绘制基因对单细胞转录组网络的影响通过扰乱响应扫描
bioRxiv : the preprint server for biology
|December 31, 2025
概括
我们开发了一种新指标,即单细胞扰乱影响指数 (scPII),以识别干扰的关键基因. scPII有效地预测基因淘汰效应,并有助于理解细胞对干扰的反应.
科学领域:
- 系统生物学 系统生物学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 通过向基因破坏,CRISPR技术已经推进了基因功能研究.
- 单细胞CRISPR查揭示了基因干扰如何改变细胞状态.
- 鉴定关键基因是具有挑战性的,因为复杂的基因网络相互作用和非线性依赖.
研究的目的:
- 开发一种新的方法来识别干扰具有最重要的全系统影响的基因.
- 通过评估系统级对干扰的反应来量化基因淘汰效应.
- 评估全球信息流的破坏和蜂的稳定性.
主要方法:
- 从蛋白质动态调整了一个扰动-响应框架,用于基因调节网络.
- 引入了单细胞扰乱影响指数 (scPII),这是一个数据驱动的指标.
- 使用基因调控网络计算scPII,独立于CRISPR查数据.
主要成果:
- scPII有效地识别了对扰乱产生最大系统范围影响的基因.
- 在scPII得分和CRISPR屏幕基因效应得分之间观察到强烈的相关性.
- 该指标准确量化了生物系统中的基因淘汰效应.
结论:
- scPII提供了一个强大的,数据驱动的方法来预测基因淘汰效应.
- 将扰动响应扫描与基因调节网络集成,可以增强单细胞数据分析.
- 这一框架通过提高对基因功能和细胞动态的理解来推进生物医学研究.
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