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Non-synonymous variation and protein structure of candidate genes associated with selection in farm and wild populations of turbot (Scophthalmus maximus)

  • Ilker, E. & Hinczewski, M. Modeling the growth of organisms validates a general relation between metabolic costs and natural selection. Phys. Rev. Lett. 122, 238101 (2019).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Boltaña, S. et al. Influences of thermal environment on fish growth. Ecol. Evol. 7, 6814–6825 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rosenfeld, J., Richards, J., Allen, D., Van Leeuwen, T. & Monnet, G. Adaptive trade-offs in fish energetics and physiology: Insights from adaptive differentiation among juvenile salmonids. Can. J. Fish. Aquat. Sci. 77, 1243–1255 (2020).

    Article 

    Google Scholar 

  • Robertson, D. R. & Collin, R. Inter- and intra-specific variation in egg size among reef fishes across the isthmus of Panama. Front. Ecol. Evol. 2, 84 (2015).

    Article 

    Google Scholar 

  • Zueva, K. J., Lumme, J., Veselov, A. E., Kent, M. P. & Primmer, C. R. Genomic signatures of parasite-driven natural selection in north European Atlantic salmon (Salmo salar). Mar. Genom. 39, 26–38 (2018).

    Article 

    Google Scholar 

  • Rajkov, J., El Taher, A., Böhne, A., Salzburger, W. & Egger, B. Gene expression remodelling and immune response during adaptive divergence in an African cichlid fish. Mol. Ecol. 30, 274–296 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Verhille, C. E. et al. Inter-population differences in salinity tolerance and osmoregulation of juvenile wild and hatchery-born Sacramento splittail. Conserv. Physiol. 4, 1–12 (2016).

    Article 

    Google Scholar 

  • Froese, R. & Pauly, D. FishBase (version Feb 2018). In: Species 2000 & ITIS Catalogue of Life, 2019 Annual Checklist (Roskov Y. et al.). (2018). www.catalogueoflife.org/annual-checklist/2019. ISSN 2405–884X.

  • Karås, P. & Klingsheim, V. Effects of temperature and salinity on embryonic development of turbot (Scophthalmus maximus L.) from the North Sea, and comparisons with Baltic populations. Helgolander Meeresuntersuchungen 51, 241–247 (1997).

    Article 
    ADS 

    Google Scholar 

  • Barbut, L. et al. How larval traits of six flatfish species impact connectivity. Limnol. Oceanogr. 64, 1150–1171 (2019).

    Article 
    ADS 

    Google Scholar 

  • Bouza, C., Presa, P., Castro, J., Sánchez, L. & Martínez, P. Allozyme and microsatellite diversity in natural and domestic populations of turbot (Scophthalmus maximus) in comparison with other Pleuronectiformes. Can. J. Fish. Aquat. Sci. 59, 1460–1473 (2002).

    Article 
    CAS 

    Google Scholar 

  • Nielsen, E. E., Nielsen, P. H., Meldrup, D. & Hansen, M. M. Genetic population structure of turbot (Scophthalmus maximus L.) supports the presence of multiple hybrid zones for marine fishes in the transition zone between the Baltic Sea and the North Sea. Mol. Ecol. 13, 585–595 (2004).

    Article 
    PubMed 

    Google Scholar 

  • Vandamme, S. G. et al. Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus). Mol. Ecol. 23, 618–636 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Vilas, R. et al. A genome scan for candidate genes involved in the adaptation of turbot (Scophthalmus maximus). Mar. Genom. 23, 77–86 (2015).

    Article 

    Google Scholar 

  • Turan, C. et al. Genetics structure analysis of turbot (Scophthalmus maximus, Linnaeus, 1758) in the Black and Mediterranean Seas for application of innovative Management Strategies. Front. Mar. Sci. 6, 740 (2019).

    Article 

    Google Scholar 

  • Ivanova, P. et al. Genetic diversity and morphological characterisation of three turbot (Scophthalmus maximus L., 1758) populations along the Bulgarian Black Sea coast. Nat. Conserv. 43, 123–146 (2021).

    Article 

    Google Scholar 

  • do Prado, F. D. et al. Parallel evolution and adaptation to environmental factors in a marine flatfish: Implications for fisheries and aquaculture management of the turbot (Scophthalmus maximus). Evol. Appl. 11, 1322–1341 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • do Prado, F. D. et al. Tracing the genetic impact of farmed turbot Scophthalmus maximus on wild populations. Aquac. Environ. Interact. 10, 447–463 (2018).

