Expression level is a major modifier of the fitness landscape of a protein coding gene
Expression level is a major modifier of the fitness landscape of a protein coding gene
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表达水平是蛋白质编码基因适应度的主要调节因素
DOI：
10.1038/s41559-021-01578-x
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发表时间：
2021-11
影响因子：
16.8
通讯作者：
Xiaoshu Chen
中科院分区：
文献类型：
--
作者：
Zhuoxing Wu;Xiujuan Cai;Xin Zhang;Yao Liu;Guo-bao Tian;Jian-Rong Yang;Xiaoshu Chen
基因突变的表型结果取决于许多因素，包括基因的表达水平。然而，这种表达效果的全面量化仍然缺乏，因为这是一个进一步的一般机制的理解效果。在这里，我们测量了几乎所有（>97.5%）的单核苷酸突变的适应性效应，GFP是一个没有生理功能的外源基因，URA3是一个条件必需基因。这两个基因都由两个启动子驱动，其表达水平相差约10倍。由此产生的适应度景观显示，基因内至少42%的单核苷酸突变的适应度效应是依赖于表达的。虽然只有一小部分的变化，在不同的突变之间的健身效果可以解释的生物物理特性的蛋白质和信使RNA的基因，我们的分析表明，避免随机分子错误的基础上的表达依赖的突变效果和建议蛋白质错误折叠的最重要的类型的分子错误之间的检查。因此，我们的结果直接解释了高表达基因的缓慢进化，并强调了由于随机分子错误导致的细胞毒性，作为理解突变表型后果的不可忽略的组成部分。
The phenotypic consequence of a genetic mutation depends on many factors including the expression level of a gene. However, a comprehensive quantification of this expression effect is still lacking, as is a further general mechanistic understanding of the effect. Here, we measured the fitness effect of almost all (>97.5%) single-nucleotide mutations inGFP, an exogenous gene with no physiological function, andURA3, a conditionally essential gene. Both genes were driven by two promoters whose expression levels differed by around tenfold. The resulting fitness landscapes revealed that the fitness effects of at least 42% of all single-nucleotide mutations within the genes were expression dependent. Although only a small fraction of variation in fitness effects among different mutations can be explained by biophysical properties of the protein and messenger RNA of the gene, our analyses revealed that the avoidance of stochastic molecular errors generally underlies the expression dependency of mutational effects and suggested protein misfolding as the most important type of molecular error among those examined. Our results therefore directly explained the slower evolution of highly expressed genes and highlighted cytotoxicity due to stochastic molecular errors as a non-negligible component for understanding the phenotypic consequence of mutations.
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影响因子：
4.8
作者：
C. Qiu;Craig D. Kaplan
通讯作者：
C. Qiu;Craig D. Kaplan
影响因子：
1.8
作者：
HOFACKER, IL;FONTANA, W;SCHUSTER, P
通讯作者：
SCHUSTER, P
影响因子：
2.6
作者：
Carrie Baker Brachmann;A. Davies;G. Cost;E. Caputo;Joachim Li;P. Hieter;J. Boeke
通讯作者：
Carrie Baker Brachmann;A. Davies;G. Cost;E. Caputo;Joachim Li;P. Hieter;J. Boeke
影响因子：
30.8
作者：
Kircher, Martin;Witten, Daniela M.;Jain, Preti;O'Roak, Brian J.;Cooper, Gregory M.;Shendure, Jay
通讯作者：
Shendure, Jay
DOI：
10.1073/pnas.1218066110
发表时间：
2013-02-19
影响因子：
11.1
作者：
Park, Chungoo;Chen, Xiaoshu;Zhang, Jianzhi
通讯作者：
Zhang, Jianzhi