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Positive selection and convergent evolution shape molecular phenotypic traits of innate immunity receptors in tits (Paridae)

. 2020 Aug ; 29 (16) : 3056-3070. [epub] 20200731

Language English Country Great Britain, England Media print-electronic

Document type Journal Article, Research Support, Non-U.S. Gov't

Despite widespread variability and redundancy abounding animal immunity, little is currently known about the rate of evolutionary convergence (functionally analogous traits not inherited from a common ancestor) in host molecular adaptations to parasite selective pressures. Toll-like receptors (TLRs) provide the molecular interface allowing hosts to recognize pathogenic structures and trigger early danger signals initiating an immune response. Using a novel combination of bioinformatic approaches, here we explore genetic variation in ligand-binding regions of bacteria-sensing TLR4 and TLR5 in 29 species belonging to the tit family of passerine birds (Aves: Paridae). Three out of the four consensual positively selected sites in TLR4 and six out of 14 positively selected positions in TLR5 were located on the receptor surface near the functionally important sites, and based on the phylogenetic pattern evolved in a convergent (parallel) manner. This type of evolution was also seen at one N-glycosylation site and two positively selected phosphorylation sites, providing the first evidence of convergence in post-translational modifications in evolutionary immunology. Finally, the overall mismatch between phylogeny and the clustering of surface charge distribution demonstrates that convergence is common in overall TLR4 and TLR5 molecular phenotypes involved in ligand binding. Our analysis did not reveal any broad ecological traits explaining the convergence observed in electrostatic potentials, suggesting that information on microbial symbionts may be needed to explain TLR evolution. Adopting state-of-the-art predictive structural bionformatics, we have outlined a new broadly applicable methodological approach to estimate the functional significance of positively selected variation and test for the adaptive molecular convergence in protein-coding polymorphisms.

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Alcaide, M., & Edwards, S. V. (2011). Molecular evolution of the toll-like receptor multigene family in birds. Molecular Biology and Evolution, 28(5), 1703-1715. https://doi.org/10.1093/molbev/msq351

Areal, H., Abrantes, J., & Esteves, P. J. (2011). Signatures of positive selection in Toll-like receptor (TLR) genes in mammals. BMC Evolutionary Biology, 11(368), 368. https://doi.org/10.1186/1471-2148-11-368

Balbuena, J. A., Míguez-Lozano, R., & Blasco-Costa, I. (2013). PACo: A novel procrustes application to cophylogenetic analysis. PLoS One, 8(4). https://doi.org/10.1371/journal.pone.0061048

Blom, N., Gammeltoft, S., & Brunak, S. (1999). Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. Journal of Molecular Biology, 294(5), 1351-1362. https://doi.org/10.1006/jmbi.1999.3310

Bohne-Lang, A., & Von der Lieth, C. W. (2005). GlyProt: In silico glycosylation of proteins. Nucleic Acids Research, 33(Suppl. 2), 214-219. https://doi.org/10.1093/nar/gki385

Boles, W. E., Caley, K. J., Clement, P., Collar, N. J., Gosler, A. G., Gregory, P. A., … Thomson, H. S. S. (2007). Handbook of the birds of the world, volume 12: Picathartes to tits and chickadees. In J. D. Hoyo, A. Elliott, & D. Christie (Eds.), Handbook of the Birds of the World (Vol. 12, pp. 1-815). Barcelona, Spain: Lynx Edicions. https://doi.org/10.1108/09504120810914574

Botos, I., Segal, D. M., & Davies, D. R. (2011). The structural biology of Toll-like receptors. Structure, 19(4), 447-459. https://doi.org/10.1016/j.str.2011.02.004

Brodie, E. D., & Brodie, E. D. (2015). Predictably convergent evolution of sodium channels in the arms race between predators and prey. Brain, Behavior and Evolution, 86, 48-57. https://doi.org/10.1159/000435905

Chastain, E. M. L., & Miller, S. D. (2012). Molecular mimicry as an inducing trigger for CNS autoimmune demyelinating disease. Immunological Reviews, 245(1), 227-238. https://doi.org/10.1111/j.1600-065X.2011.01076.x

