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2016 ; 533
(7603
): 397-401
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Local fitness landscape of the green fluorescent protein
#MMPMID27193686
Sarkisyan KS
; Bolotin DA
; Meer MV
; Usmanova DR
; Mishin AS
; Sharonov GV
; Ivankov DN
; Bozhanova NG
; Baranov MS
; Soylemez O
; Bogatyreva NS
; Vlasov PK
; Egorov ES
; Logacheva MD
; Kondrashov AS
; Chudakov DM
; Putintseva EV
; Mamedov IZ
; Tawfik DS
; Lukyanov KA
; Kondrashov FA
Nature
2016[May]; 533
(7603
): 397-401
PMID27193686
show ga
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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