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Crystal Structure of an Ancient Protein: Evolution
by Conformational Epistasis
Eric A. Ortlund, et al.
Science 317, 1544 (2007);
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proaches have been and are being considered. For
example, in Singapore, where 84% of the popu-
lation lives in public housing (35), regulations that
explicitly recognize the role of spatial segregation in
sectarianism specify the percentage of ethnic groups
to occupy housing blocks (36). This legally
compels ethnic mixing at a scale finer than that
which our study finds likely to lead to violence.
Given the natural tendency toward social separa-
tion, maintaining such mixing requires a level of
authoritarianism that might not be entertained in
other locations. Still, despite social tensions (37),
the current absence of violence provides some
support to our analysis. The alternative approach—
aiding in the separation process by establishing
clear boundaries between cultural groups to
prevent violence—has also gained recent atten-
tion (38, 39). Although further studies are
needed, there exist assessments (39) of the impact
of historical partitions in Ireland, Cyprus, the
Indian subcontinent, and the Middle East that
may be consistent with the understanding of type
separation and a critical scale of mixing or
separation presented here.
The insight provided by this study may help
inform policy debates by guiding our understanding
of the consequences of policy alternatives. The
purpose of this paper does not include promoting
specific policy options. Although our work re-
inforces suggestions to consider separation, we are
not diminishing the relevance of concerns about the
desirability of separation or its process. Even where
separation may be indicated as a way of preventing
violence, caution is warranted to ensure that the
goal of preventing violence does not become a
justification for violence. Moreover, even a peaceful
process of separation is likely to be objectionable.
There may be ways to positively motivate
separation using incentives, as well as to mitigate
negative aspects of separation that often include
displacement of populations and mobility barriers.
Our results for the range of filter diameters that
provide good statistical agreement between
reported and predicted violence in the former
Yugoslavia and India suggest that regions of width
less than 10 km or greater than 100 km may
provide sufficient mixing or isolation to reduce the
chance of violence. These bounds may be affected
by a variety of secondary factors including social
and economic conditions; the simulation resolu-
tion may limit the accuracy of the lower limit; and
boundaries such as rivers, other physical barriers,
or political divisions will surely play a role. Still,
this may provide initial guidance for strategic
planning. Identifying the nature of boundaries to
be established and the means for ensuring their
stability, however, must reflect local issues.
Our approach does not consider the relative
merits of cultures, individual acts, or immediate
causes of violence, but rather the conditions that may
promote violence. It is worth considering whether, in
places where cultural differentiation is taking place,
conflict might be prevented or minimized by political
acts that create appropriate boundaries suited to the
current geocultural regions rather than the existing
historically based state boundaries. Such bounda-
ries need not inhibit trade and commerce and need
not mark the boundaries of states, but should allow
each cultural group to adopt independent behav-
iors in separate domains. Peaceful coexistence
need not require complete integration.
References and Notes
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California Press, Berkeley and Los Angeles, ed. 2, 2000).
3. B. Harff, T. R. Gurr, Ethnic Conflict in World Politics
(Westview, Boulder, ed. 2, 2004).
4. S. Huntington, The Clash of Civilizations and the Remaking of
World Order (Simon & Schuster, New York, 1996).
5. D. Chirot, M. E. P. Seligman, Eds., Ethnopolitical Warfare:
Causes, Consequences, and Possible Solutions (American
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6. M. Reynal-Querol, J. Conflict Resolut. 46, 29 (2002).
7. T. R. Gulden, Politics Life Sciences 21, 26 (2002).
8. H. Buhaug, S. Gates, J. Peace Res. 39, 417 (2002).
9. A. Varshney, Ethnic Conflict and Civic Life: Hindus and
Muslims in India (Yale Univ. Press, New Haven, CT, 2003).
10. M. D. Toft, The Geography of Ethnic Violence: Identity,
Interests, and the Indivisibility of Territory (Princeton
Univ. Press, Princeton, NJ, 2003).
11. J. Fox, Religion, Civilization, and Civil War: 1945 through the
New Millennium (Lexington Books, Lanham, MD, 2004).
12. M. Mann, The Dark Side of Democracy: Explaining Ethnic
Cleansing (Cambridge Univ. Press, New York, 2004).
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material on Science Online.
15. T. C. Schelling, J. Math. Sociol. 1, 143 (1971).
16. J. Mimkes, J. Therm. Anal. 43, 521 (1995).
17. H. P. Young, Individual Strategy and Social Structure
(Princeton Univ. Press, Princeton, NJ, 1998).
18. R. Van Kempen, A. S. Ozuekren, Urban Stud. 35, 1631 (1998).
19. Y. Bar-Yam, in Dynamics of Complex Systems (Perseus
Press, Cambridge, MA, 1997), chap. 7.
20. A. J. Bray, Adv. Phys. 43, 357 (1994).
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22. D. A. Huse, Phys. Rev. B 34, 7845 (1986).
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24. P. Collier, A. Hoeffler, Oxf. Econ. Pap. 50, 563 (1998).
25. R. H. Bates, Am. Econ. Rev. 90, 131 (2000).
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27. D. N. Posner, Am. J. Pol. Sci. 48, 849 (2004).
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Lett. 74, 3293 (1995).
30. P. Ch. Ivanov et al., Nature 383, 323 (1996).
31. Map of Yugoslavia, Courtesy of the University of Texas
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32. R. Petrovic, Yugosl. Surv. 33, 3 (1992).
33. K. Chaudhuri, Frontline 18 (no. 2), www.hinduonnet.com/
34. Final Report, Carnegie Commission on Preventing Deadly
35. A. Brief Background, Housing and Development Board,
Singapore Government, www.hdb.gov.sg/fi10/fi10296p.nsf/
36. Ethnic Integration Policy, Housing and Development
Board, Singapore Government, www.hdb.gov.sg/fi10/
37. D. Murphy, Christian Science Monitor, 5 February 2002,
38. J. Tullberg, B. S. Tullberg, Politics Life Sciences 16, 237 (1997).
39. C. Kaufmann, Int. Secur. 23, 120 (1998).
40. We thank G. Wolfe, M. Woolsey, and L. Burlingame for
editing the manuscript; B. Wang for assistance with figures;
M. Nguyen and Z. Bar-Yam for assistance with identifying
data; and I. Epstein, S. Pimm, F. Schwartz, E. Downs, and
S. Frey for helpful comments. We acknowledge internal
support by the New England Complex Systems Institute and
the U.S. government for support of preliminary results.
Supporting Online Material
Figs. S1.1 to S4.3
30 November 2006; accepted 13 August 2007
Crystal Structure of an Ancient
Protein: Evolution by
Eric A. Ortlund,1* Jamie T. Bridgham,2* Matthew R. Redinbo,1 Joseph W. Thornton2†
The structural mechanisms by which proteins have evolved new functions are known only indirectly.
We report x-ray crystal structures of a resurrected ancestral protein—the ~450 million-year-old
precursor of vertebrate glucocorticoid (GR) and mineralocorticoid (MR) receptors. Using structural,
phylogenetic, and functional analysis, we identify the specific set of historical mutations that
recapitulate the evolution of GR’s hormone specificity from an MR-like ancestor. These
substitutions repositioned crucial residues to create new receptor-ligand and intraprotein contacts.
