健身景观
上位性
生物
进化生物学
人口
突变
遗传学
基因
社会学
人口学
作者
Karen S. Sarkisyan,Dmitriy A. Bolotin,Margarita Meer,Dinara R. Usmanova,Alexander S. Mishin,Г. В. Шаронов,Dmitry N. Ivankov,Nina G. Bozhanova,Михаил С. Баранов,Onuralp Söylemez,Natalya S. Bogatyreva,Peter K. Vlasov,Evgeny S. Egorov,Maria D. Logacheva,Alexey S. Kondrashov,Dmitriy M. Chudakov,Ekaterina V. Putintseva,Ilgar Z. Mamedov,Dan S. Tawfik,Konstantin A. Lukyanov,Fyodor A. Kondrashov
出处
期刊:Nature
[Springer Nature]
日期:2016-05-01
卷期号:533 (7603): 397-401
被引量:517
摘要
Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.
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