人間 と 霊長類 の 許容 される 遺伝子 変異 の 景観
Hong Gao1, Tobias Hamp1, Jeffrey Ede1
1Illumina Artificial Intelligence Laboratory, Illumina Inc., Foster City, CA, 94404, USA.
まとめ
科学者は霊長類のゲノムデータを用いて 何百万ものヒトの遺伝子変異を特定しました このアプローチは,どの変種が良性であるかを決定し,遺伝疾患の診断を改善するのに役立ちます.
科学分野:
- ゲノミクス
- 進化生物学
- コンピュータ生物学
背景:
- パーソナライズされたゲノム配列解析は 遺伝子の違いを多く明らかにしますが その臨床的意義は よく不明です
- 遺伝子変異の機能的影響を理解することは 遺伝疾患の診断に不可欠です
研究 の 目的:
- ヒトの遺伝子変異の臨床的関連性を 体系的に解読する
- タンパク質を変化させる変種の病原性を分類する方法を開発する.
主な方法:
- 233種の霊長類の809人の全ゲノム配列データを分析した.
- ヒトに共通する430万種のタンパク質変異変異体が確認された.
- 変異性の病原性を推定するために ディープラーニングモデルを使用した.
主要な成果:
- 類人猿の種に共通する タンパク質変異の種類を何百万個も特定しました
- ヒトのタンパク質変異の6%は,霊長類における高アレル頻度に基づいて,おそらく良性であると分類された.
- ディープラーニングを使って 病原菌変異の診断に 最先端の精度を達成しました
結論:
- 霊長類のゲノムデータは,ヒトの遺伝子変異の影響を評価するための貴重なリソースを提供します.
- この方法は遺伝子変異の分類を強化し,遺伝疾患の診断に役立ちます.
- 変種病原性のディープラーニングは 臨床ゲノミクスの強力なツールです
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