Strong epistatic interactions occur because one substitution changes the conformational position
of another site. “Permissive” mutations—substitutions of no immediate consequence, which
stabilize specific elements of the protein and allow it to tolerate subsequent function-switching
changes—played a major role in determining GR’s evolutionary trajectory.
central goal in molecular evolution is to
understand the mechanisms and dynam-
ics by which changes in gene sequence
generate shifts in function and therefore pheno-
type (1, 2). A complete understanding of this
process requires analysis of how changes in protein
structure mediate the effects of mutations on
function. Comparative analyses of extant proteins
have provided indirect insights into the diversifi-
cation of protein structure (3–6), and protein
1544 14 SEPTEMBER 2007 VOL 317 SCIENCE www.sciencemag.org
30 4010HomoGR RajaGR HomoMR
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Hormone (log M)
TetrapodGR TeleostGR ElasmobranchGR MRs(8)
(4) (6) (1) 20
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-7 -6 C
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engineering studies have elucidated structure-
function relations that shape the evolutionary
process (7–11). To directly identify the mecha-
nisms by which historical mutations generated
new functions, however, it is necessary to
compare proteins through evolutionary time.
Here we report the empirical structures of an
ancient protein, which we “resurrected” (12) by
phylogenetically determining its maximum likeli-
hood sequence from a large database of extant se-
quences, biochemically synthesizing a gene coding
for the inferred ancestral protein, expressing it in
cultured cells, and determining the protein’s
structure by x-ray crystallography. Specifically, we
investigated the mechanistic basis for the functional
evolution of the glucocorticoid receptor (GR), a
hormone-regulated transcription factor present in all
jawed vertebrates (13). GR and its sister gene, the
mineralocorticoid receptor (MR), descend from the
duplication of a single ancient gene, the ancestral
corticoid receptor (AncCR), deep in the vertebrate
lineage ~450 million years ago (Ma) (Fig. 1A) (13).
GR is activated by the adrenal steroid cortisol and
regulates stress response, glucose homeostasis, and
other functions (14). MR is activated by aldosterone
in tetrapods and by deoxycorticosterone (DOC) in
teleosts to control electrolyte homeostasis, kidney
1Department of Chemistry, University of North Carolina,
Chapel Hill, NC 27599, USA. 2Center for Ecology and
Evolutionary Biology, University of Oregon, Eugene, OR
*These authors contributed equally to this work.
†To whom correspondence should be addressed. E-mail:
Fig. 1. (A) Functional evolution
and colon function, and other processes (14). MR is
also sensitive to cortisol, though considerably less
so than to aldosterone and DOC (13, 15).
Previously, AncCR was resurrected and found to
have MR-like sensitivity to aldosterone, DOC, and
cortisol, indicating that GR’s cortisol specificity is
evolutionarily derived (13).
To identify the structural mechanisms by
which GR evolved this new function, we used
x-ray crystallography to determine the structures
of the resurrected AncCR ligand-binding domain
(LBD) in complex with aldosterone, DOC, and
cortisol (16) at 1.9, 2.0, and 2.4 Å resolution,
respectively (table S1). All structures adopt the
classic active conformation for nuclear receptors
(17), with unambiguous electron density for each
hormone (Fig. 1B and figs. S1 and S2). AncCR’s
structure is extremely similar to the human MR
[root mean square deviation (RMSD) = 0.9 Å for
all backbone atoms] and, to a lesser extent, to the
human GR (RMSD = 1.2 Å). The network of
hydrogen-bonds supporting activation in the
human MR (18) is present in AncCR, indicating
that MR’s structural mode of action has been
conserved for >400 million years (fig. S3).
Because aldosterone evolved only in the
tetrapods, tens of millions of years after AncCR,
that receptor’s sensitivity to aldosterone was
surprising (13). The AncCR-ligand structures
indicate that the receptor’s ancient response to
aldosterone was a structural by-product of its
sensitivity to DOC, the likely ancestral ligand,
which it binds almost identically (Fig. 1C). Key
contacts for binding DOC involve conserved
surfaces among the hormones, and no obligate
contacts are made with moieties at C11, C17, and
C18, the only variable positions among the three
hormones. These inferences are robust to uncer-
tainty in the sequence reconstruction: We modeled
each plausible alternate reconstruction [posterior
probability (PP) > 0.20] into the AncCR crystal
structures and found that none significantly af-
fected the backbone conformation or ligand inter-
actions. The receptor, therefore, had the structural
potential to be fortuitously activated by aldoster-
one when that hormone evolved tens of millions
of years later, providing the mechanism for evo-
lution of the MR-aldosterone partnership by mo-
lecular exploitation, as described (13).
To determine how GR’s preference for cortisol
evolved, we identified substitutions that occurred
during the same period as the shift in GR function.
We used maximum likelihood phylogenetics to de-
termine the sequences of ancestral receptors along
the GR lineage (16). The reconstructions had strong
support, with mean PP >0.93 and the vast majority
of sites with PP >0.90 (tables S2 and S3). We
synthesized a cDNA for each reconstructed LBD,
expressed it in cultured cells, and experimentally
characterized its hormone sensitivity in a reporter
gene transcription assay (16). GR from the com-
mon ancestor of all jawed vertebrates (AncGR1 in
Fig. 1A) retained AncCR’s sensitivity to aldoster-
one, DOC, and cortisol. At the next node, however,
GR from the common ancestor of bony vertebrates
(AncGR2) had a phenotype like that of modern
GRs, responding only to cortisol. This inference is
robust to reconstruction uncertainty: We introduced
of corticosteroid receptors. Dose-
response curves show transcrip-
tion of a luciferase reporter gene
by extant and resurrected ances-
tral receptors with varying doses
(in log M) of aldosterone (green),
DOC (orange), and cortisol (pur-
ple). Black box indicates evolution
of cortisol specificity. The number
of sequence changes on each
branch is shown (aa, replacement;
D, deletion). Scale bars, SEM of
three replicates. Node dates from
the fossil record (19, 20). For com-
plete phylogeny and sequences,
see fig. S10 and table S5. (B)
Crystal structure of the AncCR LBD
with bound aldosterone (green,
with red oxygens). Helices are la-
beled. (C) AncCR’s ligand-binding
pocket. Side chains (<4.2 Å from bound ligand) are superimposed from crystal structures of AncCR with aldosterone (green), DOC (orange), and cortisol (purple). Oxygen and nitrogen atoms are red and blue, respectively; dashed lines indicate hydrogen bonds. Arrows show C11, C17, and C18 positions, which differ among the h
www.sciencemag.org SCIENCE VOL 317 14 SEPTEMBER 2007 1545
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plausible alternative states by mutagenesis, but
none changed function (fig. S4). GR’s specificity
therefore evolved during the interval between these
two speciation events, ~420 to 440 Ma (19, 20).
During this interval, there were 36 substitutions
and one single-codon deletion (figs. S5 and S6).
Four substitutions and the deletion are conserved in
one state in all GRs that descend from AncGR2 and
in another state in all receptors with the ancestral
function. Two of these—S106P and L111Q (21)—
were previously identified as increasing cortisol
specificity when introduced into AncCR (13). We
introduced these substitutions into AncGR1 and
found that they recapitulate a large portion of the
functional shift from AncGR1 to AncGR2, radi-
cally reducing aldosterone and DOC response
while maintaining moderate sensitivity to cortisol
(Fig. 2A); the concentrations required for half-
maximal activation (EC50) by aldosterone and
DOC increased by 169- and 57-fold, respectively,
whereas that for cortisol increased only twofold. A
strong epistatic interaction between substitutions
was apparent: L111Q alone had little effect on
sensitivity to any hormone, but S106P dramatically
reduced activation by all ligands. Only the
combination switched receptor preference from
aldosterone and DOC to cortisol. Introducing these
historical substitutions into the human MR yielded
a completely nonfunctional receptor, as did
reversing them in the human GR (fig. S7). These
results emphasize the importance of having the
ancestral sequence to reveal the functional impacts
of historical substitutions.
