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增强的eMAGE通过组合基因编辑来确定核激素受体功能障碍的遗传因素

Peter N Ciaccia^1,2,3, Zhuobin Liang^4,5,6, Anabel Y Schweitzer^1,2

¹Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, 06520, USA.

Nature communications

|June 18, 2024

概括

我们优化了真核多重基因组工程 (eMAGE) 以在酵母中进行精确,无裂解的基因组编辑. 这种增强的方法实现了高的编辑效率,并减少了工作流的时间,使得癌症生物学中的新发现成为可能.

科学领域:

合成生物学合成生物学
基因组工程是基因组工程.
分子生物学分子生物学

背景情况:

用于基因组修改的工程核酶可以导致不需要的DNA修复结果.
需要非可切割的基因编辑策略来克服基于核酶的方法的局限性.
单核多重基因组工程 (eMAGE) 为组合基因组修改提供了精确,无断的方法.

研究的目的:

优化eMAGE系统以提高编辑频率和效率.
开发一种精确的多重基因组工程方法,减少工作流程时间.
应用优化的eMAGE来研究激素受体中与癌症相关的突变.

主要方法:

系统优化eMAGE协议以增加编辑频率和减少编辑时间.
设计一种可诱导的主导负不匹配修复系统,以抑制背景突变.
在人类雌激素受体α和孕激素受体中使用优化的eMAGE构建突变库.

主要成果:

实现了90%的编辑频率,并将编辑距离扩展到20kb,并优化了eMAGE.
通过将eMAGE与一种新的不匹配修复系统相结合,降低了17倍的背景突变率.
成功模拟了激素受体中的与癌症相关的突变,识别了已知的和新的自主激活突变.

结论:

优化的eMAGE是一个强大的,没有裂变的基因组编辑工具,用于精确的多重工程.
这种方法显著提高了编辑效率,并最大限度地减少了背景突变.
使用eMAGE开发的酵母模型对于剖析复杂的遗传相互作用和发现疾病相关突变是有效的.

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