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Updated: Jun 11, 2025

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皮提亚:非随机DNA修复允许可预测的CRISPR/Cas9集成和基因编辑

Thomas Naert^1,2, Taiyo Yamamoto¹, Shuting Han^3,4

¹Institute of Anatomy, University of Zurich, Zurich, Switzerland.

bioRxiv : the preprint server for biology

|October 10, 2024

概括

深度学习模型预测CRISPR基因组工程的DNA修复. 这使得大型DNA有效载荷和小编辑能够精确地集成到各种细胞类型中,用于研究和治疗.

科学领域:

分子生物学分子生物学
基因组学就是基因组学.
生物工程是生物工程.

背景情况:

基于CRISPR的基因组工程为科学研究和治疗开发提供了巨大的潜力.
由于管理DNA修复过程的局限性,在各种细胞环境中,高效和可控的DNA整合和编辑仍然具有挑战性.

研究的目的:

开发可预测的方法来控制基因组-货物接口上的DNA修复,以增强CRISPR应用.
为了促进大型DNA序列的整合和精确的小编辑在各种细胞类型和生物体.

主要方法:

利用深度学习模型根据序列背景预测DNA修复结果.
设计并实施了三重基对重复修复臂 (三元组) 来指导微同质介导的末端连接.
使用的寡核酸模板用于精确的单核酸或双核酸编辑.

主要成果:

通过深度学习预测和特定序列规则,在基因组-货物接口展示了可预测的DNA修复.
成功地整合了大型DNA货物 (>2kb) 并在人类细胞和体内模型中的30多个位置进行了精确的小编辑.
在Xenopus中实现了生殖系可传播的转基因整合和在分化小鼠大脑细胞中实现了内源标记,展示了广泛的应用性.

结论:

开发了一种使用预测修复臂的新策略,用于高效和可控的大型DNA集成和小核酸编辑.
皮提亚设计工具 (pythia-editing.org) 提供了一个用户友好的平台来优化定制的基因组工程策略.
这种方法显著扩大了CRISPR技术在各种细胞类型和生物体的实验和治疗应用中的实用性.

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Selection-dependent and Independent Generation of CRISPR/Cas9-mediated Gene Knockouts in Mammalian Cells

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Enhanced Genome Editing with Cas9 Ribonucleoprotein in Diverse Cells and Organisms

Enhanced Genome Editing with Cas9 Ribonucleoprotein in Diverse Cells and Organisms

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