Department of Biology, Rollins Research Center, Emory University
Correspondence: E-mail: syokoya{at}emory.edu.
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Key Words: M/LWS pigments adaptive evolution positive selection parallel evolution vertebrates
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Color vision in many vertebrates has been generated by paralogous RH2 (rhodopsin-like), SWS1 (short wavelengthsensitive type 1), SWS2 (short wavelengthsensitive type 2), and M/LWS (middle and long wavelengthsensitive) pigments in cone photoreceptor cells (S. Yokoyama and R. Yokoyama 1996; Yokoyama 2000a; Ebrey and Koutalos 2001). Each of these visual pigments consists of an apoprotein, an opsin, and the light-sensitive chromophore, either 11-cis-retinal or 11-cis-3, 4-dehydroretinal. The functions of the RH2, SWS1, SWS2, and M/LWS pigments can be characterized by their wavelengths of maximal absorption (max) of 470510 nm, 360430 nm, 440460 nm, and 510560 nm, respectively (Yokoyama 2000a; Ebrey and Koutalos 2001). Among the four groups of visual pigments, the genetics and evolution are best understood for M/LWS pigments; that is, most ancestral M/LWS pigments had
max values of
560 nm, and the
max values of all contemporary M/LWS pigments can be explained fully by various combinations of amino acid replacements S180A, H197Y, Y277F, T285A, and A308S, which is known as the "five-sites rule" (Yokoyama and Radlwimmer 2001). Having this well-established genetic information, we can explore the possibility of positive selection for the spectral tuning of M/LWS pigments at the molecular level.
Positive Darwinian selections at individual amino acid sites are often inferred by using maximum likelihood-based Bayesian method (Nielsen and Yang 1998; Yang 1997; Yang et al. 2000; Yang and Nielsen 2002) and parsimony-based method (Suzuki and Gojobori 1999; Suzuki, Gojobori, and Nei 2001). Unfortunately, because only a small number of specific amino acid changes cause the max shift of M/LWS pigments, these statistical methods are expected to be ineffective in detecting positively selected amino acid sites (Suzuki and Nei 2004). In particular, the parsimony method requires a large number of sequences to obtain any statistically significant results, while the Bayesian method may predict a significant proportion of false positives (Suzuki and Nei 2001, 2004; Zhang 2004). To detect positively selected amino acid changes, therefore, we propose a new method that requires the knowledge of specific functions of the protein under consideration at all nodes in a phylogenetic tree. Here, considering 29 representative M/LWS pigments that are sampled from a diverse range of vertebrate species, we then identify three positively selected amino acid sites 180, 277, and 285. Because positively selected M/LWS pigments are found not only in animals with red-green color vision but also in those with red-green color blindness, the results suggest that both red-green color vision and color blindness have undergone adaptive evolution independently in different lineages.
![]() |
Materials and Methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
To calculate the number of synonymous (cs) and nonsynonymous (cn) changes per codon site, we have considered the nucleotide sequences between codons 51 and 322 of the 29 opsin genes. These sites are important to compare because they encode amino acids spanning from transmembrane (TM) helix I to helix VII (Palczewski et al. 2000), where the light-sensitive chromophore and an opsin interact directly or indirectly and determine the max of visual pigments (Yokoyama 2000a; Ebrey and Koutalos 2001; Ebrey and Takahashi 2002; Shi and Yokoyama 2003). These 816 nucleotides at all nodes were then inferred by using the likelihood-based Bayesian method (Yang 1997), where paralogous bovine RH1 pigment (GenBank accession number M21606), goldfish RH2 pigment (L11865), chameleon SWS1 pigment (AF109373), and chicken SWS2 pigment (M92037) were used as the out-group. From these sequences, the cn and cs values were evaluated by taking the averages of those over all possible pathways between two codons at two closest nodes compared (for such procedures, see Suzuki and Gojobori 1999; Suzuki, Gojobori, and Nei 2001).
If we let L0 and L1 be the total lengths of the B0 and B1 branches in the phylogenetic tree, respectively, then the proportions of nucleotide substitutions in the B0 and B1 branches are L0/LT and L1/LT, respectively, where LT = L0 + L1. Based on these relative frequencies, we evaluated the binomial probabilities of finding the observed cs value or more biased number of synonymous changes (Ps) and those of finding the observed cs value or more biased number of nonsynonymous changes (Pn).