Da Silva Correia, J., & Ulevitch, R. J. (2002). MD-2 and TLR4 N-linked glycosylations are important for a functional lipopolysaccharide receptor. Journal of Biological Chemistry, 277(3), 1845-1854. https://doi.org/10.1074/jbc.M109910200

Donald, J. E., Kulp, D. W., & Degrado, W. F. (2012). Salt bridges: Geometrically specific. Designable Interactions. Biochemistry, 79(3), 898-915. https://doi.org/10.1002/prot.22927.Salt

Eichler, W. (1948). XLI.-Some rules in ectoparasitism. Annals and Magazine of Natural History, 1(8), 588-598. https://doi.org/10.1080/00222934808653932

Eisenberg, D., Schwarz, E., Komaromy, M., & Wall, R. (1984). Analysis of membrane and surface protein sequences with the hydrophobic moment plot. Journal of Molecular Biology, 179(1), 125-142. https://doi.org/10.1016/0022-2836(84)90309-7

Escalera-Zamudio, M., Zepeda-Mendoza, M. L., Loza-Rubio, E., Rojas-Anaya, E., Méndez-Ojeda, M. L., Arias, C. F., & Greenwood, A. D. (2015). The evolution of bat nucleic acid-sensing Toll-like receptors. Molecular Ecology, 24(23), 5899-5909. https://doi.org/10.1111/mec.13431

Fornuskova, A., Bryja, J., Vinkler, M., Macholan, M., & Pialek, J. (2014). Contrasting patterns of polymorphism and selection in bacterial-sensing toll-like receptor 4 in two house mouse subspecies. Ecology and Evolution, 4(14), 2931-2944. https://doi.org/10.1002/ece3.1137

Fornůsková, A., Vinkler, M., Pagès, M., Galan, M., Jousselin, E., Cerqueira, F., … Cosson, J.-F. (2013). Contrasted evolutionary histories of two Toll-like receptors (Tlr4 and Tlr7) in wild rodents (MURINAE). Bmc Evolutionary Biology, 13, 17. https://doi.org/10.1186/1471-2148-13-194

Galili, T. (2015). dendextend: An R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics, 31(22), 3718-3720. https://doi.org/10.1093/bioinformatics/btv428

Gnad, F., Gunawardena, J., & Mann, M. (2011). PHOSIDA 2011: The posttranslational modification database. Nucleic Acids Research, 39(Suppl. 1), 253-260. https://doi.org/10.1093/nar/gkq1159

Goldstein, R. A., Pollard, S. T., Shah, S. D., & Pollock, D. D. (2015). Nonadaptive amino acid convergence rates decrease over time. Molecular Biology and Evolution, 32(6), 1373-1381. https://doi.org/10.1093/molbev/msv041

Grueber, C. E., Wallis, G. P., & Jamieson, I. G. (2013). Genetic drift outweighs natural selection at toll-like receptor (TLR) immunity loci in a re-introduced population of a threatened species. Molecular Ecology, 22(17), 4470-4482. https://doi.org/10.1111/mec.12404

Grueber, C. E., Wallis, G. P., & Jamieson, I. G. (2014). Episodic positive selection in the evolution of avian toll-like receptor innate immunity genes. PLoS One, 9(3), 9. https://doi.org/10.1371/journal.pone.0089632

Grueber, C. E., Wallis, G. P., King, T. M., & Jamieson, I. G. (2012). Variation at innate immunity toll-like receptor genes in a bottlenecked population of a New Zealand. Robin. Plos ONE, 7(9), https://doi.org/10.1371/journal.pone.0045011

Hannon, E. R., Kinsella, J. M., Calhoun, D. M., Joseph, M. B., & Johnson, P. T. J. (2016). Endohelminths in bird hosts from Northern California and an analysis of the role of life history traits on parasite richness. The Journal of Parasitology, 102(2), 199-207. https://doi.org/10.1645/15-867

