Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, development, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies is currently lacking. To address this gap, we optimized the Targeted Methylation Sequencing protocol (TMS)-which profiles ~4 million CpG sites-for miniaturization, flexibility, and multispecies use. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n = 55 paired samples) and whole genome bisulfite sequencing (n = 6 paired samples). In both cases, we found strong agreement between technologies (R2 = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean = 77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R2 = 0.98). Finally, we confirmed that estimates of 1) epigenetic age and 2) tissue-specific DNA methylation patterns are strongly recapitulated using data generated from TMS versus other technologies. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

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Publication Details

Journal
PLoS Genetics
Published
2025-05-22
DOI
https://doi.org/10.1371/journal.pgen.1011667
Citations
6
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
4.84

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Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

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PLoS Genetics
Epigenetics and DNA Methylation
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article

Cost-effective solutions for high-throughput enzymatic DNA methylation sequencing

Qiuyin Cai, Baptiste Sadoughi, Vivek V. Venkataraman, James P. Higham, Alexander G. Bick, Michael J. Montague, Jie Wu, Kenneth H. Buetow, Sarah F. Brosnan, India A. Schneider‐Crease, Marina M. Watowich, Michael Gurven, Angela Jones, Yvonne Ai Lian Lim, Jonathan Stieglitz, Kee-Seong Ng, Rachel M. Petersen, Hillard S Kaplan, Benjamin C. Trumble, Noah Snyder‐Mackler, Michael L. Platt, Ian J. Wallace, Jamie Roberson, Thomas S. Kraft, Heather M. Highland, Amanda Dawn Melin, Amanda J. Lea, Yiting Huang, Jirong Long, Amy Longtin
article en
6 citations

Abstract

Characterizing DNA methylation patterns is important for addressing key questions in evolutionary biology, development, geroscience, and medical genomics. While costs are decreasing, whole-genome DNA methylation profiling remains prohibitively expensive for most population-scale studies, creating a need for cost-effective, reduced representation approaches (i.e., assays that rely on microarrays, enzyme digests, or sequence capture to target a subset of the genome). Most common whole genome and reduced representation techniques rely on bisulfite conversion, which can damage DNA resulting in DNA loss and sequencing biases. Enzymatic methyl sequencing (EM-seq) was recently proposed to overcome these issues, but thorough benchmarking of EM-seq combined with cost-effective, reduced representation strategies is currently lacking. To address this gap, we optimized the Targeted Methylation Sequencing protocol (TMS)-which profiles ~4 million CpG sites-for miniaturization, flexibility, and multispecies use. First, we tested modifications to increase throughput and reduce cost, including increasing multiplexing, decreasing DNA input, and using enzymatic rather than mechanical fragmentation to prepare DNA. Second, we compared our optimized TMS protocol to commonly used techniques, specifically the Infinium MethylationEPIC BeadChip (n = 55 paired samples) and whole genome bisulfite sequencing (n = 6 paired samples). In both cases, we found strong agreement between technologies (R2 = 0.97 and 0.99, respectively). Third, we tested the optimized TMS protocol in three non-human primate species (rhesus macaques, geladas, and capuchins). We captured a high percentage (mean = 77.1%) of targeted CpG sites and produced methylation level estimates that agreed with those generated from reduced representation bisulfite sequencing (R2 = 0.98). Finally, we confirmed that estimates of 1) epigenetic age and 2) tissue-specific DNA methylation patterns are strongly recapitulated using data generated from TMS versus other technologies. Altogether, our optimized TMS protocol will enable cost-effective, population-scale studies of genome-wide DNA methylation levels across human and non-human primate species.

PLoS GeneticsVol. 21(5)
University of North Carolina at Chapel Hill (US), University of California, Santa Barbara (US), University of Calgary (CA), University of New Mexico (US), Georgia State University (US), Chapman University (US), Vanderbilt University (US), University of Utah (US), Alberta Children's Hospital (CA), University of Malaya (MY), Toulouse School of Economics (FR), New York Consortium in Evolutionary Primatology (US), Institute for Advanced Study in Toulouse (FR), Alberta Children's Hospital Research Institute, Arizona State University (US), New York University (US), University of Pennsylvania (US), Vanderbilt University Medical Center (US)
National Science Foundation, Burroughs Wellcome Fund, Pew Charitable Trusts, Kinship Foundation, Canadian Institute for Advanced Research, Agence Nationale de la Recherche, Canada Research Chairs, Natural Sciences and Engineering Research Council of Canada, National Institute on Aging, National Institute of Mental Health, National Cancer Institute, National Institute of General Medical Sciences
Openalex Percentile: Top 5%
Epigenetics and DNA Methylation
4.84
DOIOpen Access PDFOpenAlex
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