Identification of Growth Hormone (GH) Gene Polymorphisms and Their Association with Growth Traits in European Sea Bass (Dicentrarchus labrax)

Abstract

The growth hormone (GH) gene has an important regulatory roles in postnatal somatic growth, metabolism and development of vertebrates and fish. The aim of this study was to identify the genetic variation of the GH gene and its associations with growth traits by DNA sequencing in 200 European sea bass (Dicentrarchus labrax) individuals. Ten novel SNPs were identified as g.1557 A > T, g.1611 T > C, g.1663 C > G, g.1799 T > C, g.1824 T > C, g.1912 T > A, g.2052 G > C in the 1st partial intron, 2nd exon, 2nd intron and 3rd partial exon of GH gene in European sea bass. The genotypes of GH g.1611 T > C locus were found associated with total weight, fillet weight and head length (p < 0.05). Association between the genotypes of GH g.1557A > T and pre-anal length, abdominal length were found statistically significant (p < 0.05). Similarly, the genotypes of GH g.1799 T > C locus which caused the amino acid change from Leucine to Serine (L8S) were found related to body length and abdominal length (p < 0.05). This amino acid change also caused the 3D tertiary structure of the GH peptide. Thus, these SNPs have an effect on the growth traits of European sea bass and could be used for genomic selection in European sea bass breeding.

Introduction

In recent years, aquaculture production becomes one of the most demanded product lines in the food sector due to reasons such as population growth around the world, a decrease in natural fish stocks and consumer preferences. Turkey is among the leading countries in the production of marine fish in the Mediterranean region. The Aegean Sea is one of the most suitable areas for aquaculture in the Mediterranean basin worldwide. European sea bass, which is one of the most important aquaculture species in the Mediterranean, ranks 31st in world aquaculture production, while Turkey is the first producer (FAO, 2021). European sea bass production in Turkey was around 149 thousand tones in 2020 and in the world production of European sea bass was around 236 thousand tones in 2019 (FAO, 2021). A large amount of sea bass grown in Turkey is exported to European Union countries (TUIK, 2021).

Growth hormone (GH) is synthesized by acidophilic cells in the anterior part of the pituitary gland (Hu et al., 2019). The growth hormone has a crucial role in many aquaculture species due to its regulatory role in ionic and osmotic balance, muscle growth, protein, carbohydrate and lipid metabolism development and performance (McCormick, 2001; Cheng and Sun, 2015; Bi et al., 2021; Nisembaum et al., 2021). The role of somatotropic axis hormone (GH, GH-receptor (GHR) and IGF-1) genes is very important from fertilization until the early stages of larval development in vertebrates (Besseau et al., 2013). GH gene is considered to be the main candidate gene regulating metamorphosis in fish larvae, growth in vertebrate fish and osmoregulation against the rapid salinity changes (McCormick, 2001; Clayton et al., 2011; Quik et al., 2010; Bi et al., 2021). The transcription of the GH/IGF axis genes is altered in the physiological response to the increase of salinity stress in environments with fluctuating patterns of salinity (Bi et al., 2021). GH gene also has been reported to be associated with linear growth, feed utilization and fasting metabolism (McMenamin and Parichy 2013; Wang et al. 2013).

European sea bass can reach a market size of 250–400 gr in a period of 18–24 months in Mediterranean conditions (Vandeputte et al., 2019). Increasing the meat yield while shortening the long growing period in fish such as sea bass is one of the foremost issues of fish breeding (De-Santis and Jerry, 2007). It is revealed that the transgenic GH genes could importantly increase the growth rate due to conserved regulatory functions of GH in somatic growth in many (more than 30) fish species (Li et al., 2010). For this reason, it is important to identify the genes on the fish genome that are associated with growth and meat traits. Many studies have been carried out on the relation between GH gene polymorphisms and growth traits in many species of fishes such as Salvelinus alpinus (Tao and Boulding, 2003) Cynoglossus semilaevis (Zhao et al. 2014), Pelteobagrus fulvidraco (Li et al. 2017), Oreochromis niloticus (Jaser et al., 2017) Cyprinus carpio (Liu et al. 2017, Hu et al., 2019) and Siniperca chuatsi (Li et al., 2016, Sun et al., 2019). However, the associations between GH gene polymorphisms and growth traits of European sea bass have remained unknown in Mediterranean conditions. The aim of the study is to identify GH gene polymorphisms and their associations with growth traits using DNA sequencing in European sea bass.

