Vial-Pradel Simon, Hasegawa Yoshinori, Nakagawa Ayami, Miyaki Shido, Machida Yasunori, Kojima Shoko, Machida Chiyoko, Takahashi Hiro
Graduate School of Bioscience and Biotechnology, Chubu University, Kasugai, Aichi 487-8501, Japan.
Kazusa DNA Research Institute, 2-6-7 Kazusa-kamatari, Kisarazu, Chiba 292-0818 Japan.
Plant Biotechnol (Tokyo). 2019 Dec 25;36(4):213-222. doi: 10.5511/plantbiotechnology.19.0822a.
DNA methylation in higher organisms has become an expanding field of study as it often involves the regulation of gene expression. Although Whole Genome Bisulfite Sequencing (WG-BS) based on next-generation sequencing (NGS) is the most versatile method, this is a costly technique that lacks in-depth analytic power. There are no conventional methods based on NGS that enable researchers to easily compare the level of DNA methylation from the practical number of samples handled in the laboratory. Although the targeted BS method based on Sanger sequencing is generally used in this case, it lacks in-depth analytic power. Therefore, we propose a new method that combines the high throughput analytic power of NGS and bioinformatics with the specificity and focus offered by PCR-amplification-based bisulfite sequencing methods. We use in silico size sieving of DNA-fragments and primer matchings instead of whole-fragment alignment in our bioinformatics analyses, and named our method SIMON (Simple Inference for Methylome based On NGS). The results of our targeted BS method based on NGS (SIMON method) show that small variations in DNA methylation patterns can be precisely and efficiently measured at a single nucleotide resolution. SIMON method combines pre-existing techniques to provide a cost-effective technique for in-depth studies that focus on pre-identified loci. It offers significant improvements with regard to workflow and the quality of the acquired DNA methylation information. Because of the high accuracy of the analysis, small variations of DNA methylation levels can be precisely determined even with large numbers of samples and loci.
在高等生物中,DNA甲基化已成为一个不断扩展的研究领域,因为它常常涉及基因表达的调控。尽管基于下一代测序(NGS)的全基因组亚硫酸氢盐测序(WG-BS)是最通用的方法,但这是一项成本高昂的技术,缺乏深入分析能力。目前还没有基于NGS的常规方法能让研究人员轻松比较实验室实际处理样本数量下的DNA甲基化水平。虽然在这种情况下通常使用基于桑格测序的靶向亚硫酸氢盐测序方法,但它缺乏深入分析能力。因此,我们提出了一种新方法,该方法将NGS的高通量分析能力和生物信息学与基于PCR扩增的亚硫酸氢盐测序方法所提供的特异性和针对性相结合。在生物信息学分析中,我们使用DNA片段的电子大小筛选和引物匹配,而不是全片段比对,并将我们的方法命名为SIMON(基于NGS的甲基化组简单推断)。我们基于NGS的靶向亚硫酸氢盐测序方法(SIMON方法)的结果表明,可以在单核苷酸分辨率下精确且高效地测量DNA甲基化模式的微小变化。SIMON方法结合了现有技术,为专注于预先确定位点的深入研究提供了一种经济高效的技术。它在工作流程和所获取的DNA甲基化信息质量方面有显著改进。由于分析的高精度,即使有大量样本和位点,也能精确确定DNA甲基化水平的微小变化。