comparative sequence analysis; heterologous expression; light-sensitive opsins; protein modelling; visual pigments; Opsins; Amino Acid Sequence; Animals; Evolution, Molecular; HEK293 Cells; Humans; Invertebrates; Opsins/genetics; Phylogeny; Vertebrates; Arthropods/genetics; Odonata; Arthropods; Biochemistry, Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all); General Agricultural and Biological Sciences; General Biochemistry, Genetics and Molecular Biology
Abstract :
[en] Visual opsins of vertebrates and invertebrates diversified independently and converged to detect ultraviolet to long wavelengths (LW) of green or red light. In both groups, colour vision largely derives from opsin number, expression patterns and changes in amino acids interacting with the chromophore. Functional insights regarding invertebrate opsin evolution have lagged behind those for vertebrates because of the disparity in genomic resources and the lack of robust in vitro systems to characterize spectral sensitivities. Here, we review bioinformatic approaches to identify and model functional variation in opsins as well as recently developed assays to measure spectral phenotypes. In particular, we discuss how transgenic lines, cAMP-spectroscopy and sensitive heterologous expression platforms are starting to decouple genotype-phenotype relationships of LW opsins to complement the classical physiological-behavioural-phylogenetic toolbox of invertebrate visual sensory studies. We illustrate the use of one heterologous method by characterizing novel LW Gq opsins from 10 species, including diurnal and nocturnal Lepidoptera, a terrestrial dragonfly and an aquatic crustacean, expressing them in HEK293T cells, and showing that their maximum absorbance spectra (λmax) range from 518 to 611 nm. We discuss the advantages of molecular approaches for arthropods with complications such as restricted availability, lateral filters, specialized photochemistry and/or electrophysiological constraints. This article is part of the theme issue 'Understanding colour vision: molecular, physiological, neuronal and behavioural studies in arthropods'.
Disciplines :
Genetics & genetic processes
Author, co-author :
Lienard, Marjorie ; Université de Liège - ULiège > GIGA > GIGA Molecular Biology of Diseases ; Department of Biology, Lund University, 22362 Lund, Sweden ; Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
Valencia-Montoya, Wendy A ; Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
Pierce, Naomi E ; Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
Language :
English
Title :
Molecular advances to study the function, evolution and spectral tuning of arthropod visual opsins.
Publication date :
24 October 2022
Journal title :
Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
Sverige Vetenskapsrådet NSF - National Science Foundation
Funding text :
This work was supported by the Swedish Research Council (VR 2020-0517) to M.A.L., a grant from the Mind, Brain and Behaviour (MBB) interfaculty initiative at Harvard University to W.A.V.-M and N.E.P., and grants from the National Science Foundation (PoLS 1411123 and DEB 1541560) to N.E.P. Acknowledgements
Feuda R, Hamilton S, McInerney J, Pisani D. 2012 Metazoan opsin evolution reveals a simple route to animal vision. Proc. Natl Acad. Sci. USA 109, 18 868-18 872. (doi:10.1073/pnas.1204609109)
Devine E, Oprian D, Theobald D. 2013 Relocating the active-site lysine in rhodopsin and implications for evolution of retinylidene proteins. Proc. Natl Acad. Sci. USA 110, 13 351-13 355. (doi:10.1073/ pnas.1306826110)
Cronin T, Johnsen S, Marshall J, Warrant E. 2014 Visual ecology. Princeton, NJ: Princeton University Press.
Varma N, Mutt E, Mühle J, Panneels V, Terakita A, Deupi X, Nogly P, Schertler G, Lesca E. 2019 Crystal structure of jumping spider rhodopsin-1 as a light sensitive GPCR. Proc. Natl Acad. Sci. USA 116, 14 547-14 556. (doi:10.1073/pnas. 1902192116)
Terakita A, Yamashita T, Shichida Y. 2000 Highly conserved glutamic acid in the extracellular IV-V loop in rhodopsins acts as the counterion in retinochrome, a member of the rhodopsin family. Proc. Natl Acad. Sci. USA 97, 14 263-14 267. (doi:10.1073/pnas.260349597)
Feuda R, Marlétaz F, Bentley MA, Holland PWH. 2016 Conservation, duplication, and divergence of five opsin genes in insect evolution. Gen. Biol. Evol. 8, 579-587. (doi:10.1093/gbe/evw015)
Terakita A, Kawano-Yamashita E, Koyanagi M. 2012 Evolution and diversity of opsins. Wiley Interdiscip. Rev. Membr. Transport Signal. 1, 104-111. (doi:10. 1002/wmts.6)
Smedley G, McElroy K, Serb J. 2021 Additive and epistatic effects influence spectral tuning in molluscan retinochrome opsin. bioRxiv 2021.05.26.445805. (doi:10.1101/2021.05. 26.445805)
Terakita A. 2005 The opsins. Protein Family Rev. 6, 213.