Materials And Methods

Sampling and DNA isolation

A total of 200 European sea bass individuals that were reared and managed under the same environmental conditions (natural photoperiod in net cages) in a commercial fish farm were collected randomly from the male individuals in the reproduction period at the age of 24 months from Processing Factory in İzmir (location 38°11'1.54"N 26°27'22.70"E). The fishes were categorized as a commercial grading in 4 different groups of weights (1st group, 210–300 g; 2nd group, 300–450 g; 3rd group, 450–600 g; 4th group, 600–750 g). The body depth (BD, cm), standard length (SL, cm), head length (HL, cm), body length (BL, cm), pre-anal length (PAL, cm), abdominal length (AL, cm), post-anal length (POSTAL, cm), head depth (HD, cm), total weight (TW, g), fillet weight (FL, g) of each sample were measured and muscle tissue samples were taken and stored in 96% ethanol at -20°C until DNA extraction. Genomic DNA was extracted by using GeneMATRIX Tissue & Bacterial DNA Purification Kit (EURx Ltd, Gdansk, Poland) according to the manufacturer's protocols. The purity and concentration of DNA samples were checked by using 1% agarose gel electrophoresis and spectrophotometer (MN-913 MaestroNano Micro-Volume Spectrophotometer, Maestrogen, Taiwan).

Primer design and PCR amplification of GH gene

Primer sequences of the GH gene were designed based on the European sea bass sequence retrieved from GenBank (Accession number GQ918491) using the Primer-BLAST algorithm (https:// www.ncbi.nlm.nih.gov/tools/primer-blast/). Primer sequences of GH gene are F: 5’- GTGATCAGTCGGGTTCAGGT-3’ and R: 5’-CGTTGTGTCTCGTGCTTGTC-3’. For amplification reactions, the 50 µL PCR volume contained: 100 ng genomic DNA, 0.5 µM of each primer and 2X MyTaq™ Mix (Meridian Bioscience, USA). The PCR temperature cycling conditions were as follows: initial denaturation at 95°C for 3 min; 35 cycles of denaturation at 95°C for 30 s, annealing at 60°C for 30 s, and elongation at 72°C for 60 s. The final cycle was followed by an extension at 72°C for 10 min. Afterward, the PCR products were checked on 1.5% agarose gel using horizontal electrophoresis and the gels were stained using RedSafe™ (iNtRON Biotechnology, Korea)

Sequencing

The 576 bp of the GH gene region was sequenced on an Applied Biosystems 3500XL Genetic Analyzer System (Applied Biosystems, USA). The sequences were checked by ChromasPro Version 2.1.8 (Technelysium Pty. Ltd. Australia). Expasy resource portal from the Swiss Institute of Bioinformatics (SIB) was used to translate the nucleotide sequence of the GH gene region to amino acid sequence (https://web.expasy.org/translate/). The 3D tertiary structure of the proteins based on the studied GH gene region was predicted using the I-TASSER server (Yang et al., 2015).

Statistical Analysis of GH gene

Genotypes of SNPs were tested for the Hardy–Weinberg equilibrium (HWE) with “HardyWeinberg” package in R software (R version R-3.4.3) (R Core Team, 2013). The associations between the genotypes of GH locus and the measured traits were analyzed via SPSS Ver. 21.0 (IBM Corporation, NY, USA) according to a general linear model and an alpha value of 0.05 was chosen as the significance level.

Linear Model I = Y_ijk = µ + B_i + G_j + e_ijk

Where Y_ijk represents the traits; µ represents the intercept; B_i represents the group effect, G_j represents the effect of GH genotype and e_ijk is the random error.

The significance of differences between groups was determined using one-way analysis of variance (ANOVA) and Tukey’s multiple range test. The thresholds for significant and highly significant differences were P < 0.05 and P < 0.01, respectively.

