Genome-wide DNA methylation profiling in human breast tissue by Illumina TruSeq methyl capture EPIC sequencing and infinium methylationEPIC beadchip microarray

ABSTRACT

A newly-developed platform, the Illumina TruSeq Methyl Capture EPIC library prep (TruSeq EPIC), builds on the content of the Infinium MethylationEPIC Beadchip Microarray (EPIC-array) and leverages the power of next-generation sequencing for targeted bisulphite sequencing. We empirically examined the performance of TruSeq EPIC and EPIC-array in assessing genome-wide DNA methylation in breast tissue samples. TruSeq EPIC provided data with a much higher density in the regions when compared to EPIC-array (~2.74 million CpGs with at least 10X coverage vs ~752 K CpGs, respectively). Approximately 398 K CpGs were common and measured across the two platforms in every sample. Overall, there was high concordance in methylation levels between the two platforms (Pearson correlation r = 0.98, P < 0.0001). However, we observed that TruSeq EPIC measurements provided a wider dynamic range and likely a higher quantitative sensitivity for CpGs that were either hypo- or hyper-methylated (β close to 0 or 1, respectively). In addition, when comparing different breast tissue types TruSeq EPIC identified more differentially methylated CpGs than EPIC-array, not only out of additional sites interrogated by TruSeq EPIC alone, but also out of common sites interrogated by both platforms. Our results suggest that both platforms show high reproducibility and reliability in genome-wide DNA methylation profiling, while TruSeq EPIC had a significant improvement over EPIC-array regarding genomic resolution and coverage. The wider dynamic range and likely higher precision of the estimates by the TruSeq EPIC may lead to the identification of novel differentially methylated markers that are associated with disease risk.

KEYWORDS:

• DNA methylation
• differentially methylated sites
• genomic resolution
• genome coverage
• infinium MethylationEPIC Beadchip
• microarray
• methyl-capture sequencing
• methylome
• next-generation sequencing
• quantitative sensitivity

Acknowledgments

We would like to acknowledge the Susan G. Komen ® Tissue Bank and women who contributed breast tissue samples to this study. We thank the Center for Medical Genomics at Indiana University School of Medicine for performing DNA methylation sequencing assay, and EpigenDx, Inc. for performing EPIC-array DNA methylation assay.

Authors’ contributions

C.H. designed and directed the study. Y.L. and C.H. designed the assay. N.L. and J.L. performed the methylation sequencing data processing, and N.L. performed the comparative analysis pipeline and additional data processing. A.S. processed samples. J.R.C., J.W., C.W., and Y.L. provided valuable insight, interpretations and advice. N.L. and C.H. wrote the manuscript with inputs from the other authors. All authors read and approved the final manuscript.

Disclosure statement

All authors declare no conflicts of interest.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This research was supported by the National Cancer Institute R01CA194030, Susan G. Komen Career Catalyst Research Grant CCR15333233, and the Biostatistics and Bioinformatics Shared Resource Facility of the University of Kentucky Markey Cancer Center [P30CA177558].