Leuong N, Montell C. 2017 Unconventional roles of opsins. Annu. Rev. Cell Dev. Biol. 33, 241-264. (doi:10.1146/annurev-cellbio-100616- 060432)
Shen W, Kwon Y, Adegbola A, Luo J, Chess A, Montell C. 2011 Function of rhodopsin in temperature discrimination in Drosophila. Science 331, 1333-1336. (doi:10.1126/science. 1198904)
Pisani D, Rota-Stabelli O, Feuda R. 2020 Sensory neuroscience: a taste for light and the origin of animal vision. Curr. Biol. 30, R773-R775. (doi:10. 1016/j.cub.2020.05.009)
Matsui S, Seidou M, Uchiyama I, Sekiya N, Hiraki K, Yoshihara K, Kito Y. 1988 4-Hydroxyretinal, a new visual pigment chromophore found in the bioluminescent squid, Watasenia scintillans. Biochim. Biophys. Acta 966, 370-374. (doi:10.1016/ 0304-4165(88)90087-6)
Kelber A. 2019 Bird colour vision - from cones to perception. Curr. Opin. Behav. Sci. 30, 34-40. (doi:10.1016/j.cobeha.2019.05.003)
Jacobs GH. 2009 Evolution of colour vision in mammals. Phil. Trans. R. Soc. B 364, 2957-2967. (doi:10.1098/rstb.2009.0039)
Hauser F, Chang B. 2017 Insights into visual pigment adaptation and diversity from model ecological and evolutionary systems. Curr. Opin Genet. Dev. 47, 110-120. (doi:10.1016/j.gde.2017. 09.005)
van der Kooi C, Stavenga D, Arikawa K, Belusic G, Kelber A. 2021 Evolution of insect colour vision - from spectral sensitivity to visual ecology. Annu. Rev. Entomol. 66, 435-461. (doi10.1146/annurevento- 061720-071644.)
Briscoe AD, Chittka L. 2001 The evolution of color vision in insects. Annu. Rev. Entomol. 46, 471-510. (doi:10.1146/annurev.ento.46.1.471)
Terakita A, Nagata T. 2014 Functional properties of opsins and their contribution to light sensing physiology. Zoolog. Sci. 31, 653-659. (doi:10.2108/ zs140094)
Saito T, Koyanagi M, Sugihara T, Nagata T, Arikawa K, Terakita A. 2019 Spectral tuning mediated by helix III in butterfly long wavelength-sensitive visual opsins revealed by heterologous action spectroscopy. Zool. Lett. 5, 35. (doi:10.1186/s40851- 019-0150-2)
Salcedo E, Farrell D, Zheng L, Phistry M, Bagg E, Britt S. 2009 The green-absorbing Drosophila rh6 visual pigment contains a blue-shifting amino acid substitution that is conserved in vertebrates. J. Biol. Chem. 284, 5717-5722. (doi:10.1074/jbc. M807368200)
Yokoyama S, Xing J, Liu Y, Faggionato D, Altun A, Starmer WT. 2014 Epistatic adaptive evolution of human color vision. PLoS Genet. 10, e1004884. (doi:10.1371/journal.pgen. 1004884)
Yokoyama S, Tada T, Liu Y, Faggionato D, Altun A. 2016 A simple method for studying the molecular mechanisms of ultraviolet and violet reception in vertebrates. BMC Evol. Biol. 16, 64. (doi:10.1186/ s12862-016-0637-9)
Takahashi Y, Yokoyama S. 2005 Genetic basis of spectral tuning in the violet-sensitive visual pigment of African clawed frog, Xenopus laevis. Genetics 171, 1153-1160. (doi:10.1534/genetics. 105.045849)
Hauser FE, Iv H, Chang BSW. 2014 Spectral tuning in vertebrate short wavelength-sensitive 1 (SWS1) visual pigments: can wavelength sensitivity be inferred from sequence data? J. Exp. Zool. 322, 529-539. (doi:10.1002/jez.b.22576)
Terakita A, Tsukamoto H, Koyanagi M, Sugahara M, Yamashita T, Shichida Y. 2008 Expression and comparative characterization of Gq-coupled invertebrate visual pigments and melanopsin. J. Neurochem. 105, 883-890. (doi:10.1111/j.1471- 4159.2007.05184.x)