To determine the mechanism by which these
two substitutions shift function, we compared the
structures of AncGR1 and AncGR2, which were
generated by homology modeling and energy
minimization based on the AncCR and human
GR crystal structures, respectively (16). These
structures are robust to uncertainty in the recon-
struction: Modeling plausible alternate states did
not significantly alter backbone conformation,
interactions with ligand, or intraprotein interactions.
The major structural difference between AncGR1
Fig. 2. Mechanism for switching A
AncGR1’s ligand preference from al-
and AncGR2 involves helix 7 and the loop
preceding it, which contain S106P and L111Q
and form part of the ligand pocket (Fig. 2B and fig.
S8). In AncGR1 and AncCR, the loop’s position is
stabilized by a hydrogen bond between Ser106 and
the backbone carbonyl of Met103 . Replacing Ser106
with proline in the derived GRs breaks this bond
and introduces a sharp kink into the backbone,
which pulls the loop downward, repositioning and
partially unwinding helix 7. By destabilizing this
crucial region of the receptor, S106P impairs
activation by all ligands. The movement of helix
7, however, also dramatically repositions site 111,
bringing it close to the ligand. In this conforma-
tional background, L111Q generates a hydrogen
bond with cortisol’s C17-hydroxyl, stabilizing the
receptor-hormone complex. Aldosterone and DOC
lack this hydroxyl, so the new bond is cortisol-
specific. The net effect of these two substitu-
tions is to destabilize the receptor complex with
aldosterone or DOC and restore stability in a
cortisol-specific fashion, switching AncGR2’s pref-
erence to that hormone. We call this mode of
structural evolution conformational epistasis, be-
cause one substitution remodels the protein back-
bone and repositions a second site, changing the
functional effect of substitution at the latter.
Although S106P and L111Q (“group X” for
convenience) recapitulate the evolutionary switch
in preference from aldosterone to cortisol, the
receptor retains some sensitivity to MR’s ligands,
unlike AncGR2 and extant GRs. We hypothesized
that the other three strictly conserved changes that
occurred between AncGR1 and AncGR2 (L29M,
F98I, and deletion S212D) would complete the
functional switch. Surprisingly, introducing these
“group Y” changes into the AncGR1 and AncGR1 +
X backgrounds produced completely nonfunc-
tional receptors that cannot activate transcription,
even in the presence of high ligand concentrations
(Fig. 3A). Additional epistatic substitutions must
have modulated the effect of group Y, which pro-
vided a permissive background for their evolution
that was not yet present in AncGR1.
The AncCR crystal structure allowed us to
identify these permissive mutations by analyzing
the effects of group Y substitutions (Fig. 3B).
In all steroid receptors, transcriptional activity
depends on the stability of an activation-function
helix (AF-H), which is repositioned when the
ligand binds, generating the interface for tran-
scriptional coactivators. The stability of this
orientation is determined by a network of inter-
actions among three structural elements: the loop
preceding AF-H, the ligand, and helix 3 (17).
Group Y substitutions compromise activation be-
cause they disrupt this network. S212D eliminates
a hydrogen bond that directly stabilizes the AF-H
loop, and L29M on helix 3 creates a steric clash
and unfavorable interactions with the D-ring of
the hormone. F98I opens up space between helix
3, helix 7, and the ligand; the resulting instability
is transmitted indirectly to AF-H, impairing
activation by all ligands (Fig. 3B). If the protein
could tolerate group Y, however, the structures
predict that these mutations would enhance
cortisol specificity: L29M forms a hydrogen
bond with cortisol’s unique C17-hydroxyl, and
the additional space created by F98I relieves a
steric clash between the repositioned loop and
Met108 , stabilizing the key interaction between
Q111 and the C17-hydroxyl (Fig. 3B).
We hypothesized that historical substitutions
that added stability to the regions destabilized by
group Y might have permitted the evolving pro-
tein to tolerate group Y mutations and to complete
the GR phenotype. Structural analysis suggested
two candidates (group Z): N26T generates a new
hydrogen bond between helix 3 and the AF-H
loop, and Q105L allows helix 7 to pack more
tightly against helix 3, stabilizing the latter and,
indirectly, AF-H (Fig. 3B). As predicted, intro-
ducing group Z into the nonfunctional AncGR1 +
X + Y receptor restored transcriptional activity,
indicating that Z is permissive for Y (Fig. 3A).
Further, AncGR1 + X + Y + Z displays a fully
GR-like phenotype that is unresponsive to
aldosterone and DOC and maintains moderate
dosterone to cortisol. (A) Effect of
substitutions S106P and L111Q on the
resurrected AncGR1’s response to hor-
mones. Dashed lines indicate sensitivity
to aldosterone (green), cortisol (purple),
and DOC (orange) as the EC50 for
reporter gene activation. Green arrow
shows probable pathway through a
functional intermediate; red arrow,
intermediate with radically reduced
sensitivity to all hormones. (B) Struc-
tural change conferring new ligand
specificity. Backbones of helices 6 and
7 from AncGR1 (green) and AncGR2
(yellow) in complex with cortisol are
superimposed. Substitution S106P Hormone (log M)
induces a kink in the interhelical loop
of AncGR2, repositioning sites 106 and 111 (arrows). In this background, L111Q forms a new hydrogen bond with cortisol’s unique C17-hydroxyl (dotted red line).
1546 14 SEPTEMBER 2007 VOL 317 SCIENCE www.sciencemag.org
cortisol sensitivity. Both N26T and Q105L are
required for this effect (table S4). Strong epistasis
is again apparent: Adding group Z substitutions
in the absence of Y has little or no effect on ligand-
activated transcription, presumably because the
receptor has not yet been destabilized (Fig. 3A).
Evolutionary trajectories that pass through func-
tional intermediates are more likely than those
involving nonfunctional steps (22), so the only
historically likely pathways to AncGR2 are those
in which the permissive substitutions of group Z
and the large-effect mutations of group X occurred
before group Y was complete (Fig. 3C).
Fig. 3. Permissive substitutions in the
evolution of receptor specificity. (A)
Effects of various combinations of
historical substitutions on AncGR1’s
transcriptional activity and hormone-
sensitivity in a reporter gene assay.
Group Y (L29M, F98I, and S212D) abol-
ishes receptor activity unless groups X
(S106P, L111Q) and Z (N26T and
Q105L) are present; the XYZ combina-
tion yields complete cortisol-specificity.
The 95% confidence interval for each
EC50 is in parentheses. Dash, no acti-
vation. (B) Structural prediction of
permissive substitutions. Models of
AncGR1 (green) and AncGR2 (yellow)
are shown with cortisol. Group X and Y
substitutions (circles and rectangles)
yield new interactions with the C17-
hydroxyl of cortisol (purple) but de-
stabilize receptor regions required for
activation. Group Z (underlined) imparts
additional stability to the destabilized
regions. (C) Restricted evolutionary
paths through sequence space. The
corners of the cube represent states for
residue sets X, Y, and Z. Edges represent
pathways from the ancestral sequence
(AncGR1) to the cortisol-specific combi-
Our discovery of permissive substitutions in the
AncGR1-AncGR2 interval suggested that other
permissive mutations might have evolved even
earlier. We used the structures to predict whether
any of the 25 substitutions between AncCR and
AncGR1 (fig. S5) might be required for the receptor
to tolerate the substitutions that later yielded GR
function. Only one was predicted to be important:
Y27R, which is conserved in all GRs, stabilizes
helix 3 and the ligand pocket by forming a cation-p
interaction with Tyr17 (Fig. 4A). When we reversed
Y27R in the GR-like AncGR1 + X + Y + Z,
activation by all ligands was indeed abolished (Fig.
4B). In contrast, introducing Y27R into AncCR
(Fig. 4B) or AncGR1 (fig. S9) had negligible effect
on the receptor’s response to any hormone. By con-
ferring increased stability on a crucial part of the
receptor, Y27R created a permissive sequence envi-
ronment for substitutions that, millions of years later,
remodeled the protein and yielded a new function.