To study the parallel evolution of different amino acid changes, we have evaluated the probability of observing a specific amino acid change (A B) in a certain branch. This probability is calculated as the product of two quantities: (1) the probability (
) that the ancestral amino acid, A, is replaced by another amino acid and (2) the probability (ß) that the amino acid change A
B occurs, given that A is replaced by another amino acid. To evaluate the
value, we first identify the number of amino acid sites (NA) where the vertebrate ancestor had a specific amino acid, A. For these sites, we may count the total number (NC) of changes from A to any other amino acids during vertebrate evolution. Then, NC/NA gives the average number of changes (K) from A to other amino acids during the entire vertebrate evolution or the average number of amino acid changes/site/tree (see also Yokoyama and Takenaka 2004). Because the extent of sequence divergence in the M/LWS pigments is generally very low and no reverse mutation has occurred,
= 1 exp[K x L/LT] for a specific branch of a length of L. Similarly, the ß value is the proportion of the transition A
B among all amino acid changes that occur from A to any other amino acids. Note that Zhang and Kumar (1997) have also proposed a method of evaluating the probability that parallel changes occur, but their method cannot be applied here because the B0 and B1 branches cannot be analyzed separately.
In Vitro Assays of Mutant Cavefish (P558) Pigments
Cavefish (P558) and its mutant cDNAs in an expression vector, pMT5, were expressed in COS1 cells by transient transfection (Yokoyama 2000b). The visual pigments were regenerated by incubating these opsins with 11-cis-retinal (Storm Eye Institute, Medical University of South Carolina, Charleston) in the dark. The resulting visual pigments were then purified by immunoaffinity chromatography by using monoclonal antibody 1D4 Sepharose 4B (The Cell Culture Center, Minneapolis, Minn.). The absorption spectra of visual pigments were recorded at 20°C using a Hitachi (Tokyo, Japan) U-3000 dual-beam spectrophotometer. Recorded spectra were analyzed by using SIGMAPLOT software (Jandel, San Rafael, Calif.).
Point mutations were generated by using QuickChange site-directed mutagenesis kit (Stratagene, La Jolla, Calif.). To rule out spurious mutations, the mutated opsins were sequenced by using the Sequitherm Excel II long-read kits (Epicentre Technologies, Madison, Wis.) with dye-labelled M13 forward and reverse primers. Sequencing reactions were run on a LI-COR 4200LD automated DNA sequencer (LI-COR, Lincoln, Nebr.).
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The four sets of cs values in table 2 exemplify the number of synonymous changes in the two types of branches. At these sites, the cs values in the B0 and B1 branches do not deviate significantly from the expected ratio of 0.67:0.33. In fact, at all 272 codons, the binomial probabilities (Ps) of the observed cs values or more biased number of synonymous changes are much larger than 0.05, suggesting that synonymous substitutions have followed neutral evolution (see also table 2). On the other hand, the corresponding probabilities (Pn) for nonsynonymous substitutions are much smaller than 1% at sites 180, 222, 277, and 285 (table 2). Fisher's exact test also shows that the cn and cs values in the B0 and B1 branches differ significantly at sites 277 and 285 with the probabilities of 0.012 and 0.011, respectively. It should be noted, however, that the relative cn and cs values at sites 180, 222, 277, and 285 in the B1 branches are 8:3, 6:3, 8:1, and 7:2, respectively, none of which deviates significantly from their expected ratios of 2:1 (table 2). Thus, the excess numbers of nonsynonymous substitutions at the four sites in the B1 branches over the B0 branches could have been caused either by relaxed selective constraints or by positive selection.
|
|
The cavefish (P530), gecko (P521), human (P530)/macaque (P530) ancestor, and wallaby (P528) have branch lengths of 0.57, 0.70, 0.03, and 0.25, respectively. The two relevant branch lengths for deer (P531) are 0.06 and 0.09, while those for squirrel monkey (P532) are 0.02 and 0.02 (fig. 1). If selective force was not operating, the probability of observing S180A, Y277F, and T285A in all six pigments would be on the order of 1010 109 and that of the occurrence of all three amino acid replacements in each pigment ranges from 8.2 x 108 to 2.9 x 103 (table 3). Consequently, the probability that the six MWS pigments have incorporated the three identical amino acid changes by chance would be on the order of 1028.