    Article 

    Google Scholar 

  • Robledo, D. et al. Integrating genomic resources of flatfish (Pleuronectiformes) to boost aquaculture production. Comp. Biochem. Physiol. Part D Genom. Proteom. 21, 41–55 (2017).

    CAS 

    Google Scholar 

  • Sánchez-Molano, E. et al. Detection of growth-related QTL in turbot (Scophthalmus maximus). BMC Genomics 12, 473 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Rodríguez-Ramilo, S. T. et al. QTL detection for Aeromonas salmonicida resistance related traits in turbot (Scophthalmus maximus). BMC Genom. 12, 541 (2011).

    Article 

    Google Scholar 

  • Robledo, D. et al. Integrative transcriptome, genome and quantitative trait loci resources identify single nucleotide polymorphisms in candidate genes for growth traits in turbot. Int. J. Mol. Sci. 17, 243 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sciara, A. A. et al. Validation of growth-related quantitative trait loci markers in turbot (Scophthalmus maximus) families as a step toward marker assisted selection. Aquaculture 495, 602–610 (2018).

    Article 

    Google Scholar 

  • Ma, A., Huang, Z., Wang, X. & Xu, Y. & Guo, X.,. Identification of quantitative trait loci associated with upper temperature tolerance in turbot, Scophthalmus maximus. Sci. Rep. 11, 1–12 (2021).

    Article 

    Google Scholar 

  • Cui, W. et al. Comparative transcriptomic analysis reveals mechanisms of divergence in osmotic regulation of the turbot Scophthalmus maximus. Fish Physiol. Biochem. 46, 1519–1536 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Martínez, P. et al. Identification of the major sex-determining region of turbot (Scophthalmus maximus). Genetics 183, 1443–1452 (2009).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Martínez, P. et al. A genome-wide association study, supported by a new chromosome-level genome assembly, suggests sox2 as a main driver of the undifferentiatiated ZZ/ZW sex determination of turbot (Scophthalmus maximus). Genomics 113, 1705–1718 (2021).

    Article 
    PubMed 

    Google Scholar 

  • Martínez, P. et al. Turbot (Scophthalmus maximus) genomic resources:application for boosting aquaculture production. Genomics in Aquaculture (Elsevier Inc., 2016). https://doi.org/10.1016/B978-0-12-801418-9.00006-8.

  • Saura, M. et al. Disentangling genetic variation for resistance and endurance to scuticociliatosis in turbot using pedigree and genomic information. Front. Genet. 10, 539 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Aramburu, O. et al. Genomic signatures after five generations of intensive selective breeding: Runs of homozygosity and genetic diversity in representative domestic and wild populations of turbot (Scophthalmus maximus). Front. Genet. 11, 1–14 (2020).

    Article 

    Google Scholar 

  • Aramburu, O., Blanco, A., Bouza, C. & Martínez, P. Integration of host-pathogen functional genomics data into the chromosome-level genome assembly of turbot (Scophthalmus maximus). Aquaculture 564, 739067 (2023).

    Article 
    CAS 

    Google Scholar 

  • Saul, M. C., Philip, V. M., Reinholdt, L. G. & Chesler, E. J. High-diversity mouse populations for complex traits. Trends Genet. 35, 501–514 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Moen, T. et al. Epithelial cadherin determines resistance to infectious pancreatic necrosis virus in Atlantic salmon. Genetics 200, 1313–1326 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Pavelin, J. et al. The nedd-8 activating enzyme gene underlies genetic resistance to infectious pancreatic necrosis virus in Atlantic salmon. Genomics 113, 3842–3850 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Barson, N. J. et al. Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 528, 405–408 (2015).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Chen, J. et al. Functional differences between TSHR alleles associate with variation in spawning season in Atlantic herring. Commun. Biol. 4, 795 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Imsland, A. K., Brix, O., Nævdal, G. & Samuelsen, E. N. Hemoglobin genotypes in turbot (Scophthalmus maximus Rafinesque), their oxygen affinity properties and relation with growth. Comp. Biochem. Physiol. A Physiol. 116, 157–165 (1997).

    Article 

    Google Scholar 

  • Imsland, A. K., Foss, A., Stefansson, S. O. & Nævdal, G. Hemoglobin genotypes of turbot (Scophthalmus maximus): Consequences for growth and variations in optimal temperature for growth. Fish Physiol. Biochem. 23, 75–81 (2000).