Harris, R., Carling, M., & Lovette, I. (2014). The influence of sampling design on species tree inference: A new relationship for the new world chickadees (Aves: Poecile). Evolution, 68(2), 501-513. https://doi.org/10.1111/evo.12280

Huerta-Cepas, J., Serra, F., & Bork, P. (2016). ETE 3: Reconstruction, analysis, and visualization of phylogenomic data. Molecular Biology and Evolution, 33(6), 1635-1638. https://doi.org/10.1093/molbev/msw046

Iwasaki, A., & Medzhitov, R. (2015). Control of adaptive immunity by the innate immune system. Nature Immunology, 16(4), 343-353. https://doi.org/10.1038/ni.3123

Johansson, U. S., Ekman, J., Bowie, R. C. K., Halvarsson, P., Ohlson, J. I., Price, T. D., & Ericson, P. G. P. (2013). A complete multilocus species phylogeny of the tits and chickadees (Aves: Paridae). Molecular Phylogenetics and Evolution, 69(3), 852-860. https://doi.org/10.1016/j.ympev.2013.06.019

Kaesler, E., Kappeler, P. M., Brameier, M., Demeler, J., Kraus, C., Rakotoniaina, J. H., … Huchard, E. (2017). Shared evolutionary origin of major histocompatibility complex polymorphism in sympatric lemurs. Molecular Ecology, 26(20), 5629-5645. https://doi.org/10.1111/mec.14336

Karatzoglou, A., Smola, A., Hornik, K., & Zeileis, A. (2004). kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software, 11(9), 1-20. https://doi.org/10.18637/jss.v011.i09

Kawai, T., & Akira, S. (2010). The role of pattern-recognition receptors in innate immunity: Update on Toll-like receptors. Nature Immunology, 11(5), 373-384. https://doi.org/10.1038/ni.1863

Kawai, T., & Akira, S. (2011). Toll-like receptors and their crosstalk with other innate receptors in infection and immunity. Immunity, 34(5), 637-650. https://doi.org/10.1016/j.immuni.2011.05.006

Keestra, A. M., de Zoete, M. R., van Aubel, R. A. M. H., & van Putten, J. P. M. (2008). Functional characterization of chicken TLR5 reveals species-specific recognition of flagellin. Molecular Immunology, 45(5), 1298-1307. https://doi.org/10.1016/j.molimm.2007.09.013

Klein, J., Sato, A., & Nikolaidis, N. (2007). MHC, TSP, and the origin of species: From immunogenetics to evolutionary genetics. Annual Review of Genetics, 41, 281-304. https://doi.org/10.1146/annurev.genet.41.110306.130137

Klement, E., & Medzihradszky, K. F. (2017). Extracellular protein phosphorylation, the neglected side of the modification. Molecular and Cellular Proteomics, 16(1), 1-7. https://doi.org/10.1074/mcp.O116.064188

Koch, M., Camp, S., Collen, T., Avila, D., Salomonsen, J., Wallny, H.-J., … Kaufman, J. (2007). Structures of an MHC Class I molecule from B21 chickens illustrate promiscuous peptide binding. Immunity, 27(6), 885-899. https://doi.org/10.1016/j.immuni.2007.11.007

Králová, T., Albrecht, T., Bryja, J., Hořák, D., Johnsen, A., Lifjeld, J. T., … Vinkler, M. (2018). Signatures of diversifying selection and convergence acting on passerine Toll-like receptor 4 in an evolutionary context. Molecular Ecology, 27(13), 2871-2883. https://doi.org/10.1111/mec.14724

Kriener, K., O'hUigin, C., Tichy, H., & Klein, J. (2000). Convergent evolution of major histocompatibility complex molecules in humans and New World monkeys. Immunogenetics, 51(3), 169-178. https://doi.org/10.1007/s002510050028

Kropáčková, L., Těšický, M., Albrecht, T., Kubovčiak, J., Čížková, D., Tomášek, O., … Kreisinger, J. (2017). Codiversification of gastrointestinal microbiota and phylogeny in passerines is not explained by ecological divergence. Molecular Ecology, 26(19), 5292-5304. https://doi.org/10.1111/mec.14144