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Note that the rodent and rabbit ancestor has a branch length of 0.06, and under neutral evolution, H197Y should have occurred with the probability of 0.002, which is a rare event. Figure 1 also shows that two amino acid changes (S180A and A308S) have occurred in dolphin (P524), mouse (P508), and rabbit (P509) independently, whose branch lengths are 0.26 (0.06 + 0.20), 0.24, and 0.24, respectively. Under neutral evolution, S180A and A308S should have occurred in the respective branches with the probabilities of 2.8 x 103, 1.3 x 103, and 1.3 x 103 and the parallel evolution of the two amino acid changes in the three lineages with the probability of 4.1 x 109. Because they shift the max of M/LWS pigments (Sun, Macke, and Nathans 1997), it is likely that H197Y and A308S have also been subjected to positive selection.
Parsimony-Based and Likelihood-Based Methods
It is of interest to see how currently available statistical methods perform in detecting positively selected sites for the M/LWS opsin gene data in figure 1. In applying the parsimony method to our data, we considered two situations: (1) the B0 and B1 branches are not distinguished (Suzuki and Gojobori 1999; Suzuki, Gojobori, and Nei 2001) and (2) the two types of branches are distinguished. For the latter case, we first evaluated the cn and cs values for the B0 branches and then computed the binomial probability of observing the cn and more biased numbers of nonsynonymous changes in the B1 branches. As predicted by Suzuki and Nei (2004), we could not find any positively selected codon sites for both cases.
In applying the Bayesian method (Yang 1997; see also Yang and Nielsen 2002) to our data, we also considered two situations: (1) the nonsynonymous/synonymous substitution ratios () are uniform for all branches in figure 1 and (2) the
values for the B0 and B1 branches differ from each other. Again, we could not identify any positively selected amino acid site. In these Bayesian inferences, we used 0.2 and 3.14 as the input
values but the results were the same.
Thus, when we consider the specific pattern of functional differentiations of the M/LWS pigments in figure 1, we cannot detect any positively selected amino acid sites using currently available parsimony and Bayesian methods.
Red-Green Color Vision
In many species, including human, both MWS and LWS pigments are required for red-green color vision. Having only one type of M/LWS pigments, however, many nonmammalian species have devised new methods of achieving red-green color vision. Note that the max values in table 1 are based on visual pigments with 11-cis-retinal chromophore, and their variability has been generated by a total of five amino acid changes (Yokoyama and Radlwimmer 2001). Certain lampreys, bony fishes, amphibians, and reptiles also use 11-cis-3, 4-dehydroretinal. The chromophore switches can be brought about by such factors as environmental changes in light, season, migration, temperature, and hormone (e.g., see S. Yokoyama and R. Yokoyama 1996). Replacing 11-cis-retinal by 11-cis-3, 4-dehydroretinal, the visual pigment can detect a longer wavelength (Whitmore and Bowmaker 1989; Harosi 1994; Kawamura and Yokoyama 1998). Importantly, many nonmammalian species have RH2 pigments with
max values of
500 nm (Yokoyama 2000a). Using 11-cis-3, 4-dehydroretinal, these RH2 pigments can achieve
max values
530 nm, functionally very similar to MWS pigments (Kawamura and Yokoyama 1998). Thus, without having MWS pigments, many organisms can achieve red-green color vision using LWS and RH2 pigments using the 11-cis-3, 4-dehydroretinal chromophore.
In addition, cone photoreceptor cells of many amphibians, birds, and reptiles contain colored oil droplets (Walls 1942; Lythgoe 1979). For example, the cones of the chicken contain red, orange-yellow, blue, and green oil droplets (Bowmaker and Knowles 1977). The light passes through the oil droplets, essentially providing colored filters that adjust the max of a photoreceptor cell according to the color of its oil droplet (Bowmaker and Knowles 1977). Thus, without MWS pigments (table 1), the chicken can still have red-green color vision. Importantly, there is a strong association between the types of visual pigments and those of colored oil droplet in a certain cone cell type (Bowmaker and Knowles 1977; Bowmaker 1991). Therefore, despite the introduction of colored oil droplets, the amino acid sequences of various opsins are still subjected to highly conserved evolutionary changes (fig. 1).