Results

The genetic variation at 576 bp of the partial GH gene was amplified by PCR and it is shown in Fig. 1. 1st partial intron, 2nd exon, 2nd intron and 3rd partial exon regions of GH gene in the European sea bass were investigated using DNA sequencing in this study (Fig. 2a; 2b). The European sea bass GH gene contains six exons and five introns that encode 204 amino acids (GQ918491) (NCBI, 2022). The studied GH gene region is located between 1551–2126 bp in the NCBI GenBank database (GQ918491). All SNPs and the partial DNA sequences of GH gene in sea bass were declared for the first time in this study and the studied sequences were submitted to the NCBI GenBank database with the following accession numbers MN329680-5 and ON035500-12.

The variations of the European sea bass GH gene identified in this study and their comparison with the reference sequence from NCBI GenBank was shown in Table 1. In the studied European sea bass samples nonsynonymous amino acid changes have been found from leucine to serine (L8S) and from serine to threonine (S28T) in the second exon region. Similarly, two synonymous SNPs have been seen in serine and phenylalanine amino acids in the second exon and leucine amino acids in the third exon region of the GH gene. These four synonymous and nonsynonymous amino acid changes in the second exon region are shown in Fig. 3.  

The predicted 3D tertiary structure of the European sea bass GH peptide and the effect of the detected amino acid changes on its 3D tertiary structure are shown in Fig. 4. While the C-score of native 3D tertiary structure of GH peptide was =-0.13 (estimated TM-score = 0.70 ± 0.12, estimated root-mean-square deviation (RMSD) = 5.7 ± 3.6Å), the C-score of GH peptide with the amino acid change (L8S) were 0.39 (estimated TM-score = 0.77 ± 0.10, estimated RMSD = 4.6 ± 3.0Å) and the C-score of GH peptide with the two amino acid changes were C-score = 0.19 (estimated TM-score = 0.74 ± 0.11, estimated RMSD = 5.0 ± 3.2Å).

The allele and genotype frequencies of the GH gene region in studied European sea bass samples are shown in Table 2. Three SNPs (1824 T > C, 1912 T > A and 2052 G > C) have found only three animals and the allele and genotype frequencies were not shown in Table 2. The GH gene g.1557A > T, g.1663C > G, g.1684T > C and g.1799T > C loci are in HWE, whereas the g.1611T > C, g.1769T > C and g.1857C > T loci are not in HWE. The AA genotype has not been seen in GH g.1557A > T locus, similarly, the GG genotype has not been seen in GH g.1663 C > G locus in the studied samples.

Associations between the genotypes of GH genotypes gene and growth traits

Four different weight groups of individuals that were commercially graded are recorded in this study and the means of these measurements were shown in Table 3. As a result of the relationship analysis based on the ANOVA, the observed difference between the groups was significant (P < 0.05). The associations between the genotypes of GH loci and morphological traits were analyzed and the significant associations were summarized in Table 4 (P < 0.05). There was not a significant correlation between body depth, standard length, body length, post-anal length, head depth and the SNPs. There was a significant correlation between total weight, fillet weight, head length, pre-anal length, body length, abdominal length traits and the genotypes for g.1557 A > T, g.1611 T > C, g.1663 C > G, g.1799 T > C loci (P < 0.05). The genotypes for g.1611 T > C were associated with total weight, fillet weight and head length (P < 0.05). Also, the genotypes for g.1557 A > T were associated with the pre-anal length and abdominal length (P < 0.05). The genotypes of g.1663C > G and g.1799T > C loci which caused the amino acid change from Leucine (L) to Serine (S) were found associated with body length and abdominal length (P < 0.05).