These results shed light on long-standing issues
in evolutionary genetics. One classic question is
whether adaptation proceeds by mutations of large
or small effect (23). Our findings are consistent with
a model of adaptation in which large-effect muta-
tions move a protein from one sequence optimum
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20 AncGR1+ XYZ
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Hormone (log M)
A Hormone sensitivity (EC50,nM)
Receptor Aldosterone Cortisol DOC
AncGR1 1.0 (0.5,1.7) 6.4 (5.0,8.3) 0.5 (0.3,1.0)
AncGR1 + X 161.0 (119.2,217.4) 16.0 (8.0,31.9) 30.1 (17.9,50.7)
AncGR1 + Y – – –
AncGR1 + XY – – –
AncGR1 + Z 0.5 (0.2,1.4) 6.7 (4.5,10.0) 0.3 (0.1,0.7)
AncGR1 + XZ 200.0 (174.4,228.6) 2.9 (1.5,5.7) 22.4 (11.2,44.7)
AncGR1 + YZ – – 657.7 (491.1,880.7)
AncGR1 + XYZ – 308.3 (135.7,700.5) –
nation (+XYZ). Filled circles at vertices show sensitivity to aldosterone (green), DOC (orange), and cortisol (purple); empty circles, no activation. Red octagons, paths
through nonfunctional intermediates; arrows, paths through functional intermediates with no change (white) or switched ligand preference (green).
Fig. 4. Structural identification of
an ancient permissive substitution.
(A) Comparison of the structures of
AncCR (blue) and AncGR2 (yellow).
Y27R generates a novel cation-p
interaction in AncGR2 (dotted cyan
line), replacing the weaker ances-
tral hydrogen bond (dotted red)
and imparting additional stability
to helix 3. (B) Y27R is permissive
for the substitutions that confer GR
function. Reporter gene activation
by AncGR1 + XYZ (upper right) is
abolished when Y27R is reversed
(lower right). (Left) Y27R has
negligible effect in the AncCR
background (or in AncGR1, fig. S9).
Green, orange, and purple lines
show aldosterone, DOC, and corti-
sol responses, respectively. Green arrows, likely pathway through functional intermediates.
www.sciencemag.org SCIENCE VOL 317 14 SEPTEMBER 2007 1547
to the region of a different function, which smaller-
effect substitutions then fine-tune (24, 25); permis-
sive substitutions of small immediate effect,
however, precede this process. The intrinsic
difficulty of identifying mutations of small effect
creates an ascertainment bias in favor of large-effect
mutations; the ancestral structures allowed us
isolate key combinations of small-effect substitu-
tions from a large set of historical possibilities.
A second contentious issue is whether epistasis
makes evolutionary histories contingent on chance
events (26, 27). We found several examples of
strong epistasis, where substitutions that have very
weak effects in isolation are required for the protein
to tolerate subsequent mutations that yield a new
function. Such permissive mutations create “ridges”
connecting functional sequence combinations and
narrow the range of selectively accessible path-
ways, making evolution more predictable (28).
Whether a ridge is followed, however, may not be a
deterministic outcome. If there are few potentially
permissive substitutions and these are nearly
neutral, then whether they will occur is largely a
matter of chance. If the historical “tape of life”
could be played again (29), the required permissive
changes might not happen, and a ridge leading to a
new function could become an evolutionary road
Our results provide insights into the structural
mechanisms of epistasis and the historical evo-
lution of new functions. GR’s functional speci-
ficity evolved by substitutions that destabilized
the receptor structure with all hormones but
compensated with novel interactions specific to
the new ligand. Compensatory mutations have
been thought to occur when a second substitution
restores a lost molecular interaction (30). Our
findings support this notion, but in a reversed
order: Permissive substitutions stabilized specific
structural elements, allowing them to tolerate
later destabilizing mutations that conferred a new
function (9, 10, 31). We also observed a more
striking mechanism: conformational epistasis, by
which one substitution repositions another resi-
due in three-dimensional space and changes the
effects of mutations at that site. It is well known
that mutations may have nonadditive effects on
protein stability (32), and fitness (9, 33), but we
are aware of few cases (11, 34) specifically docu-
menting new functions or epistasis via confor-
mational remodeling. This may be due to the lack
of ancestral structures, which allow evolutionary
shifts in the position of specific residues to be
determined. Conformational epistasis may be an
important theme in structural evolution, playing a
role in many cases where new gene functions
evolve via novel molecular interactions.
References and Notes
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D. S. Tawfik, Nature 444, 929 (2006).
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Proc. Natl. Acad. Sci. U.S.A. 103, 5869 (2006).
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16. Materials and methods are described in supporting
material on Science Online.
17. R. L. Wagner et al., Nature 378, 690 (1995).
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19. M. J. Benton, Vertebrate Palaeontology (Blackwell
Science, Malden, MA, 2005).
20. P. Janvier, Early Vertebrates (Clarendon Press, Oxford,
21. The one-letter abbreviations for the amino acids used in
this report are F, Phe; I, Ile; L, Leu; M, Met; N, Asn;
P, Pro; Q, Gln; R, Arg; S, Ser; T, Thr; and Y, Tyr. An
example of a substitution is Pro for Ser at codon 106
(S106P), and the deletion is in place of Ser at codon
22. J. M. Smith, Nature 225, 563 (1970).
23. H. A. Orr, Nat. Rev. Genet. 6, 119 (2005).
24. B. Charlesworth, in Evolutionary Innovations,
M. Nitecki, Ed. (Univ. of Chicago Press, Chicago, 1990),
25. H. A. Orr, Evolution Int. J. Org. Evolution 56, 1317
26. W. B. Provine, Origins of Theoretical Population Genetics
(Univ. of Chicago Press, Chicago, 1971).
27. M. C. Whitlock, P. C. Phillips, F. B. G. Moore, S. J. Tonsor,
Annu. Rev. Ecol. Syst. 26, 601 (1995).
28. D. M. Weinreich, N. F. Delaney, M. A. Depristo,
D. L. Hartl, Science 312, 111 (2006).
29. S. J. Gould, Wonderful Life: The Burgess Shale and the
Nature of History (Norton, New York, 1989).
30. A. D. Kern, F. A. Kondrashov, Nat. Genet. 36, 1207
31. E. S. Haag, M. N. Molla, Evolution Int. J. Org. Evolution
59, 1620 (2005).
32. D. Reichmann et al., Proc. Natl. Acad. Sci. U.S.A. 102, 57
33. M. Lunzer, S. P. Miller, R. Felsheim, A. M. Dean, Science
310, 499 (2005).
34. L. Hedstrom, Biol. Chem. 377, 465 (1996).
35. We thank D. Ornoff and J. Bischof for technical
assistance and the Thornton, Redinbo, Phillips, and
Cresko labs for comments. Supported by NIH-R01-
GM081592, NSF-IOB-0546906, and a Sloan fellowship
(J.W.T.), NIH-R01-DK622229 (M.R.R.), and NIH-F32-
GM074398 (J.T.B.). AncCR crystal structure has Protein
Databank identification codes 2Q1H, 2Q1V, and 2Q3Y.
Supporting Online Material
Materials and Methods
Figs. S1 to S10
Tables S1 to S5
21 March 2007; accepted 6 July 2007
Published online 16 August 2007;
Include this information when citing this paper.