Wakakuwa M, Terakita A, Koyanagi M, Stavenga DG, Shichida Y, Arikawa K. 2010 Evolution and mechanism of spectral tuning of blue-absorbing visual pigments in butterflies. PLoS ONE 5, e15015. (doi:10.1371/journal.pone.0015015)
Sugihara T, Takashi N, Mason B, Koyanagi M, Terakita A. 2016 Absorption characteristics of vertebrate non-visual opsin, Opn3. PLoS ONE 17, e0161215. (doi:10.1371/journal.pone.0161215)
Lienard M et al. 2021 The evolution of red colour vision is linked to coordinated rhodopsin tuning in lycaenid butterflies. Proc. Natl Acad. Sci. USA 118, e2008986118. (doi:10.1073/pnas.2008986118)
Frentiu F, Yuan F, Savage W, Bernard GD, Mullen SP, Briscoe AD. 2014 Clines in butterflies suggest novel roles for insect photopigments. Mol. Biol. Evol. 32, 368-379. (doi:10.1093/molbev/msu304)
Thomas G et al. 2020 Gene content evolution in the arthropods. Genome Biol. 21, 15. (doi:10.1186/ s13059-019-1925-7)
Misof B et al. 2014 Phylogenomics resolves the timing and pattern of insect evolution. Science 7, 763-767. (doi:10.1126/science.1257570)
Kjer K, Misof B, Zhou X. 2012 The 1KITE insect phylogenetics initiative. See https://1kite.cngb.org.
Li F, Zhao X, Li M, He K, Huang C, Zhou Y, Li Z, Walters J. 2019 Insect genomes: progress and challenges. Insect. Mol. Biol. 28, 739-758. (doi:10. 1111/imb.12599)
Yin C et al. 2016 InsectBase: a resource for insect genomes and transcriptomes. Nucleic Acids Res. 44, D801-D807. (doi:10.1093/nar/gkv1204)
Consortium IK. 2013 The i5 K initiative: advancing arthropod genomics for knowledge, human health, agriculture, and the environment. J. Heredity 104, 595-600. (doi:10.1093/ jhered/est050)
Levine R. 2011 i5 k: the 5,000 insect genome project. Am. Entomol. 57, 110-113. (doi:10.1093/ae/57.2.110)
Lewin H et al. 2018 Earth BioGenome project: sequencing life for the future of life. Proc. Natl Acad. Sci. USA 115, 4325-4333. (doi:10.1073/pnas. 1720115115)
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990 Basic local alignment search tool. J. Mol. Biol. 215, 403-410. (doi:10.1016/S0022-2836(05)80360-2)
Wu T, Watanabe C. 2005 GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21, 1859-1875. (doi:10.1093/bioinformatics/bti310)
Bhagwat M, Young L, Robison R. 2012 Using BLAT to find sequence similarity in closely related genomes. Curr. Protoc. Bioinfor. Ch. 10, 10-8. (doi:10.1002/0471250953.bi1008s37)
States DJ, Gish W. 1994 Combined use of sequence similarity and codon bias for coding region identification. J. Comput. Biol. 1, 39-50. (doi:10. 1089/cmb.1994.1.39)
Finn R, Clements J, Eddy S. 2011 HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29-W37. (doi:10.1093/nar/gkr367)
Stanke M, Kollmar M, Keller O, Waack S. 2011 A novel hybrid gene prediction method employing protein multiple sequence alignments. Bioinformatics 27, 757-763. (doi:10.1093/ bioinformatics/btr010)
Hoff K, Lomsadze A, Borodovsky M, Stanke M. 2019 Whole-genome annotation with BRAKER. Methods Mol. Biol. 1962, 65-95. (doi:10.1007/978-1-4939- 9173-0-5)
Cantarel B, Korf I, Robb S, Parra G, Ross E, Moore B, Holt C, Sánchez Alvarado A, Yandell M. 2008 MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res. 18, 188-196. (doi:10.1101/gr. 6743907)