Discussion

In the current study, 576 bp long 1st partial intron, 2nd exon, 2nd intron and 3rd partial regions of the GH gene were investigated by DNA sequencing. Five SNPs in the first intron, four SNPs in the second exon region and one SNP in the third exon region were found in the GH gene in farmed European sea bass populations. Three SNPs as g.1557 A > T, g.1611 T > C and g.1663 C > G located in the first intron region were found associated with total weight, fillet weight, head length, pre-anal length and abdominal length, body length traits. Although intronic regions do not encode proteins, they have important regulatory roles in mRNA splicing, gene transcription and expression (Pagani and Baralli 2004; Sun et al., 2019). SNPs in non-coding regions such as introns can participate in the modulation of gene expression and cause changes in biological properties such as growth (Kuhl et al., 2010; Özcan Gökçek et al., 2020; Özcan Gökçek and Işık, 2020). Compared to exons, intronic regions are more prone to gene mutations. Because introns are longer, selective pressure is lower, and can easily accumulate multiple mutations (Zhang et al., 2016). The GH hormone is the one of main hormones controlling metamorphosis in fish larvae and growth (McMenamin and Parichy 2013; Wang et al. 2013). The polymorphisms in the intron region of the GH gene may affect on economical traits. Tao and Boulding (2003) have reported that early-stage growth in Salvelinus alpicus is significantly affected by the SNP in the introgenic region of the GHRH (Growth Hormone Releasing Hormone) locus, which regulates growth hormone secretion.

In this study we have detected five SNPs as g.1799 T > C, 1824 T > C, g.1857 C > T, 1912 T > A and 2052 G > C in the second and third exon regions of the GH gene. The genotypes for g.1799T > C which caused the nonsynonymous amino acid change from leucine to serine were found associated with body length and abdominal length in European sea bass (P < 0.05). Similarly to our results, Li et al. (2016) have revealed that two SNPs (g.5045T > C, g.5234T > G) in the 5th exon and 5th intron regions of the GH gene were associated with growth performance in the Sniperca chuatsi population (P < 0.05). It was revealed that three SNPs detected in the GH gene in yellow catfish (Pelteobagrus fulvidraco) were significantly associated with yield characteristics such as body thickness, caudal pedicle length and body length (Li et al., 2017). In another study, Levesque et al. (2008) have found that GH administration affects the proliferative response in terms of faster growth and more myogenic progenitor cell proliferation in the transgenic Atlantic salmon (Salmo salar). Similarly, Tian et al. (2014) have reported the four SNPs that they identified in the GH gene were significantly related to the growth characteristics and these loci could be used for MAS in Siniperca chuatsi populations. Sun et al. (2019) found a total of thirty two SNPs in the Siniperca chuatsi GH gene, one in the fifth exon, thirty one in intronic regions and four diplotypes, and reported four of these polymorphic loci were associated with economically important growth characteristics. One of the four diplotype was significantly higher than the other diplotypes for body weight, total length and body length (P < 0.05). Hu et al. (2019) have found an SNP and a 4-bp indel in the third intron, and three synonymous SNPs in exon 4 in the GH gene of common carp. They also identified four haplotypes and ten diplotypes in Heilongjiang carp Cyprinus carpio haematopterus, German mirror carp Cyprinus carpio L. mirror and Purse red carp Cyprinus carpio var. wuyuanensis breeds in China. They revealed the H2H2 diplotype fish have higher body weight and net weight than the other diplotypes in the Heilongjiang carp breed (P < 0.05). In Southern China Liu et al., (2017) have found associations between SNPs in the third exon and intron regions of the GH gene with growth traits in common carp. In the GH gene, SNPs not just exon and intron regions, but also promotor and 5'UTR regions have an important effects on growth traits. Jaser et al. (2017) have identified ten SNPs, nine in the proximal promoter region and one in the 5'UTR region of the Nile tilapia (Oreochromis niloticus) GH gene, and reported that five genotypes of these SNPs were associated with the highest market weight.

C-score is a confidence score that is estimated from the significance of threading template alignments and the convergence parameters of the structure assembly simulations for calculating the quality of predicted models by I-TASSER. C-score is varying from − 5 to 2 and while a C-score has a higher value, it means signifies a model with high confidence and vice-versa. TM-score and RMSD are known standards for measuring structural similarity between two structures which are usually used to measure the accuracy of structure modeling when the native structure is known. C-score is highly correlated with TM-score and RMSD (Yang et al., 2015). The L8S amino acid change improved the reliability of GH protein from − 0.13 to 0.39. It is seen that the two amino acid changes L8S and S28T increased the reliability and stability of the GH protein from − 0.13 to 0.19.