A Common Fold Mediates Vertebrate
Defense and Bacterial Attack
Carlos J. Rosado,1,2* Ashley M. Buckle,1* Ruby H. P. Law,1* Rebecca E. Butcher,1,3
Wan-Ting Kan,1,2 Catherina H. Bird,1 Kheng Ung,1 Kylie A. Browne,4 Katherine Baran,4
Tanya A. Bashtannyk-Puhalovich,1 Noel G. Faux,1 Wilson Wong,1,2 Corrine J. Porter,1,2
Robert N. Pike,1 Andrew M. Ellisdon,1 Mary C. Pearce,1 Stephen P. Bottomley,1 Jonas Emsley,5
A. Ian Smith,1,2 Jamie Rossjohn,1,2 Elizabeth L. Hartland,6 Ilia Voskoboinik,4,7
Joseph A. Trapani,4,8 Phillip I. Bird,1 Michelle A. Dunstone,1,6† James C. Whisstock1,2†
Proteins containing membrane attack complex/perforin (MACPF) domains play important roles in
vertebrate immunity, embryonic development, and neural-cell migration. In vertebrates, the ninth
component of complement and perforin form oligomeric pores that lyse bacteria and kill virus-
infected cells, respectively. However, the mechanism of MACPF function is unknown. We
determined the crystal structure of a bacterial MACPF protein, Plu-MACPF from Photorhabdus
luminescens, to 2.0 angstrom resolution. The MACPF domain reveals structural similarity with pore-
forming cholesterol-dependent cytolysins (CDCs) from Gram-positive bacteria. This suggests that
lytic MACPF proteins may use a CDC-like mechanism to form pores and disrupt cell membranes.
Sequence similarity between bacterial and vertebrate MACPF domains suggests that the fold of the
CDCs, a family of proteins important for bacterial pathogenesis, is probably used by vertebrates for
defense against infection.
he membrane attack complex/perforin complement proteins (C6, C7, C8a, C8b, and
(MACPF) domain was originally identi- C9) and perforin (1–3) (fig. S1). These mole-
fied and named as being common to five cules perform critical functions in innate and
1548 14 SEPTEMBER 2007 VOL 317 SCIENCE www.sciencemag.org
Elucidation of phenotypic adaptations: Molecular
analyses of dim-light vision proteins in vertebrates
Shozo Yokoyama*†, Takashi Tada*, Huan Zhang‡, and Lyle Britt§
*Department of Biology, Emory University, Atlanta, GA 30322; ‡Department of Marine Sciences, University of Connecticut, Groton, CT 06340;
and §Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA 98195
Edited by Masatoshi Nei, Pennsylvania State University, University Park, PA, and approved July 14, 2008 (received for review March 12, 2008)
Vertebrate ancestors appeared in a uniform, shallow water envi-
ronment, but modern species fourish in highly variable niches. A
striking array of phenotypes exhibited by contemporary animals is
assumed to have evolved by accumulating a series of selectively
advantageous mutations. However, the experimental test of such
adaptive events at the molecular level is remarkably diffcult. One
testable phenotype, dim-light vision, is mediated by rhodopsins.
Here, we engineered 11 ancestral rhodopsins and show that those
in early ancestors absorbed light maximally (�max) at 500 nm, from
which contemporary rhodopsins with variable �maxs of 480 –525
nm evolved on at least 18 separate occasions. These highly envi-
ronment-specifc adaptations seem to have occurred largely by
amino acid replacements at 12 sites, and most of those at the
remaining 191 (�94%) sites have undergone neutral evolution.
The comparison between these results and those inferred by
commonly-used parsimony and Bayesian methods demonstrates
that statistical tests of positive selection can be misleading without
experimental support and that the molecular basis of spectral
tuning in rhodopsins should be elucidated by mutagenesis analy-
ses using ancestral pigments.
molecular adaptation � rhodopsin
The morphologies and lifestyles of animals in a wide range of environmental conditions have evolved to generate a striking
array of forms and patterns. It is generally assumed that these
variations have been driven by mutations, followed by positive
Darwinian selection. However, it has been remarkably difficult
not only to detect minute selective advantages caused by mo-
lecular changes (1), but also to find genetic systems in which
evolutionary hypotheses can be tested experimentally (2). In the
absence of proper experimental systems, molecular adaptation
in higher eukaryotes has been inferred mostly by using statistical
methods (for examples, see refs. 3–5). For several cases, how-
ever, ancestral molecules have been engineered, allowing studies
of functional changes in the past (6). These analyses demonstrate
that functional changes actually occurred, but they do not
necessarily mean that the new characters were adaptive (7). To
complicate the matter further, evolutionary changes are not
always unidirectional and ancestral phenotypes may reappear
during evolution (8, 9). One effective way of exploring the
mechanisms of molecular adaptation is to engineer ancestral
molecules at various stages of evolution and to recapitulate the
changes in their phenotypes through time. To date, the molec-
ular analyses of the origin and evolution of color vision produced
arguably ‘‘the deepest body of knowledge linking differences in
specific genes to differences in ecology and to the evolution of
species’’ (10). The study of dim-light vision provides another
opportunity to explore the adaptation of vertebrates to different
Rhodopsins. Dim-light vision in vertebrates is mediated by rho-
dopsins, which consist of a transmembrane protein, opsin, and a
chromophore, 11-cis-retinal (11). By interacting with different
opsins, the identical chromophores in different rhodopsins de-
tect various wavelengths of light (reviewed in ref. 12). To explore
the molecular basis of the spectral tuning in rhodopsins, in vitro
assay-based mutagenesis experiments are necessary, in which the
wavelengths of maximal absorption (�maxs) can be measured in
the dark (dark spectra) and/or by subtracting a spectrum mea-
sured after photobleaching from a spectrum evaluated before
light exposure (difference spectra) (for example, see ref. 13). So
far, the �maxs of contemporary rhodopsins measured by using the
in vitro assay vary between 482 and 505 nm (refs. 12 and 14 and
references therein). By using another method, microspectropho-
tometry (MSP), the rhodopsin of a deep-sea fish, shining loose-
jaw (Aristostomias scintillans), has also been reported to have a
�max of 526 nm (15).
To examine whether these �maxs represent the actual variation
of the �maxs of rhodopsins in nature, we isolated the rhodopsins
of migratory fish [Japanese eel (Anguilla japonica) and its close
relative Japanese conger (Conger myriaster)], deep-sea fish [Pa-
cific blackdragon (Idiacanthus antrostomus), Northern lampfish
(Stenobrachius leucopsarus), shining loosejaw (Aristostomias
scintillans), scabbardfish (Lepidopus fitchi), and Pacific viperfish
(Chauliodus macouni)], and freshwater bluefin killifish (Lucania
goodei), which live in diverse light environments (www.fishbase.
org) [see supporting information (SI) Methods and Fig. S1]. The
eel has two paralogous rhodopsins (EEL-A and -B), as do conger
(CONGER-A and -B) and scabbardfish (SCABBARD-A and
-B), whereas the others use one type of rhodopsins (BLACK-
DRAGON, LAMPFISH, LOOSEJAW, VIPERFISH and BFN
KILLIFISH) (16) (see also SI Result 1).
In the in vitro assay, the �maxs of the dark spectra are more
reliable than those of difference spectra (SI Result 2) and,
therefore, unless otherwise specified, the �maxs refer to the
former values throughout the paper. The �maxs were determined
for EEL-A (500 nm), EEL-B (479 nm), CONGER-A (486 nm),
CONGER-B (485 nm), SCABBARD-A (507 nm), SCAB-
BARD-B (481 nm), and BFN KILLIFISH (504 nm) (SI Result
2). The �maxs for LAMPFISH and VIPERFISH could not be
evaluated, but those of their difference spectra were 492 and 489
nm, respectively. Neither dark spectra nor difference spectra
were obtained for BLACKDRAGON and LOOSEJAW. How-
ever, a mutant pigment, which is modeled after LOOSEJAW,
has a difference spectrum �max of 526 nm (see Molecular Basis
of Spectral Tuning). Hence, the range of �480 –525 nm seems to
represent the �maxs of rhodopsins in vertebrates reasonably well.