A Possible Selective Advantage of Red-Green Color Blindness Over Red-Green Color Vision
We have seen that MWS pigments have been positively selected in gecko, deer, and wallaby. These species use neither 11-cis-3, 4-dehydroretinal nor colored oil droplets and are red-green color blind (Walls 1942; Lythgoe 1979; Bowmaker 1991). At the same time, MWS pigments have also been positively selected in cavefish, human, and squirrel monkey, all of which have red-green color vision. In cavefish and human, the MWS and LWS opsins are encoded by duplicated opsin genes, whereas, in the squirrel monkey, the MWS, LWS, and third allelic pigments with an intermediate max value have been maintained. In fact, the three-allele system is widely spread in many New World monkeys and must be maintained by some type of balancing selection (Surridge, Osorio, and Mundy 2003).
The intriguing observation is that the positively selected MWS pigments come not only from animals with red-green color vision but also from those with red-green color blindness. This means that both red-green color vision and red-green color blindness have undergone adaptive evolution independently in different lineages. This finding contradicts a widely accepted notion that animals with red-green color vision have a selective advantage over those with color blindness (e.g., see Surridge, Osorio, and Mundy 2003), but it is compatible with the observation that the majority of mammalian species and many other species are red-green color blind (Walls 1942; Jacobs 1993). One may then wonder how color blindness, instead of red-green color vision, can be positively selected in certain animals.
One characteristic of red-green color vision is, of course, the capacity of organisms to discriminate red and green colors. Red-green color vision in higher primates is believed to have evolved to facilitate the detection of yellow and red fruits against dappled foliage (e.g., see Mollon 1991). A recent literature survey of 43 primate species, however, shows that red and yellow fruits combined are consumed less frequently than green fruits (Dominy 2003). For detecting such cryptic fruits, color blindness may improve detection of edges and contours (Regan et al. 2001). Evidence is scant and is sometimes controversial, but several observations are consistent with the idea that animals with color blindness can have a selective advantage over those with red-green color vision: (1) color-blind people can detect color-camouflaged objects much better than those with red-green color vision (Morgan, Adam, and Mollon 1992); (2) Geoffroy's marmosets with red-green color vision find significantly fewer color-camouflaged food than noncamouflaged food, but there is no difference in the ability of color-blind individuals to detect the camouflaged versus noncamouflaged food (Caine, Surridge, and Mundy 2003); (3) color-blind individuals of capuchin monkeys, crab-eating monkeys, and chimpanzees are capable of discriminating color-camouflaged stimuli, while those with red-green color vision failed the task (Saitou et al. 2004); (4) field studies of emperor and saddleback tamarins show that red-green color vision of females does not provide an advantage for detecting yellow fruit rewards against mature foliage (Dominy et al. 2003); and (5) figs and palm fruits are generally more cryptically colored in the regions where primates with mixed capabilities for chromatic discrimination live than regions where those with red-green color vision live (Dominy, Svenning, and Li 2003). It is also suspected that after dark, color-blind individuals have lower light perception thresholds than trichromats, which may give a selective advantage in the dark (Verhulst and Maes 1998), but Simunovic, Regan, and Mollon (2001) do not find such evidence.
So far, comparative behavioral analyses of red-green color vision are limited to primates. This is because many primates are highly polymorphic with respect to the level of their capabilities of discriminating red and green color. Unfortunately, we do not have any information on the levels of such polymorphisms in gecko, deer, wallaby, and other nonprimate species. Note that S180 and A180 in human LWS pigments are segregating with frequencies of 60% and
40%, respectively (Winderickx et al. 1992), causing
7 nm difference in the
max values (Merbs and Nathans 1992; Yokoyama and Radlwimmer 2001). To conduct behavioral and field experiments of evolution of red-green color vision, therefore, it would be of considerable interest to evaluate the levels of amino acid polymorphisms at critical sites 180, 197, 277, 285, and 308 of M/LWS pigments in nonprimate species.
