Format

Send to

Choose Destination
Plant Biotechnol (Tokyo). 2019 Dec 25;36(4):213-222. doi: 10.5511/plantbiotechnology.19.0822a.

SIMON: Simple methods for analyzing DNA methylation by targeted bisulfite next-generation sequencing.

Author information

1
Graduate School of Bioscience and Biotechnology, Chubu University, Kasugai, Aichi 487-8501, Japan.
2
Kazusa DNA Research Institute, 2-6-7 Kazusa-kamatari, Kisarazu, Chiba 292-0818 Japan.
3
Graduate School of Horticulture, Chiba University, Matsudo 648, Matsudo, Chiba 271-8510, Japan.
4
Division of Biological Science, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan.
5
Graduate School of Medical Sciences, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan.

Abstract

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.

KEYWORDS:

DNA methylation; NGS; bioinformatics; sample size calculation; targeted BS sequencing

Conflict of interest statement

DisclosuresThe authors have no conflicts of interest to declare.

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center