Relationship between Single Nucleotide Polymorphism of IGF-1 Gene in Nile Tilapia (Oreochromis niloticus) and Weight Gain

Ⅰ. Introduction

Nile tilapia (Oreochromis niloticus) is a fish of the cichlid family. Insulin-like growth factor 1 (IGF-1) is a member of the insulin family and is an important gene involved in animal growth (Teng et al. 2020; Aljuboory and Alkhshali, 2018; Aljuboory and Alkhshali, 2018; Breidy Lizeth Cuevas-Rodríguez et al., 2016). IGF-1 regulates animal growth, development and metabolism, and plays an important role in regulating cell growth and differentiation. Researches of SNPs are also an important species improvement method in modern aquatic research (Liu et al., 2007; Feng, Yu, and Tong, 2014; Zhang et al., 2016). In addition, monitoring SNPs contributes to the traceability of many cases of aquatic fish diseases (Feng Ying et al., 2018; Nie et al., 2019; Gu et al., 2018). Variations in IGF 1 gene had an important effect on the muscle growth and body development of tilapia (Zeng et al., 2021; Laible, Wei, and Wagner, 2015). We will study the relationship between the IGF1 gene and body weight change during the growth of tilapia cultured in Janghang fish farm.

Ⅱ. Materials and Methods

2. PCR amplification and DNA sequencing analysis

We designed tilapia-specific polymerase chain reaction (PCR) primers for the promoter region, 5'UTR, and 3'UTR of the IGF-1 gene, shown in table (<Table 1>) using the NCBI database sequence (IGF-1, GenBank accession number is NC_031981). DNA amplification was performed by PCR. The composition of the PCR master mix was as follows: 0.25 µl Ex Taq DNA polymerase, 5 µl Buffer 10x, 4 µl dNTPs, 2 µl Forward Primer, 2 µl Reverse Primer, 0.5 µl genomic DNA, and 36.25 µl of distilled water. The annealing temperature was calculated for each primer pair. The thermal cycle program was set to 94℃ for 5 minutes (pre-denaturation), 94℃ for 30 seconds for denaturation, annealing temperature for 30 seconds, and at 72℃ extension time depending on the length of the PCR product. A FavorPrep GEL/PCR Purification Mini kit was used for electrophoresis and gel purification of the PCR products, which were then submitted to Macrogen CO (Macrogen Building, 238 Teheran-ro, Gangnam-gu, Seoul, Korea).

<Table 1>

Primer designs for PCR in IGF-1 genes devise

Ⅲ. Results

1. Analysis and classification of sample DNA results

This study was helpful as we explored effective techniques for discovering SNPs in the IGF-1 gene that can regulate muscle growth traits. We found a total of 9 SNPs in the IGF-1 gene, of which one site (~80bp) was found at the promoter region with a C/T change, and 3 sites were found in the 5'UTR at ~63bp (G/C), ~404bp (G/A), and ~443 bp (G/C). In the 3'UTR, we found a total of five SNPs at 18255bp (T/A), 18280bp (G/A), 18381 (G/A), 18425 (C/T), and 18456 (G/T). The location, base types, and the percentages of each SNPs were shown in <Tables 2> and <Tables 3>.

<Table 2>

The location, base types and allele ratio of each SNPs in Nile tilapia male

<Table 3>

Allele ratio of each SNPs in Nile tilapia female

The average value of polymorphism was higher in exon regions than in intron and promoter regions.

2. Summary of analysis sample results

The relationship between the Genotype distribution and average body weight of male Nile tilapia is described in detail in <Table 4>. There are a total of 23 genotypes, The average individual body weight ranges from 1.33 kg to 0.61 kg.

<Table 4>

Genotype blocks and its average body weight in male Nile tilapia

With a total of 18 genotypes, <Table 5> details the link between the genotype distribution and average body weight of female Nile tilapia. The average body weight of an individual might range from 1.18 kg to 0.30 kg.

<Table 5>

Genotype blocks and its average body weight in male Nile tilapia

The results were combined according to the above data analysis; samples with the same genotypes were combined, and repeated similar genes were deleted. As shown in Table 6, a total of 32 fish samples with different genotypes were obtained for reference, Each genotype block (GB) with specific SNP type were showm in Table 6. GBF1 to GBF9（GBF: Genotype Blocks IGF-1） are the common genotypic blocks of male and female samples. GBF10 to GBF23 are unique genotypes for male samples, GBF24 to GBF32 are unique genotypes for female samples, and the GBF9 genotype is the wild-type genotype.

<Table 6>

Genotypic block as a whole distinguishes genotype divisions according to SNP type

3. Sample statistical analysis

The genotype of each male sample was considered separately, and the average value and the percentage of male samples overall was calculated according to the weight score. As shown in Figure 1, the following excellent genotypes were selected: GBF1, GBF2, GBF3, GBF4, GBF8, and GBF10.

