在mRNA和蛋白质水平的进化变化的解上
Daohan Jiang1, Alexander L Cope2,3,4, Jianzhi Zhang5
1Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Molecular biology and evolution
|July 27, 2023
概括
基因表达变异驱动了适应,但mRNA水平并不总是预测蛋白质水平. mRNA和翻译之间的补偿进化有助于解释这种不匹配,特别是在稳定选择下.
科学领域:
- 进化生物学是进化的生物学.
- 分子进化是分子进化的过程.
- 系统生物学 系统生物学
背景情况:
- 基因表达变异是表型多样性和适应性的关键.
- mRNA水平通常用于推断蛋白质水平,但相关性往往很弱.
- 差异可能来自mRNA丰富度和转化调节之间的补偿进化.
研究的目的:
- 开发一个理论模型,用于mRNA和蛋白质水平的共同进化.
- 研究有利于补偿进化的进化条件.
- 了解不同选择方案下的mRNA和蛋白质水平之间的相关性强度.
主要方法:
- 基因表达进化的理论建模.
- 分析mRNA和蛋白质水平之间的共同进化动态.
- 在稳定和定向选择下对调节路径的模拟.
主要成果:
- 在蛋白质水平上稳定选择下,mRNA和翻译之间的补偿进化广泛存在.
- 在定向选择下,mRNA和翻译率显示出跨谱系的负相关性,但跨基因的正相关性.
- mRNA-蛋白相关性的强度取决于选择的类型和监管背景.
结论:
- 补偿进化为mRNA-蛋白质水平不匹配提供了一个生物学解释.
- 了解这些动态对于解释比较的转录组和蛋白组数据至关重要.
- 该模型提供了一个框架来解开影响基因表达数据的进化和统计因素.
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