Lefort, V., Longueville, J. E., & Gascuel, O. (2017). SMS: Smart model selection in PhyML. Molecular Biology and Evolution, 34(9), 2422-2424. https://doi.org/10.1093/molbev/msx149

Leifer, C. A., & Medvedev, A. E. (2016). Molecular mechanisms of regulation of Toll-like receptor signaling. Journal of Leukocyte Biology, 100(5), 927-941. https://doi.org/10.1189/jlb.2MR0316-117RR

Leveque, G., Forgetta, V., Morroll, S., Adrian, L., Bumstead, N., Barrow, P., … Smith, A. L. (2003). Allelic variation in TLR4 is linked to susceptibility to Salmonella enterica serovar Typhimurium infection in chickens. Infection and Immunity, 71(3), 1116-1124. https://doi.org/10.1128/IAI.71.3.1116

Li, L., Zhou, X. P., & Chen, X. L. (2011). Characterization and evolution of MHC Class II B genes in ardeid birds. Journal of Molecular Evolution, 72(5-6), 474-483. https://doi.org/10.1007/s00239-011-9446-3

Li, Z. (2006). Flexible Structural Neighborhood-a database of protein structural similarities and alignments. Nucleic Acids Research, 34(90001), D277-D280. https://doi.org/10.1093/nar/gkj124

Librado, P., & Rozas, J. (2009). DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25(11), 1451-1452. https://doi.org/10.1093/bioinformatics/btp187

Lyons, J. J., Milner, J. D., & Rosenzweig, S. D. (2015). Glycans instructing immunity: The emerging role of altered glycosylation in clinical immunology. Frontiers in Pediatrics, 3(June), 54. https://doi.org/10.3389/fped.2015.00054

Maddison, W. P., & Maddison, D. R. (2018). Mesquite: A modular system for evolutionary analysis. Retrieved fromhttp://www.mesquiteproject.org

Marth, J. D., & Grewal, P. K. (2008). Mammalian glycosylation in immunity. Nature Reviews Immunology, 8(11), 874-887. https://doi.org/10.1038/nri2417

McGuffin, L. J., Buenavista, M. T., & Roche, D. B. (2013). The ModFOLD4 server for the quality assessment of 3D protein models. Nucleic Acids Research, 41(W1), 368-372. https://doi.org/10.1093/nar/gkt294

Meyer, D., & Thomson, G. (2001). How selection shapes variation of the human major histocompatibility complex: A review. Annals of Human Genetics, 65, 1-26. https://doi.org/10.1046/j.1469-1809.2001.6510001.x

Murrell, B., Moola, S., Mabona, A., Weighill, T., Sheward, D., Kosakovsky Pond, S. L., & Scheffler, K. (2013). FUBAR: A fast, unconstrained bayesian AppRoximation for inferring selection. Molecular Biology and Evolution, 30(5), 1196-1205. https://doi.org/10.1093/molbev/mst030

Murrell, B., Wertheim, J. O., Moola, S., Weighill, T., Scheffler, K., & Kosakovsky Pond, S. L. (2012). Detecting individual sites subject to episodic diversifying selection. PLoS Genetics, 8(7), e1002764. https://doi.org/10.1371/journal.pgen.1002764

Nakajima, T., Ohtani, H., Satta, Y., Uno, Y., Akari, H., Ishida, T., & Kimura, A. (2008). Natural selection in the TLR-related genes in the course of primate evolution. Immunogenetics, 60(12), 727-735. https://doi.org/10.1007/s00251-008-0332-0

Ohara, T., Morishita, T., Suzuki, H., & Hibi, T. (2006). Heterozygous Thr 135 Ala polymorphism at leucine-rich repeat (LRR) in genomic DNA of toll-like receptor 4 in patients with poorly-differentiated gastric adenocarcinomas. International Journal of Molecular Medicine, 18(1), 59-63. https://doi.org/10.3892/ijmm.18.1.59