    Article 
    CAS 

    Google Scholar 

  • Andersen, Ø., Rubiolo, J. A., De Rosa, M. C. & Martinez, P. The hemoglobin Gly16β1Asp polymorphism in turbot (Scophthalmus maximus) is differentially distributed across European populations. Fish Physiol. Biochem. 46, 2367–2376 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Torrisi, M., Pollastri, G. & Le, Q. Deep learning methods in protein structure prediction. Comput. Struct. Biotechnol. J. 18, 1301–1310 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • AlQuraishi, M. Machine learning in protein structure prediction. Curr. Opin. Chem. Biol. 65, 1–8 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Powder, K. E., Cousin, H., McLinden, G. P. & Craig Albertson, R. A nonsynonymous mutation in the transcriptional regulator lbh is associated with cichlid craniofacial adaptation and neural crest cell development. Mol. Biol. Evol. 31, 3113–3124 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Lamichhaney, S. et al. Evolution of Darwin’s finches and their beaks revealed by genome sequencing. Nature 518, 371–375 (2015).

    Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 

  • Gupta, A. M., Chakrabarti, J. & Mandal, S. Non-synonymous mutations of SARS-CoV-2 leads epitope loss and segregates its variants. Microbes Infect. 22, 598–607 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Verde, C. et al. Structure, function and molecular adaptations of haemoglobins of the polar cartilaginous fish Bathyraja eatonii and Raja hyperborea. Biochem. J. 389, 297–306 (2005).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Pearce, R. & Zhang, Y. Toward the solution of the protein structure prediction problem. J. Biol. Chem. 297, 100870 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Zhang, Y. I-TASSER server for protein 3D structure prediction. BMC Bioinf. 9, 40 (2008).

    Article 

    Google Scholar 

  • Pirolli, D. et al. Insights from molecular dynamics simulations: Structural basis for the V567D mutation-induced instability of zebrafish alpha-dystroglycan and comparison with the murine model. PLoS ONE 9, e103866 (2014).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Lee, J., Freddolino, P. L. & Zhang, Y. From Protein Structure to Function with Bioinformatics. In From Protein Structure to Function with Bioinformatics: Second Edition (ed. Rigden, D. J.) (2017). https://doi.org/10.1007/978-94-024-1069-3

  • Baek, M. et al. Accurate prediction of protein structures and interactions using a 3-track neural network. Science 373, 871–876 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Castro, J. et al. Potential sources of error in parentage assessment of turbot (Scophthalmus maximus) using microsatellite loci. Aquaculture 242, 119–135 (2004).

    Article 
    CAS 

    Google Scholar 

  • Chen, S., Zhou, Y., Chen, Y. & Gu, J. Fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. ArXiv ID 1303.3997v2 00, 1–3 (2013).

  • Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6, 80–92 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Vera, M. et al. Development and validation of single nucleotide polymorphisms (SNPs) markers from two transcriptome 454-runs of turbot (Scophthalmus maximus) using high-throughput genotyping. Int. J. Mol. Sci. 14, 5694–5711 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ellis, J. A. & Ong, B. The MassARRAY® system for targeted SNP genotyping. Methods in molecular biology vol. 1492 (2017).

  • Choi, Y. & Chan, A. P. PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 31, 2745–2747 (2015).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Costello, M. J. Ecology of sea lice parasitic on farmed and wild fish. Trends Parasitol. 22, 475–483 (2006).

    Article 
    PubMed 

    Google Scholar 

  • Blanchet, S., Rey, O. & Loot, G. Evidence for host variation in parasite tolerance in a wild fish population. Evol. Ecol. 24, 1129–1139 (2010).

    Article 

    Google Scholar 

  • Rousset, F. GENEPOP’007: A complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).

    Article 
    PubMed 

    Google Scholar 

  • Foll, M. & Gaggiotti, O. A Genome-scan method to identify selected loci appropriate for both dominant and codominant markers: A bayesian perspective. Genetics 993, 977–993 (2008).

    Article 

    Google Scholar 

  • Excoffier, L. & Lischer, H. E. L. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 10, 564–567 (2010).

    Article 
    PubMed 

    Google Scholar 

  • Narum, S. R. & Hess, J. E. Comparison of FST outlier tests for SNP loci under selection. Mol. Ecol. Resour. 11, 184–194 (2011).

