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病原性変異の予測可能で正確なテンプレートフリーCRISPR編集
Max W Shen1,2, Mandana Arbab3,4,5, Jonathan Y Hsu6,7
1Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nature
|November 9, 2018
まとめ
テンプレートなしのCas9ゲノム編集は 精密なDNA修復を可能にしました この機械学習アプローチは 病気に関連した変異を修正し 遺伝子療法の新たなツールを提供します
科学分野:
- ゲノミクス
- 分子生物学
- バイオ情報学
背景:
- Cas9分裂後のDNA修復は ランダムで予測不可能です
- これは単純な遺伝子破壊を超えてその適用を制限します.
研究 の 目的:
- 予測可能で正確な テンプレートフリーCas9ゲノム編集を証明する
- 編集結果を予測するための機械学習モデルを開発する.
主な方法:
- 機械学習モデルをデルフィで訓練した 2千のCas9ガイドRNAとDNAの標的サイトペアで
- inDelphiは削除と挿入の遺伝子型と頻度を予測します.
- ヒトとマウスの細胞系で検証された予測.
主要な成果:
- inDelphiは編集結果を正確に予測しています (r=0.87).
- 特定されたCas9ガイドRNAは,5~11%の症例で精密な編集 (精密な50) を得ている.
- 患者由来細胞 (ヘルマンスキ・プードラック症候群,メンケス病) の病原性突然変異を正した.
結論:
- テンプレートなしのCas9編集は,正確かつ予測可能である.
- inDelphiはゲノム編集のための正確な遺伝子型予測を可能にします.
- このアプローチは遺伝疾患の正確な修正を容易にする.
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