biological interpretation—ensuring reliable and publication-ready results.
Customizable Epigenotyping Solutions: We tailor array platform selection, labelling strategies, and downstream analysis workflows to meet your specific research goals, whether you're studying environmental epigenetic responses, transgenerational inheritance, population structure, or adaptive regulation.

Demo Results

DNA Methylation Microarray for GenomeStudio 450K (Wilhelm et al. 2013)

Sample Requirement

Sample Type	Minimum Amount	Concentration	Purity (A260/A280)	Storage Conditions	Notes
Blood	≥ 200 µL	≥ 20 ng/µL	1.8 ~ 2.0	Store at -80°C	Collect in EDTA tubes; avoid freeze-thaw cycles
Tissue	≥ 30 mg	≥ 20 ng/µL	1.8 ~ 2.0	Store at -80°C	Fresh or snap-frozen in liquid nitrogen
Cell Pellet	≥ 1×10^6 cells	≥ 20 ng/µL	1.8 ~ 2.0	Store at -80°C	Remove culture medium; avoid contamination
Purified DNA Sample	≥ 500 ng (total)	≥ 50 ng/µL	1.8 ~ 2.0	Store at 4°C short-term in TE buffer	High-quality genomic DNA purified
FFPE Tissue Sections	≥ 5 slides, 5 µm thick	—	—	Store at room temperature	Please specify fixation conditions

Case Study

Revisiting genetic artifacts on DNA methylation microarrays exposes novel biological implicationsJournal: Genome Biology

Published:2021

https://doi.org/10.1186/s13059-021-02484-y

Illumina DNA methylation microarrays enable epigenome-wide analysis, vastly used for the discovery of novel DNA methylation variation in health and disease. However, the microarrays’ probe design cannot fully consider the vast human genetic diversity, leading to genetic artefacts. Distinguishing genuine from artifactual genetic influence is of particular relevance in the study of DNA methylation heritability and methylation quantitative trait loci. But despite its importance, current strategies to account for genetic artefacts are lagging due to a limited mechanistic understanding of how such artefacts operate.

DNA methylation microarrays
Bioinfomatics

To address this, we develop and benchmark UMtools, an R package containing novel methods for the quantification and qualification of genetic artefacts based on fluorescence intensity signals. With our approach, we model and validate known SNPs/indels on a genetically controlled dataset of monozygotic twins, and we estimate minor allele frequency from DNA methylation data and empirically detect variants not included in dbSNP. Moreover, we identify examples where genetic artefacts interact with each other or with imprinting, X-inactivation, or tissue-specific regulation.

Overview of Illumina DNA methylation microarray probe design and general principles of UMtools.

FAQs

What is DNA Methylation Microarray Coverage Efficiency?

DNA methylation microarray coverage efficiency refers to the proportion of targeted CpG sites that are reliably detected with high signal intensity and specificity across all samples. Unlike whole-genome bisulfite sequencing, which provides base-resolution methylation data across the entire genome, microarrays offer a reduced-representation yet highly informative view by focusing on thousands to millions of biologically relevant, pre-selected CpG loci. High coverage efficiency ensures consistent detection of methylation signals across individuals and populations, enabling robust analysis of epigenetic diversity, population structure, and environmentally responsive methylation patterns in large-scale studies.

How Efficient is DNA Methylation Microarray in Epigenetic Variation Detection?

DNA methylation microarrays are highly efficient for detecting genome-wide epigenetic variation across large populations. While they do not profile the entire methylome, microarrays consistently interrogate key regulatory regions, including promoters, enhancers, CpG islands, and known disease- or trait-associated loci. This platform is particularly suited for identifying differential methylation associated with environmental exposure, developmental stage, or population structure. The reproducibility, scalability, and cost-effectiveness of methylation arrays make them an ideal tool for epigenome-wide association studies (EWAS), population epigenetics, and transgenerational epigenetic research.

What is the Recommended Sample Quality and Input for Methylation Microarrays in Population Epigenetics?

The quality and quantity of DNA input are critical for successful methylation profiling:

≥500 ng high-quality genomic DNA per sample is typically required, with A260/280 ratio ~1.8–2.0 and minimal degradation.
Consistent extraction methods should be used across all samples to minimize batch effects in large population studies.
Bisulfite conversion efficiency or methylation enrichment performance should be validated in pilot samples prior to large-scale processing.

References

Sahoo, K., & Sundararajan, V. (2024). Methods in DNA methylation array dataset analysis: A review. Computational and structural biotechnology journal, 23, 2304–2325. https://doi.org/10.1016/j.csbj.2024.05.015
Wilhelm-Benartzi, C. S., Koestler, D. C., Karagas, M. R., Flanagan, J. M., Christensen, B. C., Kelsey, K. T., Marsit, C. J., Houseman, E. A., & Brown, R. (2013). Review of processing and analysis methods for DNA methylation array data. British journal of cancer, 109(6), 1394–1402. https://doi.org/10.1038/bjc.2013.496
Planterose Jiménez, B., Kayser, M., & Vidaki, A. (2021). Revisiting genetic artifacts on DNA methylation microarrays exposes novel biological implications. Genome biology, 22(1), 274. https://doi.org/10.1186/s13059-021-02484-y

* Designed for biological research and industrial applications, not intended for individual clinical or medical purposes.