Itemized cost-per-sample breakdown of TMS.

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.

解析DNA甲基化模式，对于解答进化生物学、发育生物学、衰老科学以及医学基因组学中的核心问题具有重要意义。尽管测序成本持续下降，但全基因组DNA甲基化谱分析对于大多数群体规模研究而言仍过于昂贵，因此亟需开发低成本的简化表征检测策略——即依赖微阵列、酶切或序列捕获技术靶向基因组特定区域的检测手段。当前主流的全基因组及简化表征甲基化检测技术均依赖亚硫酸氢盐转化法，但该方法会损伤DNA，导致DNA丢失及测序偏差。酶促甲基化测序（Enzymatic methyl sequencing, EM-seq）的提出旨在解决上述问题，但目前尚缺乏针对EM-seq与低成本简化表征检测策略联用方案的全面基准评测。为填补这一研究空白，我们对靶向甲基化测序方案（Targeted Methylation Sequencing protocol, TMS）进行了优化——该方案可靶向检测约400万个CpG位点——以实现实验流程微型化、操作灵活性提升及跨物种适配。首先，我们测试了多项可提升通量、降低成本的优化方案，包括增加多重测序复用率、减少DNA起始投入量，以及采用酶切法而非机械法进行DNA片段化处理。其次，我们将优化后的TMS方案与主流检测技术进行了对比，具体包括Infinium MethylationEPIC微珠芯片（n=55对配对样本）及全基因组亚硫酸氢盐测序（n=6对配对样本），结果显示两种技术的检测结果均具有高度一致性（决定系数R²分别为0.97和0.99）。第三，我们在三种非人灵长类动物（恒河猴、狮尾狒及卷尾猴）中验证了优化后的TMS方案，结果显示该方案可高效捕获靶向CpG位点（平均捕获率达77.1%），且所得甲基化水平估算结果与简化代表性亚硫酸氢盐测序的结果高度一致（R²=0.98）。最后，我们验证了利用TMS生成的数据可高度准确地复现1）表观遗传年龄估算结果，以及2）组织特异性DNA甲基化模式，其表现与其他技术所得结果相当。综上，我们优化后的TMS方案可支持开展跨人类及非人灵长类物种的、低成本的群体规模全基因组DNA甲基化水平研究。