    Article 
    PubMed 

    Google Scholar 

  • Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl. Acids Res. 25, 3389–3402 (1997).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Romero, P. et al. Sequence complexity of disordered protein. Prot. Struct. Funct. Genet. 42, 38–48 (2001).

    <a data-track="click" rel="nofollow noopener" data-track-label="10.1002/1097-0134(20010101)42:13.0.CO;2-3″ data-track-action=”article reference” href=”https://doi.org/10.1002%2F1097-0134%2820010101%2942%3A1%3C38%3A%3AAID-PROT50%3E3.0.CO%3B2-3″ aria-label=”Article reference 67″ data-doi=”10.1002/1097-0134(20010101)42:13.0.CO;2-3″>Article 
    CAS 

    Google Scholar 

  • Jones, D. T. & Cozzetto, D. DISOPRED3: Precise disordered region predictions with annotated protein-binding activity. Bioinformatics 31, 857–863 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Mészáros, B., Erdös, G. & Dosztányi, Z. IUPred2A: Context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucl. Acids Res. 46, W329–W337 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ishida, T. & Kinoshita, K. PrDOS: Prediction of disordered protein regions from amino acid sequence. Nucl. Acids Res. 35, W460-464 (2007).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ito, N., Komiyama, N. H. & Fermi, G. Structure of deoxyhaemoglobin of the Anctartic fish Pagothenia bernacchi and structural basis of the root effect. J. Mol. Biol. https://doi.org/10.2210/pdb1hbh/pdb (1995).

    Article 
    PubMed 

    Google Scholar 

  • Šali, A. & Blundell, T. L. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779–815 (1993).

    Article 
    PubMed 

    Google Scholar 

  • Gou, X. et al. Whole-genome sequencing of six dog breeds from continuous altitudes reveals adaptation to high-altitude hypoxia. Genome Res. 24, 1308–1315 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Grossman, S. R. et al. Identifying recent adaptations in large-scale genomic data. Cell 152, 703–713 (2013).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Macpherson, J. M., Sella, G., Davis, J. C. & Petrov, D. A. Genomewide spatial correspondence between nonsynonymous divergence and neutral polymorphism reveals extensive adaptation in Drosophila. Genetics 177, 2083–2099 (2007).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Howe, D. G. et al. ZFIN, the Zebrafish model organism database: Increased support for mutants and transgenics. Nucl. Acids Res. 41, 854–860 (2013).

    Article 

    Google Scholar 

  • Huber, C. D., Kim, B. Y., Marsden, C. D. & Lohmueller, K. E. Determining the factors driving selective effects of new nonsynonymous mutations. Proc. Natl. Acad. Sci. USA 114, 4465–4470 (2017).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Stenson, P. D. et al. The Human Gene Mutation Database (HGMD®): Optimizing its use in a clinical diagnostic or research setting. Hum. Genet. 139, 1197–1207 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Naruse, K., Hori, H., Shimizu, N., Kohara, Y. & Takeda, H. Medaka genomics: A bridge between mutant phenotype and gene function. Mech. Dev. 121, 619–628 (2004).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Chintalapati, M. & Moorjani, P. Evolution of the mutation rate across primates. Curr. Opin. Genet. Dev. 62, 58–64 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Rodin, R. E. et al. The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing. Nat. Neurosci. 24, 176–185 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cayuela, H. et al. Thermal adaptation rather than demographic history drives genetic structure inferred by copy number variants in a marine fish. Mol. Ecol. 30, 1624–1641 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Kess, T. et al. A putative structural variant and environmental variation associated with genomic divergence across the Northwest Atlantic in Atlantic Halibut. ICES J. Mar. Sci. 78, 2371–2384 (2021).

    Article 

    Google Scholar 

  • Le Moan, A., Bekkevold, D. & Hemmer-Hansen, J. Evolution at two time frames: ancient structural variants involved in post-glacial divergence of the European plaice (Pleuronectes platessa). Heredity (Edinb). 126, 668–683 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ruigrok, M. et al. The relative power of structural genomic variation versus SNPs in explaining the quantitative trait growth in the marine teleost Chrysophrys auratus. Genes (Basel). 13, 1129 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • De la Herran, R. et al. A chromosome-level genome assembly enables the identification of the follicle stimulating hormone receptor as the master sex determining gene in Solea senegalensis. Mol. Ecol. Resour. 00, 1–19 (2023).

