Bioinformatics methods for PacBio methylation data towards microbial differential epigenome analysis

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K20409
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: National Institute of Advanced Industrial Science and Technology
• Principal Investigator: Saito Yutaka 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 主任研究員 (60721496)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: エピゲノム / DNAメチル化 / PacBio / 微生物 / バイオインフォマティクス

Outline of Final Research Achievements

In epigenome studies for bacteria and eukaryotic microorganisms, PacBio sequencers are widely used due to its ability to detect various types of DNA methylation including 6mA. When the polymerase encounters a methylated site during sequencing, it spends a longer time for incorporating the base, which is measured as a kinetics feature called inter pulse duration (IPD). In bioinformatics methods for PacBio methylation analysis, several machine learning (ML) models have been developed for using IPD for various downstream tasks e.g. methylation detection and methylation fraction estimation. In this study, we improved these ML models.

Free Research Field

バイオインフォマティクス

Academic Significance and Societal Importance of the Research Achievements

本研究で開発した微生物エピゲノムデータ解析技術により、病原菌や環境細菌叢におけるエピゲノム研究を加速できる。これにより、人類の健康や環境問題の解決などに貢献できると期待される。