Our evolutionary genetic analyses and behavioral results obtained by others suggest that both red-green color vision and color blindness have been strongly selected independently in different lineages. Certainly, the widely accepted notion that animals with red-green color vision have a selective advantage over those with color blindness does not seem to be as general as previously believed. To better understand the evolution of red-green color vision in general, it will be necessary to establish biological and ecological conditions under which organisms with red-green color vision fit better than those with red-green color blindness or vice versa. To solve such problems, behavioral studies of animals with different color sensitivities within and between species in different color environments will offer an excellent opportunity. It is also necessary to understand why certain color-blind species have shifted their max values from 560 to 510530 nm, while others maintained theirs at
560 nm.
![]() |
Acknowledgements |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
Footnotes |
---|
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Asenjo, A. B., J. Rim, and D. D. Oprian. 1994. Molecular determinants of human red/green color discrimination. Neuron 12:11311138.[ISI][Medline]
Bowmaker, J. K. 1991. Evolution of photoreceptors and visual pigments. Pp. 6381 in J. R. Cronly-Dillon and R. L. Gregory, eds. Evolution of the eye and visual pigments. CRC Press, Boca Raton, Fla.
Bowmaker, J. K., and A. Knowles. 1977. The visual pigments and oil droplets of the chicken retina. Vision Res. 17:755764.[CrossRef][ISI][Medline]
Caine, N. G., A. K. Surridge, and N. I. Mundy. 2003. Dichromatic and trichromatic Callithrix geoffroyi differ in relative foraging ability for red-green color-camouflaged and non-camouflaged food. Int. J. Primatol. 24:11631175.[CrossRef][ISI]
Carroll, R. L. 1988. Vertebrate paleontology and evolution. W. H. Freeman & Co., New York.
Chinen, A., T. Hamaoka, Y. Yamada, and S. Kawamura. 2003. Gene duplication and spectral diversification of cone visual pigments of zebrafish. Genetics 163:663675.
Deeb, S., M. J. Wakefield, T. Tada, L. Marotte, S. Yokoyama, and J. A. Marshall Graves. 2003. The cone visual pigments of an Australian marsupial, the Tammar wallaby (Macropus eugenii): sequence, spectral tuning, and evolution. Mol. Biol. Evol. 20:16421649.
Dominy, N. J. 2003. Color as an indicator of food quality to anthropoid primates: ecological evidence and an evolutionary scenario. Pp. 599628 in C. F. Ross and R. F. Kay, eds. Anthropoid origins: new visions. Kluwer Academic, New York.
Dominy, N. J., P. A. Garber, J. C. Bicca-Marques, and M. A. D. O. Azevedo-Lopes. 2003. Do female tamarins use visual cues to detect fruit rewards more successfully than do males? Anim. Behav. 66:829837.[CrossRef][ISI]
Dominy, N. J., J.-C. Svenning, and W.-H. Li. 2003. Historical contingency in the evolution of primate color vision. J. Hum. Evol. 44:2545.[CrossRef][ISI][Medline]
Dulai, K. S., J. K. Bowmaker, J. D. Mollon, and D. M. Hunt. 1994. Sequence divergence, polymorphism and evolution of the middle-wave and long-wave visual pigment genes of great apes and old world monkeys. Vision Res. 34:24832491.[CrossRef][ISI][Medline]
Ebrey, T., and Y. Koutalos. 2001. Vertebrate photoreceptors. Prog. Retin. Eye Res. 20:4994.[CrossRef][ISI][Medline]
Ebrey, T. G., and Y. Takahashi. 2002. Photobiology of retinal proteins. Pp. 101133 in T. P. Coohil and D. P. Valenzeno, eds. Photobiology for the 21st century. Valdenmar, Overland Park, Va.
Endler, J. A. 1991. Variation in the appearance of guppy color patterns to guppies and their predators under different visual conditions. Vision Res. 31:587608.[CrossRef][ISI][Medline]
Fasick, J. I., T. W. Cronin, D. M. Hunt, and P. R. Robinson. 1998. The visual pigments of the bottlenose dolphin (Tursiops truncates). Vis. Neurosci. 15:643651.[CrossRef][ISI][Medline]
Fodgen, M., and P. Fodgen. 1974. Animals and their colors. Crown Press, New York.