Onofrio, A., Parisi, G., Punzi, G., Todisco, S., Di Noia, M. A., Bossis, F., … Pierri, C. L. (2014). Distance-dependent hydrophobic-hydrophobic contacts in protein folding simulations. Physical Chemistry Chemical Physics, 16(35), 18907-18917. https://doi.org/10.1039/c4cp01131g

Paradis, E., Claude, J., & Strimmer, K. (2004). APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20(2), 289-290. https://doi.org/10.1093/bioinformatics/btg412

Paramo, T., Piggot, T. J., Bryant, C. E., & Bond, P. J. (2013). The structural basis for endotoxin-induced allosteric regulation of the toll-like receptor 4 (tlr4) innate immune receptor. Journal of Biological Chemistry, 288(51), 36215-36225. https://doi.org/10.1074/jbc.M113.501957

Park, B. S., Song, D. H., Kim, H. M., Choi, B.-S., Lee, H., & Lee, J.-O. (2009). The structural basis of lipopolysaccharide recognition by the TLR4-MD-2 complex. Nature, 458(7242), 1191-1195. https://doi.org/10.1038/nature07830

Parker, J., Tsagkogeorga, G., Cotton, J. A., Liu, Y., Provero, P., Stupka, E., & Rossiter, S. J. (2013). Genome-wide signatures of convergent evolution in echolocating mammals. Nature, 502(7470), 228-231. https://doi.org/10.1038/nature12511

Pond, S., & Frost, S. (2005). Datamonkey: Rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics, 21(10), 2531-2533. https://doi.org/10.1093/bioinformatics/bti320

Posada, D., & Crandall, K. (1998). MODELTEST: Testing the model of DNA substitution. Bioinformatics, 14(9), 817-818. https://doi.org/10.1093/bioinformatics/14.9.817

R Core Team (2017). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/

Revell, L. J. (2012). Bioinformatics-dendextend-an R package for visualizing, adjusting and comapring trees of hierachical clutering. Methods in Ecology and Evolution, 3(2), 217-223. https://doi.org/10.1111/j.2041-210X.2011.00169.x

Ricci-Azevedo, R., Roque-Barreira, M. C., & Gay, N. J. (2017). Targeting and recognition of toll-like receptors by plant and pathogen lectins. Frontiers in Immunology, 8, 6-9. https://doi.org/10.3389/fimmu.2017.01820

Richter, S., Wenzel, A., Stein, M., Gabdoulline, R. R., & Wade, R. C. (2008). webPIPSA: A web server for the comparison of protein interaction properties. Nucleic Acids Research, 36(Web Server), W276-W280. https://doi.org/10.1093/nar/gkn181

Rudd, P. M., Elliott, T., Cresswell, P., Wilson, I. A., & Dwek, R. A. (2001). Glycosylation and the immune system. Science, 291(5512), 2370-2376. https://doi.org/10.1126/science.291.5512.2370

Schemske, D. W., Mittelbach, G. G., Cornell, H. V., Sobel, J. M., & Roy, K. (2009). Is there a latitudinal gradient in the importance of biotic interactions? Annual Review of Ecology, Evolution, and Systematics, 40(1), 245-269. https://doi.org/10.1146/annurev.ecolsys.39.110707.173430

Smirnova, I., Poltorak, A., Chan, E. K., McBride, C., & Beutler, B. (2000). Phylogenetic variation and polymorphism at the toll-like receptor 4 locus (TLR4). Genome Biology, 1(1), research002-1. https://doi.org/10.1186/gb-2000-1-1-research002

Smith, S. A., Jann, O. C., Haig, D., Russell, G. C., Werling, D., Glass, E. J., & Emes, R. D. (2012). Adaptive evolution of Toll-like receptor 5 in domesticated mammals. BMC Evolutionary Biology, 12(1), 122. https://doi.org/10.1186/1471-2148-12-122