Speiser DI et al. 2014 Using phylogeneticallyinformed annotation (PIA) to search for lightinteracting genes in transcriptomes from non-model organisms. BMC Bioinf. 15, 350. (doi:10.1186/ s12859-014-0350-x)
Emms D, Kelly S. 2019 OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238. (doi:10.1186/s13059-019- 1832-y)
Proost S, Fostier J, De Witte D, Dhoedt B, Demeester P, Van de Peer Y, Vandepoele K. 2012 i-ADHoRe 3.0-fast and sensitive detection of genomic homology in extremely large data sets. Nucleic Acids Res. 40, e11. (doi:10.1093/nar/gkr955)
Wang Y et al. 2012 MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 40, e49. (doi:10.1093/ nar/gkr1293)
Sonnhammer E, Östlund G. 2015 InParanoid 8: orthology analysis between 273 proteomes, mostly eukaryotic. Nucleic Acids Res. 43, D234-D239. (doi:10.1093/nar/gku1203)
Katoh K, Standley DM. 2013 MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772-780. (doi:10.1093/molbev/ mst010)
Edgar RC. 2004 MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792-1797. (doi:10.1093/nar/ gkh340)
Sievers F, Higgins D. 2018 Clustal Omega for making accurate alignments of many protein sequences. Protein Sci. 27, 135-145. (doi:10.1002/pro.3290)
Li H, Durbin R. 2009 Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760. (doi:10.1093/ bioinformatics/btp324)
Langmead B, Trapnell C, Pop M, Salzberg S. 2009 Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25. (doi:10.1186/gb-2009- 10-3-r25)
Dobin A, Davis C, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras T. 2013 STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21. (doi:10.1093/ bioinformatics/bts635)
De Pristo M et al. 2011 A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491-498. (doi:10.1038/ng.806)
Li H. 2011 A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987-2993. (doi:10.1093/bioinformatics/btr509)
Garrison E, Marth G. 2012 Haplotype-based variant detection from short-read sequencing. arXiv, 1207.3907 [q-bio].
Minh B, Schmidt H, Chernomor O, Schrempf D, Woodhams M, von Haeseler A, Lanfear R. 2020 IQTREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530-1534. (doi:10.1093/molbev/ msaa015)
Kozlov A, Darriba D, Flouri T, Morel B, Stamatakis A. 2019 RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 35, 4453-4455. (doi:10.1093/ bioinformatics/btz305)
Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W, Gascuel O. 2010 New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307-321. (doi:10.1093/ sysbio/syq010)
Cai W, Pei J, Grishin N. 2004 Reconstruction of ancestral protein sequences and its applications. BMC Evol. Biol. 4, 33. (doi:10.1186/1471-2148-4-33)
Hanson-Smith V, Johnson A. 2016 PhyloBot: a web portal for automated phylogenetics, ancestral sequence reconstruction, and exploration of mutational trajectories. PLoS Comput. Biol. 12, e1004976. (doi:10.1371/journal.pcbi.1004976)
Arenas M, Bastolla U. 2020 ProtASR2: ancestral reconstruction of protein sequences accounting for folding stability. Methods Ecol. Evol. 11, 248-257. (doi:10.1111/2041-210X.13341)
Musil M, Khan R, Beier A, Stourac J, Konegger H, Damborsky J, Bednar D. 2021 FireProtASR: a web server for fully automated ancestral sequence reconstruction. Brief. Bioinform. 22, bbaa337. (doi:10.1093/bib/bbaa337)
Ashkenazy H, Penn O, Doron-Faigenboim A, Cohen O, Cannarozzi G, Zomer O, Pupko T. 2012 FastML: a web server for probabilistic reconstruction of ancestral sequences. Nucleic Acids Res. 40, W580-W584. (doi:10.1093/nar/gks498)
