Molecular Characterization of Crustacean Visual Pigments and the Evolution of Pancrustacean Opsins

Abstract

Investigations of opsin evolution outside of vertebrate systems have long been focused on insect visual pigments, whereas other groups have received little attention. Furthermore, few studies have explicitly investigated the selective influences across all the currently characterized arthropod opsins. In this study, we contribute to the knowledge of crustacean opsins by sequencing 1 opsin gene each from 6 previously uncharacterized crustacean species (Euphausia superba, Homarus gammarus, Archaeomysis grebnitzkii, Holmesimysis costata, Mysis diluviana, and Neomysis americana). Visual pigment spectral absorbances were measured using microspectrophotometry for species not previously characterized (A. grebnitzkii=496 nm, H. costata=512 nm, M. diluviana=501 nm, and N. americana=520 nm). These novel crustacean opsin sequences were included in a phylogenetic analysis with previously characterized arthropod opsin sequences to determine the evolutionary placement relative to the well-established insect spectral clades (long-/middle-/short-wavelength sensitive). Phylogenetic analyses indicate these novel crustacean opsins form a monophyletic clade with previously characterized crayfish opsin sequences and form a sister group to insect middle-/long-wavelength-sensitive opsins. The reconstructed opsin phylogeny and the corresponding spectral data for each sequence were used to investigate selective influences within arthropod, and mainly "pancrustacean," opsin evolution using standard dN/dS ratio methods and more sensitive techniques investigating the amino acid property changes resulting from nonsynonymous replacements in a historical (i.e., phylogenetic) context. Although the conservative dN/dS methods did not detect any selection, 4 amino acid properties (coil tendencies, compressibility, power to be at the middle of an alpha-helix, and refractive index) were found to be influenced by destabilizing positive selection. Ten amino acid sites relating to these properties were found to face the binding pocket, within 4 A of the chromophore and thus have the potential to affect spectral tuning.

Molecular phylogeny of the brachyuran crab superfamily Majoidea indicates close congruence with trees based on larval morphology

“…Phylogenies based on molecular and morphological characters are invaluable tools to trace the evolution of morphological, behavioral, and physiological diversity in decapods (Kitaura et al, 2006;Macdonald et al, 2006;Patek and Oakley, 2003;Porter et al, 2007;Schubart et al, 2000a). Although many studies have examined relationships among the major decapod groups (Ahyong and O'Meally, 2004;Brosing et al, 2007;Guinot, 1978;Jamieson, 1994;Kim and Abele, 1990;Porter et al, 2005;Spears et al, 1992), we know relatively little about phylogenetic relationships within these groups, especially compared with wellstudied taxa such as the Vertebrata Davis, 2001, 2006).…”

Evolution under pressure and the adaptation of visual pigment compressibility in deep-sea environments

“…Although previous studies have demonstrated that individual amino acid compressibility may play a role in the evolution of visual pigment function in relation to spectral tuning (Porter et al, 2007), this is the first study to link selection on specific amino acid properties to the evolution of overall protein compressibility in high pressure (e.g. deep-sea)…”

“…This method is based on the magnitudes of property change due to amino acid residue replacement as inferred across a phylogeny (McClellan et al, 2005), and has been demonstrated to be a more sensitive method for detecting positive selection than more common dN/dS based methods (Garb and Hayashi, 2013;McClellan et al, 2005;Porter et al, 2007;Wang et al, 2015). Because we are interested in the evolution of the opsin protein in response to the increased hydrostatic pressures of the deep-sea, we targeted sites identified to be under positive destabilizing selection, defined as selection for radical amino acid property changes (McClellan et al, 2005).…”

Assessing and improving the accuracy of detecting protein adaptation with the TreeSAAP analytical software

“…The use of amino acid properties results in a high degree of resolution that is more sensitive than the dN/dS approach [12], [16], and allows for the detailed diagnosis of individual amino acid changes in the context of the structure and function of proteins [1]. This alternative approach for detecting selection also exhibits great promise as a tool in the area of biomedical research [4], [14], [10].…”

“…A sliding window may be implemented to test the hypothesis that significant changes are localized in a particular part of the protein. Adaptive changes may then be mapped onto three-dimensional structures to qualitatively assess the degree to which adaptive changes are associated with functional domains and motifs [16], [14], [10].…”