An experimental assay of the interactions of amino acids from orthologous sequences shaping a complex fitness landscape.

Victoria O Pokusaeva,Arseniy V Akopyan,Alexander S Mishin,Sergey Ya Avvakumov,Fyodor A Kondrashov,Karen S Sarkisyan,Lucas B Carey,Guillaume J Filion,Natalya S Bogatyreva,Dinara R Usmanova,Lorena Espinar,Ekaterina V Putintseva,Inna S Povolotskaya,Dmitry N Ivankov,Dmitri A Petrov

doi:10.1371/journal.pgen.1008079

Abstract

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, amino acid replacements were under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. The fitness impact of amino acid replacements was influenced by only a few genetic backgrounds but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible.

Highlights

Predicting function and fitness of organisms from their genotypes is the ultimate goal of many fields in biology, from medical genetics to systems biology to the study of evolution [1,2,3,4,5]
We studied His3, a gene coding for imidazoleglycerol-phosphate dehydratase (IGPD, His3p), an enzyme essential for histidine synthesis
In a multiple alignment of His3 orthologues from 21 yeast species we identified 686 extant amino acid states (S1 Supporting Information), which were evenly distributed across the His3p structure (Fig 1D)

Summary

Introduction

Predicting function and fitness of organisms from their genotypes is the ultimate goal of many fields in biology, from medical genetics to systems biology to the study of evolution [1,2,3,4,5]. Large-scale experimental assays described the shape of the fitness landscape a few mutations away from a local fitness peak (see [7,8,9,10] and references within). Some assays involving a smaller number of genotypes considered combinations of mutations with established functional [11,12,13,14,15,16,17] or evolutionary [18,19,20,21,22,23,24,25] significance

Results

Discussion

Conclusion