Yang Z. 2007 PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586-1591. (doi:10.1093/molbev/msm088)
Excoffier L, Laval G, Schneider S. 2005 Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol. Bioinform. Online 1, 117693430500100000. (doi:10.1177/ 117693430500100003)
Beaumont M, Nichols R. 1996 Evaluating loci for use in the genetic analysis of population structure. Proc. R. Soc. Lond. B 263, 1619-1626. (doi:10.1098/ rspb.1996.0237)
Foll M, Gaggiotti O. 2008 A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180, 977-993. (doi:10.1534/ genetics.108.092221)
Coop G, Witonsky D, Di Rienzo A, Pritchard J. 2010 Using environmental correlations to identify loci underlying local adaptation. Genetics 185, 1411-1423. (doi:10.1534/genetics.110.114819)
Frichot E, Schoville S, de Villemereuil P, Gaggiotti O, François O. 2015 Detecting adaptive evolution based on association with ecological gradients: orientation matters! Heredity 115, 22-28. (doi:10.1038/hdy. 2015.7)
McGaughran A, Morgan K, Sommer R. 2014 Environmental variables explain genetic structure in a beetle-associated nematode. PLoS ONE 9, e87317. (doi:10.1371/journal.pone.0087317)
Pond S, Frost S, Muse S. 2005 HyPhy: hypothesis testing using phylogenies. Bioinformatics 21, 676-679. (doi:10.1093/bioinformatics/bti079)
Murga-Moreno J, Coronado-Zamora M, Hervas S, Casillas S, Barbadilla A. 2019 iMKT: the integrative McDonald and Kreitman test. Nucleic Acids Res. 47, W283-W288. (doi:10.1093/nar/gkz372)
Eswar N, Webb B, Marti-Renom M, Madhusudhan M, Eramian D, Shen M, Pieper U, Sali A. 2006 Comparative protein structure modeling using modeller. Curr. Protoc. Bioinfor. 15, Unit-5.6. (doi:10.1002/0471250953.bi0506s15)
Waterhouse A et al. 2018 SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46, W296-W303. (doi:10.1093/ nar/gky427)
Kelley L, Mezulis S, Yates C, Wass M, Sternberg M. 2015 The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 10, 845-858. (doi:10.1038/nprot.2015.053)
Jumper J et al. 2021 Highly accurate protein structure prediction with AlphaFold. Nature 596, 583-589. (doi:10.1038/s41586-021-03819-2)
Schrödinger. 2016 The PyMOL molecular graphics system, version 1.8. Schrödinger, LLC. See https:// pymol.org/2/.
Pettersen E, Goddard T, Huang C, Couch G, Greenblatt D, Meng E, Ferrin T. 2004 UCSF Chimera-a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605-1612. (doi:10.1002/jcc.20084)
Pérez-Moreno J, De Leo D, Palero F, Bracken-Grissom H. 2018 Phylogenetic annotation and genomic architecture of opsin genes in Crustacea. Hydrobiologia 825, 159-175. (doi:10.1007/s10750- 018-3678-9)
Faggionato D, Serb JM. 2017 Strategy to identify and test putative light sensitive non-opsin gprotein-coupled receptors: a case study. Biol. Bull. 233, 70-82. (doi:10.1086/694842)
Gerrard E et al. 2018 Convergent evolution of tertiary structure in rhodopsin visual proteins from vertebrates and box jellyfish. Proc. Natl Acad. Sci. USA 115, 6201-6206. (doi:10.1073/pnas. 1721333115)
Chang B, Jönsson K, Kazmi M, Donoghue M, Sakmar T. 2002 Recreating a functional ancestral archosaur visual pigment. Mol. Biol. Evol. 19, 1483-1489. (doi:10.1093/oxfordjournals.molbev.a004211)