Author contributions: S.Y. designed research; S.Y., T.T., H.Z., and L.B. performed research;
S.Y. analyzed data; and S.Y. wrote the paper.
The authors declare no confict of interest.
This article is a PNAS Direct Submission.
Data deposition: The sequences reported in this paper have been deposited in the GenBank
database (accession nos. EU407248 –EU407253).
†To whom correspondence should be addressed at: Department of Biology, Rollins Re-
search Center, Emory University, 1510 Clifton Road, Atlanta, GA 30322. E-mail:
This article contains supporting information online at www.pnas.org/cgi/content/full/
© 2008 by The National Academy of Sciences of the USA
13480 –13485 � PNAS � Septmber 9, 2008 � vol. 105 � no. 36 www.pnas.org�cgi�doi�10.1073�pnas.0802426105
The Ecology of Dim-Light and Deep-Sea Vision. One of the critical
times for the survival of animals in shallow water and on land is
at twilight when the most abundant light falls between 400 and
500 nm (17). Many fish, amphibians, birds, and mammals that
live in these environments use rhodopsins with �maxs of �500 nm
(12). In contrast, in deep water, the distribution of light is much
narrower at �480 nm (18). Mature conger, mature eel, thorny-
head, and coelacanth all live at the depths of 200 –1,800 m
(www.fishbase.org). Our data and that of others (19, 20) show
that these fishes achieve their dim-light vision by using rho-
dopsins with �maxs of �480 nm. Because of their �maxs and
specific light environments, the two groups of rhodopsins may be
classified simply as ‘‘surface’’ and ‘‘deep-sea,’’ respectively.
Despite being active at much deeper depths of 3,000 – 4,000 m
(www.fishbase.org), however, Northern lampfish and Pacific
viperfish use rhodopsins with �maxs of �490 nm. The higher
�maxs can be explained by their upward migration at night, and
LAMPFISH and VIPERFISH can be regarded as ‘‘intermedi-
ate’’ rhodopsins. Then, through the use of far-red (�700 nm)
bioluminescence to create an artificial light environment, shining
loosejaw achieves dim-light vision with the ‘‘red-shifted’’ rho-
Japanese eel spawns in the deep sea, the young adults migrate
into freshwater, and the mature fish return to the deep sea for
reproduction. Similarly, Japanese conger spawns in the deep sea,
their larvae hatch near the coast, but they live only in the sea
(www.fishbase.org). For their dim-light vision, young and adult
eels use EEL-A and EEL-B, respectively, whereas congers use
only CONGER-B; CONGER-A is expressed in the pineal
complex (16). The �max of EEL-A (500 nm) ref lects the shallow
freshwater environment, whereas those of EEL-B and CON-
GER-B (480 – 485 nm) match with their light environments in the
deep-sea. The �max of CONGER-A (486 nm) is similar to those
of 470 – 482 nm in the pineal gland-specific pigments of American
chameleon, pigeon, and chicken (reviewed in ref. 12). Hence,
EEL-A is a surface rhodopsin and EEL-B and CONGER-B are
deep-sea rhodopsins. CONGER-A does not ref lect the deep-sea
environment directly; however, because of its �max, CONGER-A
may also be classified as a deep-sea rhodopsin.
Based on considerations of ecology, life history, and �maxs of
rhodopsins, dim-light vision can be classified into biologically
meaningful deep-sea, intermediate, surface, and red-shifted
vision (see SI Result 3 for detailed discussion of the classifications
of other rhodopsins). The corresponding rhodopsins have �maxs
of 479 – 486, 491– 496, 500 –507, and 526 nm, respectively, estab-
lishing the units of possible selection. Consequently, it is possible
that selective force may be able to differentiate even 4 –5 nm of
�max differences of rhodopsins.
Ancestral Rhodopsins. Based on the composite phylogenetic tree
(Fig. 1) (see also SI Result 4 and Fig. S2) of the 11 newly
characterized rhodopsins and 27 others from a wide range of
vertebrate species, we inferred the amino acid sequences of
ancestral rhodopsins. Because most of their rhodopsin genes
have been sequenced partially (Fig. S3), squirrelfish (21) and
cichlid (14) rhodopsins were first excluded from this inference.
The amino acids inferred by using the Jones, Taylor, and
Thornton and Dayhoff models of amino acid replacements of the
PAML program (3) are highly reliable (SI Results 5 and 6, and
Tables S1 and S2).
By introducing a total of 137 amino acid changes into various
rhodopsins (Table S3), we then engineered pigments at nodes
a– k (pigments a– k). The in vitro assays show that pigments a– d
and f– h have �maxs of 501–502 nm, whereas others have �maxs of
496 nm (pigment i) and 482– 486 nm (pigments e, j, and k), which
are also highly reliable (SI Results 5 and 6).
Fig. 1. A composite tree topology of 38 representative rhodopsins in ver-
tebrates. Numbers in ovals are �maxs evaluated from MSP (*), dark spectra, and
difference spectra (†). The numbers in white, blue, black, and red ovals
indicate surface, intermediate, deep-sea, and red-shifted rhodopsins, respec-
tively, whereas those in rectangles indicate the expected values based on the
mutagenesis results. Because of their incomplete data, the amino acid se-
quences of pigments a– k have been inferred by excluding the squirrelfsh,
bluefn killifsh, and cichlid rhodopsins. S-PUN and S-XAN are classifed as
intermediate rhodopsins because of their expected �maxs, but currently avail-
able data are ambiguous. Red- and blue-colored amino acid replacements
indicate the color of the shifts in the �max. The �max of avian ancestral pigment
shows that of the ancestral Archosaur rhodopsin (39). ND, the �max could not
Molecular Basis of Spectral Tuning. Because of the interactions
between the 11-cis-retinal and various amino acids, the �max
shifts caused by mutations in the opposite directions are often
nonsymmetrical (22–24). Hence, to understand the evolutionary
mechanism that has generated the various �maxs of rhodopsins in
nature, we must analyze ‘‘forward’’ amino acid replacements that
actually took place in specific lineages. The reconstruction of
multiple ancestral pigments opens an unprecedented opportu-
nity to study the effects of such forward amino acid replacements
on the �max shift in different lineages.
At present, certain amino acid changes at a total of 26 sites are
known to have generated various �maxs of rhodopsins and other
paralogous visual pigments in vertebrates (25). The amino acid
sequences of the 38 representative rhodopsins differ at 11 of the
26 sites (Fig. 2, second column). Among these, the specific amino
acid replacements at 46, 49, 52, 93, 97, 116, and 164 are unlikely
to have been involved in the spectral tuning (SI Result 7). These
and other amino acid site numbers in this paper are standardized
Yokoyama et al. PNAS � Septmber 9, 2008 � vol. 105 � no. 36 � 13481
pigment a FLFDTTFEAFA YYMLKMTM
pigment b ……….. ……..
pigment c .I……… ……..
pigment d .I……… …PN…
pigment e .I……..S ……..
pigment f ……….. …RA…
pigment g ……….. …RA…
pigment h ……….. …RA…
pigment i ……….. VFLRA…
pigment j …N……S …RA…
pigment k …N.S….S …RA…
pigment m ……….. ……..
CONGER-A .I……..S ..LRA…
EEL-A .I……… …PN…
CONGER-B .I……..S ..L…..
EEL-B T..N……S ……..
CAVEFISH …….I.Y. …RA…
GOLDFISH .I……… …RP…
ZEBRAFISH .I……… …RT…
N-SAM .I…SSM.Y. …RA…
N-ARG .I…SSM.Y. …RA…
S-PUN .I…SSM… …RA…
S-MIC .I…..M… …RA…
S-DIA .I…..M… …RA…
S-XAN .I…..M… …RA…
N-AUR .I…S.M..S …RA.A.