Conclusions

In summary, the present study investigated the genetic variations of the GH gene in European sea bass populations reared in Mediterranean conditions. We have found ten SNPs, five SNPs in the first intron region and five SNPs in the exon regions of the GH gene in farmed European sea bass. Association analysis indicated that some of these SNPs in the GH gene are related to growth traits and these SNPs could be used for genomic selection in European sea bass breeding by including SNP array.

Declarations

Author contributions EÖG and RI developed the research topic and acted as study principal investigator (PI). EÖG, BK and KG collected phenotypic data, EÖG and RI performed genetic data and statistical analysis, and wrote the manuscript. 

Funding This work was supported by the Scientific Research Projects Coordination Unit of Ege University (Project No: FKP-2020-21912).

Data availability The authors confirm that the data supporting the findings of this study are available within the article.

Code availability Not applicable.

Ethics approval Animal handling was conducted in accordance with the guidelines of the University of Ege Animal Ethics Committee.

Consent to participate Not applicable.

Consent for publication All authors review and approve the manuscript for publication.

Conflicts of interest The authors declare that there are no conflicts of interest to disclose. 

References

1. Besseau L, Fuentes M, Sauzet S, Beauchaud M, Chatain B, Covès D, Boeuf G, Falcón J (2013) Somatotropic axis genes are expressed before pituitary onset during zebrafish and sea bass development. Gen Comp Endocrinol 194:133–141. https://doi.org/10.1016/j.ygcen.2013.08.018
2. Bi B, Gao Y, Jia D, Kong L, Su Y, Rong H, Wu X, Wang X, Hu Z, Hu Q (2021) Growth influence of juvenile golden trout (Oncorhynchus mykiss) in different osmotic conditions: implications for tissue histology, biochemical indicators, and genes transcription involved in GH/IGF system. Fish Physiol Biochem 47:583–597. https://doi.org/10.1007/s10695-021-00933-w
3. Cheng L, Sun YH (2015) Polymorphisms in a myostatin gene and associations with growth in a hybrid of Culter alburnus and Ancherythroculter nigrocauda. Genet Mol Res 14(2):5615–5620. https://doi.org/10.4238/2015.may.25.13
4. Clayton PE, Banerjee I, Murray PG, Renehan AG (2011) Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat Rev Endocrinol 7:11–24. https://doi.org/10.1038/nrendo.2010.171
5. De-Santis C, Jerry DR (2007) Candidate growth genes in finfish–where should we be looking? Aquac 272:22–38. https://doi.org/10.1016/j.aquaculture.2007.08.036
6. FAO (2022) Fishery and Aquaculture Statistics.1976–2019. . Accessed January 2022
7. Hu X, Li C, Luan P, Ge Y, Jia Z, Zhang Q, Shi L (2019) A novel diplotype in the GH gene associated with body weight traits around the first overwintering period in common carp (Cyprinus carpio L.) cultured in Northeast China. Aquac 511:734214. https://doi.org/10.1016/j.aquaculture.2019.734214
8. Jaser SKK, Dias MAD, Lago ADA, Reis Neto RV, Hilsdorf AWS (2017) Single nucleotide polymorphisms in the growth hormone gene of Oreochromis niloticus and their association with growth performance. Aquac Res 48(12):5835–5845. https://doi.org/10.1111/are.13406
9. Kuhl H, Beck A, Wozniak G, Canario A, Volckaert F, Reinhardt R (2010) The European sea bass Dicentrarchus labrax genome puzzle: comparative BAC-mapping and low coverage shotgun sequencing. BMC Genom 11:68. https://doi.org/10.1186/1471-2164-11-68
10. Li G, Gu Y, Xu P, Lu X, Wang P, Sun J, Wang H (2016) Polymorphism in growth hormone gene and its association with growth traits in Siniperca Chuatsi. Isr J Aquac 68:1257–1265. http://dx.doi.org/10.46989/001c.20833