    Google Scholar 

  • Harrison, P. W. et al. The FAANG data portal: Global, open-access, “FAIR”, and richly validated genotype to phenotype data for high-quality functional annotation of animal genomes. Front. Genet. 12, 639238 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Figueras, A. et al. Whole genome sequencing of turbot (Scophthalmus maximus; Pleuronectiformes): A fish adapted to demersal life. DNA Res. 23, 181–192 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Moore, J. S. et al. Conservation genomics of anadromous Atlantic salmon across its North American range: Outlier loci identify the same patterns of population structure as neutral loci. Mol. Ecol. 23, 5680–5697 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Barrio, A. M. et al. The genetic basis for ecological adaptation of the Atlantic herring revealed by genome sequencing. Elife 5, e12081 (2016).

    Article 

    Google Scholar 

  • Pettersson, M. E. et al. A chromosome-level assembly of the Atlantic herring genome-detection of a supergene and other signals of selection. Genome Res. 29, 1919–1928 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Bo, J. et al. Opah (Lampris megalopsis) genome sheds light on the evolution of aquatic endothermy. Zool. Res. 43, 26–29 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wang, S. et al. Resequencing and SNP discovery of Amur ide (Leuciscus waleckii) provides insights into local adaptations to extreme environments. Sci. Rep. 11, 5064 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Meng, Z., Hu, P., Lei, J. & Jia, Y. Expression of insulin-like growth factors at mRNA levels during the metamorphic development of turbot (Scophthalmus maximus). Gen. Comp. Endocrinol. 235, 11–17 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Duan, C., Ren, H. & Gao, S. Insulin-like growth factors (IGFs), IGF receptors, and IGF-binding proteins: Roles in skeletal muscle growth and differentiation. Gen. Comp. Endocrinol. 167, 344–351 (2010).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Duan, C., Ding, J., Li, Q., Tsai, W. & Pozios, K. Insulin-like growth factor binding protein 2 is a growth inhibitory protein conserved in zebrafish. Proc. Natl. Acad. Sci. USA 96, 15274–15279 (1999).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Furqon, A., Gunawan, A., Ulupi, N., Suryati, T. & Sumantri, C. A Polymorphism of Insulin-like growth factor binding protein 2 gene associated with growth and body composition traits in Kampong Chickens. J. Vet. 19, 183 (2018).

    Google Scholar 

  • Kibbey, M. M., Jameson, M. J., Eaton, E. M. & Rosenzweig, S. A. Insulin-like growth factor binding protein-2: Contributions of the C-terminal domain to insulin-like growth factor-1 binding. Mol. Pharmacol. 69, 833–845 (2006).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Coughlan, J. P. et al. Microsatellite DNA variation in wild populations and farmed strains of turbot from Ireland and Norway: A preliminary study. J. Fish Biol. 52, 916–922 (1998).

    Article 
    CAS 

    Google Scholar 

  • Zhang, H. et al. Characterization and Identification of Single Nucleotide Polymorphism within the IGF-1R gene associated with growth traits of Odontobutis potamophila. J. World Aquac. Soc. 49, 366–379 (2018).

    Article 
    CAS 

    Google Scholar 

  • Guo, L., Yang, S., Li, M. M., Meng, Z. N. & Lin, H. R. 2016) Divergence and polymorphism analysis of IGF1Ra and IGF1Rb from orange-spotted grouper, Epinephelus coioides (Hamilton). Genet. Mol. Res. 15, 1. https://doi.org/10.4238/gmr15048768 (2016).

    Article 
    CAS 

    Google Scholar 

  • Yu, X. et al. Genome-wide association analysis of adaptation to oxygen stress in Nile tilapia (Oreochromis niloticus). BMC Genomics 22, 426 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Harano, T. et al. Hemoglobin Kawachi [α44 (CE2) Pro → Arg]: A new hemoglobin variant of high oxygen affinity with amino acid substitution at α1β2 contact. Hemoglobin 6, 43–49 (1982).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Alharby, E. et al. A homozygous potentially pathogenic variant in the PAXBP1 gene in a large family with global developmental delay and myopathic hypotonia. Clin. Genet. 92, 579–586 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Ceinos, R. M. et al. Differential circadian and light-driven rhythmicity of clock gene expression and behaviour in the turbot, Scophthalmus maximus. PLoS ONE 14, e0219153 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Nishiwaki-Ohkawa, T. & Yoshimura, T. Molecular basis for regulating seasonal reproduction in vertebrates. J. Endocrinol. 229, R117–R127 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Wood, S. H. et al. Circadian clock mechanism driving mammalian photoperiodism. Nat. Commun. 11, 4291 (2020).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Piovesan, D. et al. DisProt 7.0: A major update of the database of disordered proteins. Nucl. Acids Res. 45, 219–227 (2017).

