Development of integrated pathogenicity prediction system using single nucleotide variants (SNVs)

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K14684
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 43060:System genome science-related
• Research Institution: Nagoya University
• Principal Investigator: Takeda Junichi 名古屋大学, 医学系研究科, 特任助教 (60625672)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: 一塩基変異の病因性予測ツール

Outline of Final Research Achievements

The nucleic acid sequence of a human gene is translated to the protein sequence. Some single nucleotide mutations change the corresponding amino acids, and the changes have the potential to damage the protein functions and may cause a sort of pathogenicity. In recently reported single nucleotide mutations detected from the whole genome sequences of patients, there are many mutations of undetermined significance. In this study, we developed the web service of pathogenicity prediction to the single nucleotide mutations of undetermined significance, and published the paper. The web service is called InMeRF（https://www.med.nagoya-u.ac.jp/neurogenetics/InMeRF/）.

Free Research Field

ゲノム生物学

Academic Significance and Societal Importance of the Research Achievements

本研究では、遺伝子配列の中でアミノ酸の変化を引き起こす一塩基変異に対し、その病因性を予測するウェブツールであるInMeRF（https://www.med.nagoya-u.ac.jp/neurogenetics/InMeRF/）を構築した。InMeRFは比較可能な既存の9つのツールに対し、感度（既知の病因性一塩基変異が病因性だと予測される）・特異度（既知の非病因性一塩基変異が非病因性だと予測される）など7つの項目による性能評価が上回った。InMeRFを用いることにより、患者のゲノムから検出される未知の一塩基変異に対し、病因性かどうかを判断するのに役立つと考えている。