O'Quin K, Hofmann C, Hofmann H, Carleton K. 2010 Parallel evolution of opsin gene expression in African cichlid fishes. Mol. Biol. Evol. 27, 2839-2854. (doi:10.1093/molbev/msq171)
Shi Y, Radlwimmer F, Yokoyama S. 2001 Molecular genetics and the evolution of ultraviolet vision in vertebrates. Proc. Natl Acad. Sci. USA 98, 11 731-11 736. (doi:10.1073/pnas.201257398)
Yokoyama S. 2012 Synthesis of experimental molecular biology and evolutionary biology: an example from the world of vision. BioScience 62, 939-948. (doi:10.1525/bio.2012.62.11.3)
Lord NP, Plimpton RL, Sharkey CR, Suvorov A, Lelito JP, Willardson BM, Bybee SM. 2016 A cure for the blues: opsin duplication and subfunctionalization for short-wavelength sensitivity in jewel beetles (Coleoptera: Buprestidae). BMC Evol. Biol. 16, 107. (doi:10.1186/s12862-016-0674-4)
Sharkey CR, Fujimoto MS, Lord NP, Shin S, McKenna DD, Suvorov A, Martin GJ, Bybee SM. 2017 Overcoming the loss of blue sensitivity through opsin duplication in the largest animal group, beetles. Sci. Rep. 7, 8. (doi:10.1038/s41598-017- 00061-7)
Frentiu F, Bernard G, Sison-Mangus M, Van Zandt Brower A, Briscoe A. 2007 Gene duplication is an evolutionary mechanism for expanding spectral diversity in the long-wavelength photopigments of butterflies. Mol. Biol. Evol. 24, 2016-2028. (doi:10. 1093/molbev/msm132)
Briscoe AD, Bybee SM, Bernard GD, Yuan F, Sison-Mangus MP, Reed RD, Warren AD, Llorente-Bousquets J, Chiao C-C. 2010 Positive selection of a duplicated UV-sensitive visual pigment coincides with wing pigment evolution in Heliconius butterflies. Proc. Natl Acad. Sci. USA 107, 3628-3633. (doi:10.1073/pnas.0910085107)
Mugal C, Wolf J, Kaj I. 2014 Why time matters: codon evolution and the temporal dynamics of dN/ dS. Mol. Biol. Evol. 31, 212-231. (doi:10.1093/ molbev/mst192)
Messer P, Petrov D. 2013 Frequent adaptation and the McDonald-Kreitman test. Proc. Natl Acad. Sci. USA 110, 8615-8620. (doi:10.1073/pnas. 1220835110)
Yang Z. 1998 Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol. Biol. Evol. 15, 568-573. (doi:10.1093/oxfordjournals.molbev.a025957)
Sondhi Y, Ellis E, Bybee S, Theobald J, Kawahara A. 2021 Light environment drives evolution of color vision genes in butterflies and moths. Commun. Biol. 4, 177. (doi:10.1038/s42003-021-01688-z)
Yuan F, Bernard G, Le J, Briscoe A. 2010 Contrasting modes of evolution of the visual pigments in Heliconius butterflies. Mol. Biol. Evol. 27, 2392-2405. (doi:10.1093/molbev/msq124)
Porter ML, Awata H, Bok MJ, Cronin TW. 2020 Exceptional diversity of opsin expression patterns in Neogonodactylus oerstedii (Stomatopoda) retinas. Proc. Natl Acad. Sci. USA 117, 8948. (doi:10.1073/ pnas.1917303117)
Feuda R et al. 2021 Phylogenomics of opsin genes in diptera reveals lineage-specific events and contrasting evolutionary dynamics in Anopheles and Drosophila. Genome Biol. Evol. 13, evab170. (doi:10. 1093/gbe/evab170)
Schulte J, O'Brien C, Conte M, O'Quin K, Carleton K. 2014 Interspecific variation in Rx1 expression controls opsin expression and causes visual system diversity in African cichlid fishes. Mol. Biol. Evol. 31, 2297-2308. (doi:10.1093/molbev/msu172)
Smith A, Carleton K. 2010 Allelic variation in Malawi cichlid opsins: a tale of two genera. J. Mol. Evol. 70, 593-604. (doi:10.1007/s00239-010-9355-x)