S-SPI .I…S.M.YS …RA.A.
S-TIE .I…S.M.YS …RA.A.
M-VIO .I….SMG.. …RA…
M-BER .I….SMGG. …RA…
BFN KILLIFISH .I……… …RA…
O-NIL ……….. …RA…
X-CAU ……….S ..LRA…
THORNYHEAD L..N……S …RA…
LAMPFISH ……MQ… …RA…
SCABBARD-A .I…….Y. VFLRA…
SCABBARD-B …N……S VFLRA…
VIPERFISH …N.S….S …RA.A.
BLACKDRAGON …N.S….S …RA.A.
LOOSEJAW …N…..YI ..FRAL.I
COELACANTH ….VS.Q..S ……G.
CLAWED FROG L.LNV…… …….L
SALAMANDER L..NVS….. ……..
CHAMELEON L..N……. …PT…
PIGEON M………. ……..
CHICKEN M………. ……..
ZEBRA FINCH M………. ……..
BOVINE LM……… …PH…
DOLPHIN LV.N……S …SR…
ELEPHANT LV.N……. ……..
Fig. 2. Amino acids at the 11 previously known (25) and newly found critical
residues of rhodopsins. The numerical column headings specify the amino acid
positions, and the third column describes the newly discovered critical resi-
dues. Shades indicate amino acid replacements that are unlikely to cause any
�max shifts (SI Result 7). Dots indicate the identity of the amino acids with those
of pigment a. The ancestral amino acids that have a posterior probability of
95% or less are underlined.
by those of the bovine rhodopsin (BOVINE). From the mu-
tagenesis results (SI Result 8 and Table S4), four key observations
of evolutionary significance emerge.
First, the �maxs of most contemporary rhodopsins can be
explained largely by a total of 15 amino acid replacements at 12
sites. Namely, significant �max shifts have been caused by 4 of the
11 currently known sites (D83N, E122M, E122Q, F261Y, A292S,
and S292I) as well as newly discovered sites Y96V, Y102F,
E122I, M183F, P194R, N195A, M253L, T289G, and M317I (Fig.
2, third column). Therefore, the functional differentiation of
vertebrate rhodopsin was caused mostly by only �3% of 354
amino acid sites.
Second, 4 of the 15 critical amino acid replacements occurred
multiple times during rhodopsin evolution: D83N (seven times),
A292S (nine times), F261Y (five times), E122Q (two times), and
D83N/A292S (five times) (Fig. 1). Such extensive parallel
changes strongly implicate the importance of these and other
amino acid replacements at the 12 sites in the functional
adaptation of vertebrate dim-light vision.
Third, we uncovered new types of amino acid interactions.
A292S usually decreases the �max of rhodopsin by �10 nm (12)
(see also pigments c and g in Table S4). Much to our surprise,
when A292S was introduced into pigment d (Fig. 1), it did not
decrease the �max at all. However, when the reverse mutation,
S292A, was introduced into CONGER-A, a descendant of
pigment d, the mutant rhodopsin increased the �max by 12 nm,
explaining the �max of pigment d reasonably well. From the latter
analysis alone, we may erroneously conclude that the �max of
CONGER-A was achieved by A292S; instead, it was achieved
purely by the interaction of three amino acid replacements
(P194R, N195A, and A292S) (SI Result 8). Moreover, F261Y in
pigment b increases the �max by 10 nm, and CAVEFISH, a
descendant of pigment b, should have a �max of �510 nm, but the
observed value is 504 nm (12), where the effect of F261Y was
countered by E122I (for more details, see SI Result 8).
To study the molecular basis of spectral tuning, quantum
chemists analyze the interactions between the 11-cis-retinal and
amino acids that are located in the retinal binding pocket, within
4.5 Å of the 11-cis-retinal (26, 27). The residue 292 is �4.5 Å
away from the 11-cis-retinal and is very close to the functionally
critical hydrogen bonded network (28). However, the tertiary
structure of the bovine rhodopsin (28) shows that the residues
194 and 195 are �20 Å away from residue 292 and are not even
in the transmembrane segments. This magnitude of �max shift
and the distance of interacting amino acids are totally unex-
The fourth significant observation is that the �max shifts of
rhodopsins can be cyclic during vertebrate evolution. In partic-
ular, F261Y reversed the direction of �max shift four times (Fig.
1). If F261Y preceded E122I in the CAVEFISH lineage, then the
functional reversions occurred five times.
Paleontology, Ecology, and Habitats. The ancestors of bony fish most
likely used rhodopsins with �maxs of �500 nm (Fig. 1). What types
of light environment did these ancestors have? The origin of many
early vertebrate ancestors is controversial, but that of bony fish
ancestors is clear (29). The fossil records from late Cambrian and
early Ordovician, �500 Mya, show that the ancestors of bony fish
lived in shallow, near-shore marine environments (30 –32). There-
fore, pigment a must have functioned as a surface rhodopsin and its
�max would be consistent with that role. Interpolating from the
ancestral and contemporary rhodopsins, it is most likely that
pigments b– d and f– h (�max � 501–502 nm) were also surface
rhodopsins, pigment i (496 nm) was an intermediate rhodopsin, and
pigments e, j, and k (480 – 485 nm) were deep-sea rhodopsins (Fig.
1). From their predicted �maxs, it is also likely that pigments q, r, s,
and v were intermediate rhodospins and pigment u was a deep-sea
rhodopsin (Fig. 1).
Based on the four types of dim-light vision, vertebrates show
six different evolutionary paths (Fig. 1). First, surface vision has
been maintained in a wide range of species, from eels to
mammals. Second, the transition of surface 3 intermediate
vision also occurred in a wide range of species. Third, many
deep-sea fish have achieved the directed transitions of surface 3
intermediate 3 deep-sea vision. The three additional changes
are surface 3 intermediate 3 surface vision (some squirrelfish),
surface 3 intermediate 3 deep-sea 3 intermediate vision
(some squirrelfish and Pacific viperfish), and surface 3 inter-
mediate 3 deep-sea 3 red-shifted vision (shining loosejaw), all
showing that the evolution of dim-light vision is reversible.
Molecular Evolution. In vertebrate rhodopsins, several amino acid
replacements occurred multiple times and, furthermore, the
biologically significant �max shifts occurred on at least 18 sepa-
rate occasions (Fig. 1). These observations strongly suggest that
the 15 amino acid changes have undergone positive selection. To
search for positively selected amino acid sites, we applied the
13482 � www.pnas.org�cgi�doi�10.1073�pnas.0802426105 Yokoyama et al.
Table 1. Results from the NEB and BEB analyses
Rhodopsins Model* NEB BEB
Squirrelfsh M2a 50 162 213 214 50 162 213 214
M8 37 50 162 213 214 37 50 112 162
213 214 217
Squirrelfsh and other fsh M2a 162 212 162, 212
M8 162, 212 162, 212
Coelacanth and tetrapods M2a None None
M8 None None
All M2a None None
M8 None None
Sites with P � 0.01 levels are in bold.
*The null models and other parameters are given in Table S5.
naive-empirical-Bayes (NEB) and Bayes-empirical-Bayes (BEB)
approaches of maximum-likelihood-based Bayesian method (3,
33) and parsimony method (4) to four sets of rhodopsin genes:
(i) 11 squirrelfish genes; (ii) the squirrelfish rhodopsins and the
bluefin killifish, cichlid, and deep-sea fish genes, excluding the
coelacanth gene; (iii) the coelacanth and 9 tetrapod genes; and
(iv) all 38 genes (Fig. 1).