Steentoft, C., Vakhrushev, S. Y., Joshi, H. J., Kong, Y., Vester-Christensen, M. B., Schjoldager, K.-B.-G., … Clausen, H. (2013). Precision mapping of the human O-GalNAc glycoproteome through SimpleCell technology. EMBO Journal, 32(10), 1478-1488. https://doi.org/10.1038/emboj.2013.79

Stern, D. L. (2013). The genetic causes of convergent evolution. Nature Reviews Genetics, 14(11), 751-764. https://doi.org/10.1038/nrg3483

Storz, J. F. (2016). Causes of molecular convergence and parallelism in protein evolution. Nature Reviews Genetics, 17(4), 239-250. https://doi.org/10.1038/nrg.2016.11

Świderská, Z., Šmídová, A., Buchtová, L., Bryjová, A., Fabiánová, A., Munclinger, P., & Vinkler, M. (2018). Avian Toll-like receptor allelic diversity far exceeds human polymorphism: An insight from domestic chicken breeds. Scientific Reports, 8(1), 1-11. https://doi.org/10.1038/s41598-018-36226-1

Tamura, K., Stecher, G., Peterson, D., Filipski, A., & Kumar, S. (2013). MEGA6: Molecular evolutionary genetics analysis version 6.0. Molecular Biology and Evolution, 30(12), 2725-2729. https://doi.org/10.1093/molbev/mst197

Tatárová, Z., Brábek, J., Rösel, D., & Novotný, M. (2012). SH3 domain tyrosine phosphorylation - sites, role and evolution. PLoS One, 7(5), e36310. https://doi.org/10.1371/journal.pone.0036310

Těšický, M., & Vinkler, M. (2015). Trans-species polymorphism in immune genes: General pattern or MHC-restricted phenomenon? Journal of Immunology Research, 10(MAY), 838035. https://doi.org/10.1155/2015/838035

Tietze, D. T., & Borthakur, U. (2012). Historical biogeography of tits (Aves: Paridae, Remizidae). Organisms Diversity and Evolution, 12(4), 433-444. https://doi.org/10.1007/s13127-012-0101-7

Tschirren, B., Andersson, M., Scherman, K., Westerdahl, H., Mittl, P. R., & Raberg, L. (2013). Polymorphisms at the innate immune receptor TLR2 are associated with Borrelia infection in a wild rodent population. Proc Biol Sci, 280, 20130364. https://doi.org/10.1098/rspb.2013.0364

Unckless, R. L., & Lazzaro, B. P. (2016). The potential for adaptive maintenance of diversity in insect antimicrobial peptides. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 371(1695), 20150291. https://doi.org/10.1098/rstb.2015.0291

Velová, H., Gutowska-Ding, M. W., Burt, D. W., & Vinkler, M. (2018). Toll-like receptor evolution in birds: Gene duplication, pseudogenisation and diversifying selection. Molecular Biology and Evolution, 35(9), 2170-2184. https://doi.org/10.1093/molbev/msy119

Vinkler, M., & Albrecht, T. (2009). The question waiting to be asked: Innate immunity receptors in the perspective of zoological research. Folia Zoologica, 58, 15-28.

Vinkler, M., Bainova, H., & Bryja, J. (2014). Protein evolution of Toll-like receptors 4, 5 and 7 within Galloanserae birds. Genetics Selection Evolution, 46, 12. https://doi.org/10.1186/s12711-014-0072-6

Vinkler, M., Bryjova, A., Albrecht, T., & Bryja, J. (2009). Identification of the first Toll-like receptor gene in passerine birds: TLR4 orthologue in zebra finch (Taeniopygia guttata). Tissue Antigens, 74(1), 32-41. https://doi.org/10.1111/j.1399-0039.2009.01273.x

Waldenstrom, J., Bensch, S., Kiboi, S., Hasselquist, D., & Ottosson, U. (2002). Cross-species infection of blood parasites between resident and migratory songbirds in Africa. Molecular Ecology, 11(8), 1545-1554. https://doi.org/10.1046/j.1365-294X.2002.01523.x