Ahrens C, Rymer P, Stow A, Bragg J, Dillon S, Umbers K, Dudaniec R. 2018 The search for loci under selection: trends, biases and progress. Mol. Ecol. 27, 1342-1356. (doi:10.1111/mec.14549)
Marques DA, Taylor JS, Jones FC, Di Palma F, Kingsley DM, Reimchen TE. 2017 Convergent evolution of SWS2 opsin facilitates adaptive radiation of threespine stickleback into different light environments. PLoS Biol. 15, e2001627. (doi:10.1371/journal.pbio.2001627)
Hiwatashi T et al. 2010 An explicit signature of balancing selection for color-vision variation in New World Monkeys. Mol. Biol. Evol. 27, 453-464. (doi:10.1093/molbev/msp262)
Tezuka A et al. 2014 Divergent selection for opsin gene variation in guppy (Poecilia reticulata) populations of Trinidad and Tobago. Heredity 113, 381-389. (doi:10.1038/hdy.2014.35)
Terai Y et al. 2006 Divergent selection on opsins drives incipient speciation in Lake Victoria cichlids. PLoS Biol. 4, e433. (doi:10.1371/journal.pbio. 0040433)
Lehtonen P et al. 2012 Candidate genes for colour and vision exhibit signals of selection across the pied flycatcher (Ficedula hypoleuca) breeding range. Heredity 108, 431-440. (doi:10.1038/hdy.2011.93)
Lower SE, Stanger-Hall KF, Hall DW. 2018 Molecular variation across populations of a widespread North American firefly, Photinus pyralis, reveals that coding changes do not underlie flash color variation or associated visual sensitivity. BMC Evol. Biol. 18, 129. (doi:10.1186/s12862-018-1251-9)
Leung N, Thakur D, Gurav A, Kim S, Di Pizio A, Niv M, Montell C. 2020 Functions of opsins in Drosophila taste. Curr. Biol. 30, 1367-1379.e1366. (doi:10.1016/j.cub.2020.01.068)
Briscoe A. 2002 Homology modeling suggests a functional role for parallel amino acid substitutions between bee and butterfly red- and green-sensitive opsins. Mol. Biol. Evol. 19, 983-986. (doi:10.1093/ oxfordjournals.molbev.a004158)
Haddad Y, Adam V, Heger Z. 2020 Ten quick tips for homology modeling of high-resolution protein 3D structures. PLoS Comput. Biol. 16, e1007449. (doi:10.1371/journal.pcbi.1007449)
Sekharan S, Morokuma K. 2011 Why 11-cis-Retinal? Why not 7-cis, 9-cis or 13-cis-retinal in the eye? J. Am. Chem. Soc. 133, 19 052-19 055. (doi:10. 1021/ja208789h)
Jeffrey G. 1997 An introduction to hydrogen bonding. New York, NY: Oxford University Press.
Yokoyama S, Radlwimmer F. 1998 The 'five-sites' rule and the evolution of red and green color vision in mammals. Mol. Biol. Evol. 15, 560-567. (doi:10. 1093/oxfordjournals.molbev.a025956)
Patel J, Brown C, Ytreberg F, Stenkamp D. 2018 Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations. PLoS Comput. Biol. 14, e1005974. (doi:10.1371/journal.pcbi. 1005974)
Yokoyama S. 2002 Molecular evolution of color vision in vertebrates. Gene 300, 69-78. (doi:10. 1016/s0378-1119(02)00845-4)
Knox B, Salcedo E, Mathiesz K, Schaefer J, Chou WH, Chadwell L, Smith W, Britt S, Barlow R. 2003 Heterologous expression of Limulus rhodopsin. J. Biol. Chem. 278, 40 493-40 502. (doi:10.1074/ jbc.M304567200)
Salcedo E, Huber A, Henrich S, Chadwell L, Chou W, Paulsen R, Britt S. 1999 Blue- and green-absorbing visual pigments of Drosophila: ectopic expression and physiological characterization of the R8 photoreceptor cell-specific Rh5 and Rh6 rhodopsins. J. Neurosci. 19, 10 716-10 726. (doi:10.1523/ JNEUROSCI.19-24-10716.1999)