Harosi, F. I. 1994. Analysis of two spectral properties of vertebrate visual pigments. Vision Res. 34:13591367.[CrossRef][ISI][Medline]
Hiramatsu, C., F. B. Radlwimmer, S. Yokoyama, and S. Kawamura. 2004. Mutagenesis and reconstitution of middle-to-long-wave-sensitive visual pigments of New World monkeys for testing the tuning effect of residues at sites 229 and 233. Vision Res. 44:22252231.[CrossRef][ISI][Medline]
Jacobs, G. H. 1993. The distribution and nature of color vision among the mammals. Biol. Rev. 68:413471.[ISI][Medline]
Kawamura, S., N. S. Blow, and S. Yokoyama. 1999. Genetic analyses of visual pigments of the pigeon (Columba livia). Genetics 153:18391850.
Kawamura, S., and S. Yokoyama. 1998. Functional characterization of visual and nonvisual pigments of American chameleon (Anolis carolinensis). Vision Res. 38:3744.[CrossRef][ISI][Medline]
Lythgoe, J. N. 1979. The ecology of vision. Clarendon, Oxford.
Madsen, O., M. Scally, C. J. Douady, D. J. Kao, R. W. DeBry, R. Adkins, H. M. Amrine, M. J. Stanhope, W. W. de Jong, and M. S. Springer. 2001. Parallel adaptive radiations in two major clades of placental mammals. Nature 409:610614.[CrossRef][ISI][Medline]
Makino, C. L., T. W. Raft, R. A. Mathies, J. Lugtenburg, M. E. Miley, R. van der Steen, and D. A. Baylor. 1990. Effects of modified chromophores on the spectral sensitivity of salamander, squirrel and macaque cones. J. Physiol. 424:545560.[Abstract]
McLaughlin, P. J., and M. O. Dayhoff. 1972. Evolution of species and proteins: a time scale. Pp. 4766 in M. O. Dayhoff, ed. Atlas of protein sequence and structure. National Biomedical Research Foundation, Washington, D.C.
Merbs, S. L., and J. Nathans. 1992. Absorption spectrum of human cone pigments. Nature 356:433435.[CrossRef][ISI][Medline]
Mollon, J. 1991. The uses and evolutionary origins of primate color vision. Pp. 306319 in J. R. Cronly-Dillon and R. L. Gregory, eds. Evolution of the eye and visual system. CRC Press, Boca Raton, Fla.
Morgan, M. J., A. Adam, and J. D. Mollon. 1992. Dichromats detect colour-camouflaged objects that are not detected by trichromats. Proc. R. Soc. Lond. B Biol. Sci. 248:291295.[ISI][Medline]
Murphy, W. J., E. Eizirik, W. E. Johnson, Y. P. Zhang, O. A. Ryder, and S. J. O'Brien. 2001. Molecular phylogenetics and the origins of placental mammals. Nature 409:614618.[CrossRef][ISI][Medline]
Nielsen, R., and Z. Yang. 1998. Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics 148:929936.
Oprian, D. D., A. B. Asenjo, N. Lee, and S. L. Pelletier. 1991. Design, chemical synthesis, and expression of genes for the three human color vision pigments. Biochemistry 30:1136711372.[CrossRef][ISI][Medline]
Palczewski, K., T. Kumasaka, and T. Hori. (12 co-authors). 2000. Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289:739745.
Radlwimmer, F. B., and S. Yokoyama. 1997. Cloning and expression of the red visual pigment gene of goat (Capra hircus). Gene 198:211215.[CrossRef][ISI][Medline]
. 1998. Genetic analyses of the green visual pigments of rabbit (Oryctolagus cuniculus) and rat (Rattus norvegicus). Gene 218:103109.[CrossRef][ISI][Medline]
Regan, B. C., C. Julliot, B. Simmen, F. Vienot, P. Charles-Dominique, and J. D. Mollon. 2001. Fruits, foliage and the evolution of primate colour vision. Philos. Trans. R. Soc. Lond. B Biol. Sci. 356:229283.[CrossRef][ISI][Medline]
Saitou, A., A. Mikami, Y. Ueno, S. Kawamura, K. A. Wiidayati, B. Suryobroto, Y. Mori, M. Teramoto, and T. Hasegawa. 2004. Advantage of dichromats over trichromats in discrimination of colour-camouflaged stimuli. Folia Primatol. 75:S186.