    Article 

    Google Scholar 

  • Pajkos, M. & Dosztányi, Z. Chapter Two – Functions of intrinsically disordered proteins through evolutionary lenses. in Dancing Protein Clouds: Intrinsically Disordered Proteins in the Norm and Pathology, Part C (ed. Uversky, V. N. B. T.-P. in M. B. and T. S.) vol. 183 45–74 (Academic Press, 2021).

  • Malagrinò, F. et al. Understanding the binding induced folding of intrinsically disordered proteins by protein engineering: Caveats and pitfalls. Int. J. Mol. Sci. 21, 3484 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Doyle, A., Cowan, M. E., Migaud, H., Wright, P. J. & Davie, A. Neuroendocrine regulation of reproduction in Atlantic cod (Gadus morhua): Evidence of Eya3 as an integrator of photoperiodic cues and nutritional regulation to initiate sexual maturation. Comput. Biochem. Physiol. -Part A Mol. Integr. Physiol. 260, 111000 (2021).

  • Silver, S. J., Davies, E. L., Doyon, L. & Rebay, I. Functional dissection of eyes absent reveals new modes of regulation within the retinal determination gene network. Mol. Cell. Biol. 23, 5989–5999 (2003).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jin, M. & Mardon, G. Distinct biochemical activities of eyes absent during drosophila eye development. Sci. Rep. 6, 23228 (2016).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • McGowan, K. L., Passow, C. N., Arias-Rodriguez, L., Tobler, M. & Kelley, J. L. Expression analyses of cave mollies (Poecilia mexicana) reveal key genes involved in the early evolution of eye regression. Biol. Lett. 15, 20190554 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Cui, W. et al. Transcriptomic analysis reveals putative osmoregulation mechanisms in the kidney of euryhaline turbot Scophthalmus maximus responded to hypo-saline seawater. J. Oceanol. Limnol. 38, 467–479 (2020).

    Article 
    CAS 

    Google Scholar 

  • Mármol-Sánchez, E., Quintanilla, R., Cardoso, T. F., Jordana Vidal, J. & Amills, M. Polymorphisms of the cryptochrome 2 and mitoguardin 2 genes are associated with the variation of lipid-related traits in Duroc pigs. Sci. Rep. 9, 9025 (2019).

    Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Takvam, M., Wood, C. M., Kryvi, H. & Nilsen, T. O. Ion transporters and osmoregulation in the didney of teleost fishes as a function of salinity. Front. Physiol. 12, 664588 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Engelund, M. B. & Madsen, S. S. The role of aquaporins in the kidney of euryhaline teleosts. Front. Physiol. 2, 51 (2011).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Nam, B. H. et al. Identification and characterization of the prepro-vasoactive intestinal peptide gene from the teleost Paralichthys olivaceus. Vet. Immunol. Immunopathol. 127, 249–258 (2009).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Paladini, F. et al. Age-dependent association of idiopathic achalasia with vasoactive intestinal peptide receptor 1 gene. Neurogastroenterol. Motil. 21, 597–602 (2009).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Hosseinpour, L., Nikbin, S., Hedayat-Evrigh, N. & Elyasi-Zarringhabaie, G. Association of polymorphisms of vasoactive intestinal peptide and its receptor with reproductive traits of turkey hens. South Afr. J. Anim. Sci. 50, 345–352 (2020).

    Article 
    CAS 

    Google Scholar 

  • Pereiro, P., Figueras, A. & Novoa, B. A novel hepcidin-like in turbot (Scophthalmus maximus L.) highly expressed after pathogen challenge but not after iron overload. Fish Shellfish Immunol. 32, 879–889 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Zhang, J., Yu, L., Ping, L., Fei, M. & Sun, L. Turbot (Scophthalmus maximus) hepcidin-1 and hepcidin-2 possess antimicrobial activity and promote resistance against bacterial and viral infection. Fish Shellfish Immunol. 38, 127–134 (2014).

    Article 
    PubMed 

    Google Scholar 


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