Walsh, C., Gangloff, M., Monie, T., Smyth, T., Wei, B., McKinley, T. J., … Bryant, C. (2008). Elucidation of the MD-2/TLR4 interface required for signaling by lipid IVa. The Journal of Immunology, 181(2), 1245-1254. https://doi.org/10.4049/jimmunol.181.2.1245

Wang, X., Quinn, P. J., & Yan, A. (2015). Kdo2-lipid A: Structural diversity and impact on immunopharmacology. Biological Reviews, 90(2), 408-427. https://doi.org/10.1111/brv.12114

Webb, B., & Sali, A. (2016). Comparative protein structure modeling using MODELLER. Current Protocols in Bioinformatics, 54(1), 1-5. https://doi.org/10.1002/cpbi.3

Weber, A. N. R., Morse, M. A., & Gay, N. J. (2004). Four N-linked glycosylation sites in human toll-like receptor 2 cooperate to direct efficient biosynthesis and secretion. Journal of Biological Chemistry, 279(33), 34589-34594. https://doi.org/10.1074/jbc.M403830200

Wilman, H., Belmaker, J., Simpson, J., de la Rosa, C., Rivadeneira, M. M., & Jetz, W. (2014). EltonTraits 1.0: Species-level foraging attributes of the world's birds and mammals. Ecology, 95(7), 2027. https://doi.org/10.1890/13-1917.1

Wlasiuk, G., Khan, S., Switzer, W. M., & Nachman, M. W. (2009). A history of recurrent positive selection at the Toll-Like receptor 5 in primates. Molecular Biology and Evolution, 26(4), 937-949. https://doi.org/10.1093/molbev/msp018

Wlasiuk, G., & Nachman, M. W. (2010). Adaptation and constraint at toll-like receptors in primates. Molecular Biology and Evolution, 27(9), 2172-2186. https://doi.org/10.1093/molbev/msq104

Wong, Y.-H., Lee, T.-Y., Liang, H.-K., Huang, C.-M., Wang, T.-Y., Yang, Y.-H., … Hwang, J.-K. (2007). KinasePhos 2.0: A web server for identifying protein kinase-specific phosphorylation sites based on sequences and coupling patterns. Nucleic Acids Research, 35(Suppl.2), 588-594. https://doi.org/10.1093/nar/gkm322

Woolhouse, M. E. J., Webster, J. P., Domingo, E., Charlesworth, B., & Levin, B. R. (2002). Biological and biomedical implications of the co-evolution of pathogens and their hosts. Nature Genetics, 32(4), 569-577. https://doi.org/10.1038/ng1202-569

Xue, Y., Liu, Z., Cao, J., Ma, Q., Gao, X., Wang, Q., Ren, J. (2011). GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection. Protein Engineering Design and Selection, 24(3), 255-260. https://doi.org/10.1093/protein/gzq094

Yang, Z. (2007). PAML 4: Phylogenetic analysis by maximum likelihood. Molecular Biology and Evolution, 24(8), 1586-1591. https://doi.org/10.1093/molbev/msm088

Ye, Y., & Godzik, A. (2004). FATCAT: A web server for flexible structure comparison and structure similarity searching. Nucleic Acids Research, 32(Web Server), W582-W585. https://doi.org/10.1093/nar/gkh430

Yeager, M., & Hughes, A. L. (1999). Evolution of the mammalian MHC: Natural selection, recombination, and convergent evolution. Immunological Reviews, 167, 45-58. https://doi.org/10.1111/j.1600-065X.1999.tb01381.x

Yokoyama, S., Yang, H., & Starmer, W. T. (2008). Molecular basis of spectral tuning in the red- and green-sensitive (M/LWS) pigments in vertebrates. Genetics, 179(4), 2037-2043. https://doi.org/10.1534/genetics.108.090449

Yoon, S., Kurnasov, O., Natarajan, V., Hong, M., Gudkov, A., Osterman, A., & Wilson, I. (2013). Structural basis of TLR5-flagellin recognition and signaling. Science, 335(6070), 859-864. https://doi.org/10.1126/science.1215584

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