Salcedo E, Zheng L, Phistry M, Bagg E, Britt S. 2003 Molecular basis for ultraviolet vision in invertebrates. J. Neurosci. 23, 10 873-10 878. (doi:10.1523/JNEUROSCI.23-34-10873.2003)
Townson S, Chang B, Salcedo E, Chadwell L, Pierce N, Britt S. 1998 Honeybee blue- and ultravioletsensitive opsins: cloning, heterologous expression in Drosophila, and physiological characterization. J. Neurosci. 18, 2412-2422. (doi:10.1523/ JNEUROSCI.18-07-02412.1998)
Sharkey C, Blanco J, Leibowitz M, Pinto-Benito D, Wardill T. 2020 The spectral sensitivity of Drosophila photoreceptors. Sci. Rep. 10, 18242. (doi:10.1038/ s41598-020-74742-1)
Szymczak-Workman AL, Vignali KM, Vignali DAA. 2012 Generation of 2A-linked multicistronic cassettes by recombinant PCR. Cold Spring Harbor Protocols 2012, pdb.prot067884. (doi:10.1101/pdb.prot067884)
Telles FJ, Lind O, Henze MJ, Rodríguez-Gironés MA, Goyret J, Kelber A. 2014 Out of the blue: the spectral sensitivity of hummingbird hawkmoths. J. Comp. Physiol. A 200, 537-546. (doi:10.1007/ s00359-014-0888-0)
Arikawa K. 2017 The eyes and vision of butterflies. J. Physiol. 595, 5457-5464. (doi:10.1113/JP273917)
Cong Q, Borek D, Otwinowski Z, Grishin NV. 2015 Skipper genome sheds light on unique phenotypic traits and phylogeny. BMC Genomics 16, 639. (doi:10.1186/s12864-015-1846-0)
Futahashi R, Kawahara-Miki R, Kinoshita M, Yoshitake K, Yajima S, Arikawa K, Fukatsu T. 2015 Extraordinary diversity of visual opsin genes in dragonflies. Proc. Natl Acad. Sci. USA 112, E1247. (doi:10.1073/pnas.1424670112)
Porter M, Bok M, Robinson P, Cronin T. 2009 Molecular diversity of visual pigments in Stomatopoda (Crustacea). Vis. Neurosci. 26, 255-265. (doi:10.1017/S0952523809090129)
Cronin TW, Marshall NJ, Caldwell RL. 2000 Spectral tuning and the visual ecology of mantis shrimps. Phil. Trans. R. Soc. Lond. B 355, 1263-1267. (doi:10.1098/rstb.2000.0680)
Ni JD, Baik LS, Holmes TC, Montell C. 2017 A rhodopsin in the brain functions in circadian photoentrainment in Drosophila. Nature 545, 340. (doi:10.1038/nature22325)
Sakai T, Tsutsui K, Yamashita T, Iwabe N, Takahashi K, Wada A, Shichida Y. 2017 Drosophila melanogaster rhodopsin Rh7 is a UV-to-visible light sensor with an extraordinarily broad absorption spectrum. Sci. Rep. 7, 7349. (doi:10.1038/s41598-017-07461-9)
Trifinopoulos J, Nguyen L-T, von Haeseler A, Minh B. 2016 W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res. 44, W232-W235. (doi:10.1093/nar/gkw256)
Kalyaanamoorthy S, Minh B, Wong T, von Haeseler A, Jermiin L. 2017 ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587-589. (doi:10.1038/nmeth.4285)
Hoang D, Chernomor O, von Haeseler A, Minh B, Vinh L. 2018 UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518-522. (doi:10.1093/molbev/msx281)
Zhang H, Gao S, Lercher M, Hu S, Chen W-H. 2012 EvolView, an online tool for visualizing, annotating and managing phylogenetic trees. Nucleic Acids Res. 40, W569-W572. (doi:10.1093/nar/gks576)
Govardovskii V, Fyhrquist N, Reuter T, Kuzmin D, Donner K. 2000 In search of the visual pigment template. Vis. Neurosci. 17, 509-528. (doi:10.1017/ s0952523800174036)
Liénard MA, Valencia-Montoya WA, Pierce NE. 2022 Molecular advances to study the function, evolution, and spectral tuning of arthropod visual opsins. Figshare. (doi:10.6084/m9.figshare.c. 6098624)
