在转录网络中存在无关联的因果关系
bioRxiv : the preprint server for biology
|February 23, 2026
概括
基因表达网络中的因果关系可以在没有相关性的情况下存在. 一项新的非线性因果关系测试揭示了酵母和小鼠中的这些隐藏联系,挑战了传统的基于相关性的分析.
科学领域:
- 系统生物学 系统生物学
- 基因监管网络分析 基因监管网络分析
- 计算生物学是一种计算生物学.
背景情况:
- 相关性经常被错误地用作生物系统中因果关系的证据.
- 转录网络表现出复杂的动态,包括非线性和时间协调的基因表达模式.
- 现有的方法可能会错过因果关系,因缺乏线性相关性而掩盖.
研究的目的:
- 调查与相关性独立的转录网络中因果关系的存在.
- 开发和应用一种非线性因果关系测试,以揭示隐藏的因果关系.
- 在酵母和小鼠模型中验证发现.
主要方法:
- 来自酵母和小鼠的基因表达数据的分析.
- 应用一种新的非线性因果关系测试,考虑依赖状态和时间动态.
- 在酵母中检测到的非相关的因果关系的实验验证.
主要成果:
- 酵母和小鼠中很大一部分 (65-77%) 的基因表现出依赖状态和时间协调的表达.
- 非线性因果关系测试确定了基于关联的方法看不到的强有力的因果关系.
- 在酵母中检测到转录调节器WHI5和YHP1的非相关因果关系,并通过实验验证 (71-78%准确率).
结论:
- 缺乏相关性并不意味着在转录网络中缺乏因果关系.
- 非线性因果关系测试对于发现复杂的调节相互作用至关重要.
- 这种方法提高了我们对关键细胞检查点的基因调节的理解.
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