11. Li MJ, Liu WS, Luo W, Zhang XQ, Zhu WL, Wang J, Liao LY, Li GH (2017) Polymorphisms and their association with growth traits in the growth hormone gene of yellow catfish, (Pelteobagrus fulvidraco). Aquaculture 469:117–123. https://doi.org/10.1016/j.aquaculture.2016.11.028
12. Liu X, Liang H, Liang Y, Li Z, Qin X, Zhang T (2017) Significant associations of polymorphisms in the growth hormone gene with growth traits in common carp (Cyprinus carpio). Meta Gene 14:38–41. https://doi.org/10.1016/j.mgene.2017.07.008
13. McCormick SD (2001) Endocrine control of osmoregulation in teleost fish. Am Zool 41:781–794. https://doi.org/10.1093/icb/41.4.781
14. McMenamin SK, Parichy DM (2013) Metamorphosis in teleosts. Curr Top Dev Biol 103:127–165. https://doi.org/10.1016/b978-0-12-385979-2.00005-8
15. Nisembaum LG, Martin P, Lecomte F, Falcón J (2021) Melatonin and osmoregulation in fish: A focus on Atlantic salmon Salmo salar smoltification. J Neuroendocrinol 33:e12955. https://doi.org/10.1111/jne.12955
16. Özcan Gökçek E, Işık R, Karahan B, Gamsız K (2020) Genetic variation of Insulin-like growth factor II (IGF-II) gene and its associations with growth traits in European sea bass (Dicentrarchus labrax). Turkish J Fish Aquat Sci 20(7):541–548. http://doi.org/10.4194/1303-2712-v20_7_04
17. Özcan Gökçek E, Işık R (2020) Associations between genetic variants of the insulin-like growth factor I (IGF-I) gene and growth traits in European sea bass (Dicentrarchus labrax, L.). Fish Physiol Biochem 46:1131–1138. https://doi.org/10.1007/s10695-020-00779-8
18. Pagani F, Baralle FE (2004) Genomic variants in exons and introns: identifying the splicing spoilers. Nat Rev Genet 5(5):389–396. https://doi.org/10.1038/nrg1327
19. Quik EH, van Dam PS, Kenemans JL (2010) Growth hormone and selective attention: A review. Neurosci Biobehav Rev 34:1137–1143. https://doi.org/10.1016/j.neubiorev.2010.01.001
20. R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. URL http://www.R-project.org/
21. Sun CF, Sun HL, Dong JJ, Tian YY, Hu J, Ye X (2019) Correlation analysis of mandarin fish (Siniperca chuatsi) growth hormone gene polymorphisms and growth traits. J Genet 98(2):1–10
22. Wang H, Sun J, Lu X, Wang P, Xu P, Zeng L, Yu D, Li G (2013) Identification of insulin-like growth factor I gene polymorphisms using high-resolution melting and its effect on growth traits in sinipercid species. Fish Sci 79:439–446. https://doi.org/10.1007/s12562-013-0607-8
23. Tao WJ, Boulding EG (2003) Associations between single nucleotide polymorphisms in candidate genes and growth rate in Arctic charr (Salvelinus alpinus L.). J Hered 91:60–69. https://doi.org/10.1038/sj.hdy.6800281
24. Tian C, Yang M, Lv L, Yuan Y, Liang X, Guo W, Song Y, Zhao C (2014) Single nucleotide polymorphisms in growth hormone gene and their association with growth traits in Siniperca chuatsi (Basilewsky). Int J Mol Sci 15:7029–7036. https://doi.org/10.3390/ijms15047029
25. TUİK (2022) Turkish Statistical Institute aquaculture statistics, https://biruni.tuik.gov.tr/medas/?kn=97&locale=tr Accessed 18 February 2022
26. Vandeputte M, Gagnaire PA, Allal F (2019) The European sea bass: a key marine fish model in the wild and in aquaculture. Anim Genet 50(3):195–206. https://doi.org/10.1111/age.12779
27. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER Suite: protein structure and function prediction. Nat Methods 12:7–8. https://doi.org/10.1038/nmeth.3213
28. Zhang S, Zhong L, Qin Q, Wang M, Pan J, Chen X, Bian W (2016) Three SNPs polymorphism of growth hormone-releasing hormone gene (GHRH) and association analysis with growth traits in channel catfish. Acta Microbiol Sin 40(5):886–893
29. Zhao J, He F, Wen H, Li J, Si Y (2014) Correlation between the polymorphism of GH gene of male half-smooth tongue sole and their growth traits and hormone content. Period Ocean Univ China 44:35–40