Using the parsimony method, we could not find any positively
selected amino acid sites. Using the Bayesian methods, however,
a total of eight positively selected sites (positions 37, 50, 112, 162,
212, 213, 214, and 217) are predicted (Table 1). The Bayesian
results reveal two characteristics. First, the positively selected
amino acid sites are predicted only for relatively closely related
genes, involving squirrelfish genes, but they disappear as more
distantly related genes are considered together. It is also sur-
prising that none of these predicted sites coincide with those
detected by mutagenesis experiments. Second, different amino
acids at these predicted sites do not seem to cause any �max-shifts
(SI Result 9, Tables S5–S8, and Fig. S4).
Considering 17 closely related cichlid rhodopsin genes, 26
positively selected sites have also been predicted (34). Again,
none of the different amino acids at these sites seem to cause any
�max shifts and, furthermore, when we add the other 23 genes
(the eel, conger, cavefish, goldfish, zebrafsh, deep-sea fish, and
tetrapod rhodopsin genes in Fig. 1) in the Bayesian analyses, all
positively selected sites disappear (SI Result 9)! Why can posi-
rhodopsins. According to their �maxs and light environments,
rhodopsins are classified into four groups: deep-sea (�480 – 485
nm), intermediate (�490 – 495 nm), surface (�500 –507 nm), and
red-shifted (�525 nm) rhodopsins. Our mutagenesis results
establish five fundamental features of molecular evolution that
cannot be learned from the standard statistical analyses of
protein sequence data.
First, mutagenesis experiments can offer critical and decisive
tests of whether or not candidate amino acid changes actually
cause any functional changes. Second, the same amino acid
replacements do not always produce the same functional change
but can be affected by the amino acid composition of the
molecule. Therefore, the likelihood of parallel amino acid
replacements, which may or may not result in any functional
change, can overestimate the actual probability of functional
adaptations (SI Result 9).
Third, similar functional changes can be achieved by differ-
ent amino acid replacements; for example, D83N/A 292S,
P194R/N195A/A 292S, and E122Q decrease the �max by 14 –20
nm (Table S4). Thus, by simply looking for parallel replace-
ments of specific amino acids, one can fail to discover other
amino acid replacements that generate the same functional
change, thereby underestimating the chance of finding func-
tively selected sites be inferred more often in closely related
genes than in distantly related genes? When nucleotide changes
occur at random, the proportions of nonsynonymous and syn-
onymous mutations are roughly 70% and 30%, respectively.
Hence, under neutral evolution, or even under some purifying
selection, closely related molecules can initially accumulate
more nonsynonymous changes than synonymous changes. How-
ever, as the evolutionary time increases, synonymous mutations
will accumulate more often than nonsynonymous mutations
(35). The differential rates of synonymous and nonsynonymous
nucleotide substitutions during evolution may explain the pre-
diction of false-positives among the relatively closely related
rhodopsins. Or, such inferences may also be affected by the
statistical procedures (36).
As we saw earlier, D83N, Y96V, Y102F, E122I, E122M,
E122Q, P194R, N195A, and A292S decreased the �max, whereas
M183F, M253L, F261Y, T289G, S292I, and M317I increased it.
These changes are located within or near the transmembrane
segments, but most of the amino acid replacements at the
remaining 191 neutral sites are scattered all over the rhodopsin
Fig. 3. Secondary structure of BOVINE (26) with a total of 203 naturallymolecule (Fig. 3).
occurring amino acid replacements in the 38 vertebrate rhodopsins, where
seven transmembrane helices are indicated by dotted rectangles. The amino Discussion
acid changes that cause blue and red shifts in the �max are shown by blue and
When moving into new dim-light environments, vertebrate red circles, respectively, and those that are unlikely to cause any �max shifts are
ancestors adjusted their dim-light vision by modifying their indicated by black circles.
Yokoyama et al. PNAS � Septmber 9, 2008 � vol. 105 � no. 36 � 13483
Fourth, not only can the identical mutations in different
pigments cause different magnitudes of �max shift, but also
mutations in the opposite directions often shift the �max to the
opposite directions by different magnitudes. Hence, if we are
interested in elucidating the evolutionary mechanisms of func-
tional and phenotypic adaptations, we have to study forward
mutations by using appropriate ancestral molecules rather than
introducing mutations into contemporary molecules.
Fifth, even when the phylogenetic position of a molecule is
unknown, its functional assay can clarify the molecular evolution
of functional adaptation. For example, the phylogenetic position
of LAMPFISH is uncertain (Fig. 1). However, because the
E122Q that decreased the �max of pigment f is different from the
other critical amino acid replacements in evolutionarily closely
related rhodopsins, we can easily establish an independent origin
of the functional change in LAMPFISH. To explore adaptive
evolution of certain traits, therefore, both functional and mo-
lecular analyses of such traits are necessary.
Our analyses demonstrate that it is important to relate the
functional changes of molecules to the ecological or behavioral
changes that presumably caused the functional and phenotypic
changes in the first place. Studying functional changes of ances-
tral rhodopsins and relating them to the associated environmen-
tal changes of organisms’ habitats, we have established the
mechanisms of functional adaptation of dim-light vision in
vertebrates. To fully appreciate how adaptive evolution of dim-
light vision has occurred, it is essential that the effects of critical
amino acid changes on the �max shift are studied at the chemical
level. Quantum chemical analyses of these amino acid changes
will lead to a better understanding of the chemical basis of
adaptive evolution of visual pigments and significantly enhance
our understanding of the chemical basis of phototransduction in
Materials and Methods
Samples and Molecular Cloning of Rhodopsin Genes. High molecular weight
DNAs of the fve deep-sea fsh (Northern lampfsh, scabbardfsh, Pacifc viper-
fsh, Pacifc blackdragon, and shining loosejaw) were isolated from their body
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CONGER-A, CONGER-B (Japanese conger), EEL-A, EEL-B (Japanese eel), CAVE-
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relfsh), BFN KILLIFISH (bluefn killifsh), O-NIL, X-CAU (cichlids), THORNYHEAD
(thornyhead), LAMPFISH (Northern lampfsh), SCABBARD-A, SCABBARD-B
(scabbardfsh), VIPERFISH (Pacifc viperfsh), BLACKDRAGON (Pacifc black-
dragon), LOOSEJAW (shining loosejaw), COELACANTH (coelacanth), CLAWED
FROG (African clawed frog), SALAMANDER (tiger salamander), CHAMELEON
(American chameleon), PIGEON (pigeon), CHICKEN (chicken), ZEBRA FINCH
(zebra fnch), BOVINE (bovine), DOLPHIN (bottlenose dolphin), and ELEPHANT
(African elephant) (refs. 12, 14, 19, 21, 37, and 38 and references therein).
Based on the phylogenetic-tree topology in Fig. 1, we inferred the amino acid
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ancestral pigments were engineered by introducing a series of mutations into
several contemporary rhodopsins (Table S3). All necessary mutations in recon-
structing ancestral rhodopsins as well as forward and reverse mutations were
introduced by using the QuikChange site-directed mutagenesis kit (Strat-
agene). To rule out spurious mutations, the DNA sequences of the mutant
rhodopsins were sequenced.
ACKNOWLEDGMENTS. We thank P. Dunham, J. Lucchesi, M. Nei, Y. Tao, R.
Yokoyama, and two anonymous reviewers for their helpful comments, B.G.
Hall for his extensive editorial comments and many suggestions, N. Takenaka
for her considerable technical contribution to this research, and R. Crouch for
the 11-cis-retinal. This work was supported by the National Institutes of Health
and Emory University.
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Yokoyama et al. PNAS � Septmber 9, 2008 � vol. 105 � no. 36 � 13485
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