Shi, Y., and S. Yokoyama. 2003. Molecular analysis of the evolutionary significance of ultraviolet vision in vertebrates. Proc. Natl. Acad. Sci. USA 100:83088313.
Simunovic, M. P., B. C. Regan, and J. D. Mollon. 2001. Is color vision deficiency an advantage under scotopic conditions? Investig. Ophthalmol. Vis. Sci. 42:33573364.
Sun, H., J. P. Macke, and J. Nathans. 1997. Mechanisms of spectral tuning in the mouse green cone pigment. Proc. Natl. Acad. Sci. USA 94:88608865.
Surridge, A. K., D. Osorio, and N. I. Mundy. 2003. Evolution and selection of trichromatic vision in primates. Trends Ecol. Evol. 18:198205.[CrossRef][ISI]
Suzuki, Y., and T. Gojobori. 1999. A method for detecting positive selection at single amino acid sites. Mol. Biol. Evol. 16:13151328.[Abstract]
Suzuki, Y., T. Gojobori, and M. Nei. 2001. ADAPTSITE: detecting natural selection at single amino acid sites. Bioinformatics 17:660661.
Suzuki, Y., and Nei. 2001. Reliabilities of parsimony-based and likelihood methods for detecting positive selection at single amino acid sites. Mol. Biol. Evol. 18:21792185.
Suzuki, Y., and M. Nei. 2004. False-positive selection identified by ML-based methods: examples from the Sig1 gene of the diatom Thalassiosira weissflogii and the tax gene of a human T-cell lymphotrophic virus. Mol. Biol. Evol. 21:914921.
Verhulst, S., and F. W. Maes. 1998. Scotopic vision in colour-blinds. Vision Res. 38:33873390.[CrossRef][ISI][Medline]
Walls, G. L. 1942. The vertebrate eye and its adaptive dadiation. Hafner, New York.
Whitmore, A. V., and J. K. Bowmaker. 1989. Seasonal variation in cone sensitivity and short-wave absorbing visual pigments in the rudd Scadinius erythrophthalmus. J. Comp. Physiol. A Sens. Neural. Behav. Physiol. 166:103115.[ISI]
Winderickx, J., D. T. Lindsey, E. Sanocki, D. Y. Teller, A. G. Motulsky, and S. S. Deeb. 1992. Polymorphism in red photopigment underlies variation in color matching. Nature 356:431433.[CrossRef][ISI][Medline]
Yang, Z. 1997. PAML: a program package for phylogenetic analysis by maximum likelihood. Comput. Appl. Biosci. 13:555556.[Medline]
Yang, Z., and R. Nielsen. 2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19:908917.
Yang, Z., R. Nielsen, N. Goldman, and A.-M. K. Pedersen. 2000. Codon-substitution models for heterogeneous selection pressure at amino acids. Genetics 155:431449.
Yokoyama, S. 2000a. Molecular evolution of vertebrate visual pigments. Prog. Retin. Eye Res. 19:385419.[CrossRef][ISI][Medline]
. 2000b. Phylogenetic analysis and experimental approaches to study color vision in vertebrates. Methods Enzymol. 315:312325.[ISI][Medline]
Yokoyama, S., and F. B. Radlwimmer. 1999. The molecular genetics of red and green color vision in mammals. Genetics 153:919932.
. 2001. The molecular genetics and evolution of red and green color vision in vertebrates. Genetics 158:16971710.
Yokoyama, S., F. B. Radlwimmer, and N. S. Blow. 2000. Molecular evolution of color vision of zebra finch. Gene 259:1724.[CrossRef][ISI][Medline]
Yokoyama, S., and N. Takenaka. 2004. The molecular basis of adaptive evolution of squirrelfish rhodopsins. Mol. Biol. Evol. 21:18.
Yokoyama, S., and R. Yokoyama. 1996. Adaptive evolution of photoreceptors and visual pigments in vertebrates. Annu. Rev. Ecol. Syst. 27:543567.[CrossRef][ISI]
Zhang, J. 2004. Frequent false detection of positive selection by the likelihood method with branch-site models. Mol. Biol. Evol. 21:13321339.
Zhang, J., and S. Kumar. 1997. Detection of convergent and parallel evolution at the amino acid sequence level. Mol. Biol. Evol. 14:527536.[Abstract]