Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Doctor Aiguader 88, 08003, Barcelona, Spain.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Doctor Aiguader 88, 08003, Barcelona, Spain.
Nat Commun. 2019 Jul 18;10(1):3180. doi: 10.1038/s41467-019-11116-w.
The effects of cell-to-cell variation (noise) in gene expression have proven difficult to quantify because of the mechanistic coupling of noise to mean expression. To independently quantify the effects of changes in mean expression and noise we determine the fitness landscapes in mean-noise expression space for 33 genes in yeast. For most genes, short-lived (noise) deviations away from the expression optimum are nearly as detrimental as sustained (mean) deviations. Fitness landscapes can be classified by a combination of each gene's sensitivity to protein shortage or surplus. We use this classification to explore evolutionary scenarios for gene expression and find that certain landscape topologies can break the mechanistic coupling of mean and noise, thus promoting independent optimization of both properties. These results demonstrate that noise is detrimental for many genes and reveal non-trivial consequences of mean-noise-fitness topologies for the evolution of gene expression systems.
细胞间基因表达变化（噪声）的影响由于噪声与平均表达的机制耦合而难以定量。为了独立量化平均表达和噪声变化的影响，我们确定了酵母中 33 个基因在平均噪声表达空间中的适应度景观。对于大多数基因，短暂（噪声）偏离表达最佳值的情况几乎与持续（平均）偏离一样有害。适应度景观可以通过每个基因对蛋白质短缺或过剩的敏感性的组合来分类。我们使用这种分类来探索基因表达的进化情景，发现某些景观拓扑结构可以打破平均和噪声的机制耦合，从而促进这两个特性的独立优化。这些结果表明噪声对许多基因都是有害的，并揭示了平均噪声适应度拓扑结构对基因表达系统进化的重要影响。
