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在哺乳动物细胞中预测由Cas9,基编辑和主要编辑产生的突变

Juliane Weller¹, Ananth Pallaseni¹, Jonas Koeppel¹

¹Wellcome Sanger Institute, Hinxton, United Kingdom.

The CRISPR journal

|June 20, 2023

概括

基因编辑CRISPR为遗传疾病提供了新的治疗方法,但控制突变是关键. 本综述详细介绍了机器学习模型如何预测哺乳动物细胞中的CRISPR编辑结果,以更好地设计实验.

科学领域:

分子生物学分子生物学
生物信息学是一种生物信息学.
遗传学遗传学是一个

背景情况:

CRISPR-Cas基因编辑正在向遗传疾病的临床应用中取得进展.
精确控制基因编辑结果,如突变,对于治疗成功至关重要.
编辑结果可以根据特定的DNA目标站点显著不同.

研究的目的:

审查目前对哺乳动物细胞中的CRISPR-Cas切割,基编辑和原始编辑的理解和预测能力.
为基因编辑预测提供有关DNA修复机制和机器学习的基础知识.
整合关于数据集,方法和洞察力的信息,以在规模上描述基因编辑事件.

主要方法:

在CRISPR-Cas中介编辑中涉及的DNA修复途径的概述.
机器学习原理的介绍,这些原理是预测模型的基础.
对现有数据集和方法的调查,用于基因编辑的大规模表征.
分析从这些数据集和方法中获得的见解.

主要成果:

在哺乳动物细胞中,可以预测CRISPR-Cas,基编辑和主要编辑的结果.
在全面数据集上训练的机器学习模型,为编辑变化提供了洞察力.
了解DNA修复和编辑模式对于模型开发至关重要.

结论:

预测模型是设计高效基因编辑实验的基础.
通过计算方法,可以对基于CRISPR的基因编辑结果进行增强的控制.
本综述综合了当前的知识,以指导未来的治疗开发和研究.

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