[Fig. 1]

The relationship between male tilapia genotype block and body weight.*The X-axis and Y-axis represents the genotype-categorized male samples and their weight. The dotted line represents the average value of male samples 1.02kg. Green is the coloring of high-quality samples. Red is the coloring of poor-quality samples. Black and white are samples that are close to the average.

Considering the genotypes of the female samples separately, the average was calculated by weight and data from half of the total female samples. As shown in Figure 2, the excellent genetic samples we identified were as follows: GBF1, GBF2, GBF3, GBF24, GBF25, GBF26, and GBF27.

[Fig. 2]

The relationship between female tilapia genotype block and body weight. *The X-axis represents the female samples classified by genotype and the Y-axis weight. the dotted line represents the average weight of female samples 0.63kg. Green is to highlight high-quality samples, red is for inferior samples, and black and white are close to the average the sample is mediocre.

4. principal component analysis

A statistical method was used to transform a group of potentially correlated variables into a group of linearly uncorrelated variables through orthogonal transformation, and this group of variables after conversion is called the principal component. In actual subjects, many related variables (or factors) are often put forward to analyze the problem comprehensively because each variable reflects some information about the subject to varying degrees. When using statistical analysis methods to study multivariate topics, too many variables will increase the complexity. People naturally hope that fewer variables will result in more information. In many cases, there is a certain correlation between variables. When there is a certain correlation between two variables, the two variables reflect an overlap in information about the subject to a certain degree. A principal component analysis removes redundant variables (closely related variables) and establishes a smaller number of uncorrelated ones while retaining the original information as much as possible. This statistical method, the principal component analysis, is also used in mathematics to reduce dimensionality. It is created by collecting the body weight of the Nile tilapia the DNA sample was extracted from and determining its relationship with the average value.

As shown in the PKC diagram in Figure 3 and Figure 4, male GBF1 and female GBF2 is a specific genotypes with an outstanding phenotype.

[Fig. 3]

PCA analysis of male tilapia samples.*The weight of Nile tilapia was measured and recorded, and the sample DNA was extracted to further determine the genotype and classification. Single nucleotide polymorphism is the measurement point of the genotype variable of each sample in this study. In this figure, the Y-axis represents dimension 1 (dim1), and the calculated percentage is 43.3%, while the X-axis represents dimension DIM2, and the calculated percentage is 43.3%.

[Fig. 4]

PCA analysis of female tilapia samples.*The weight of Nile tilapia was measured and recorded, and the sample DNA was extracted to further determine the genotype and classification. Single nucleotide polymorphism is the measurement point of the genotype variable of each sample in this study. In this figure, the Y-axis represents dimension 1 (dim1), and the calculated percentage is 30.7%, while the X-axis represents dimension DIM2, and the calculated percentage is 30.7%.

Measure and record the body weight of Nile tilapia to extract sample DNA to further determine genotype and classification. Single nucleotide polymorphism is the measurement point of the genotypic variables of each sample in this study. In Figure 4, the Y-axis represents dimension 1 (Dim1), and the calculated percentage is 43.3%, while the X-axis represents the calculated percentage of dimension Dim2 is 43.3%. In Figure 5, the Y-axis represents dimension 1 (Dim1), and the calculated percentage is 30.7%, while the X-axis represents the dimension Dim2’s calculated percentage is 30.7%. The closer the Y-axis and X-axis percentages are, the more sufficient sample collection is and the more universal it is.

Ⅳ. Conclusion

According to the data of this study, it is concluded that IGF-1 plays a crucial regulatory role in the growth of Nile tilapia. According to the 9 controllable SNPs found in the IGF-1 gene, we can select individuals with excellent genotypes and after special cultivation, obtain high-quality biological products and food for humans. The use of SNP screening is an efficient and rapid method of species improvement experimentation.

V. Discussion

Nile tilapia (Oreochromis niloticus) has an increasing significance in aquaculture worldwide (Kuebutornye et al., 2020; Marjanovic et al., 2016; Zou et al., 2015; Kishawy et al., 2020; Richter et al. 2021; Wardani et al., 2021). Other applications of QTL technology in aquatic research have also produced extensive and far-reaching significance (Fernández, Villanueva, and Toro, 2021; Mohammed, Raji, and Igwebuike, 2020; Sullivan et al., 2015). In this study, we used individual samples from Nile tilapia to explore the relationship between SNPs in the IGF-1 gene and fish growth. Other contemporary research studies on IGF-1 in other animals helped our experiments (Lu et al., 2020; Tsai et al., 2014; Wuertz et al., 2006). We found a total of 9 SNPs. The body weight of male fish was commonly greater than that of female fish. The difference in growth and the the average growth rate varies with gender. We classified individual fish according to gender and weight. Due to the increasing demand for Nile tilapia genetic research, food sources, and aquaculture industry, many countries have focused on cultivating Nile tilapia, enriching human food nutrition sources, and high-quality biological commodity breeding industry and quality improvement projects for other species (Zhiyun et al., 2016; Zhou et al., 2019). The study of genetic markers provides key information and helps select individuals with excellent genotypes, conduct experiments, explore optimum breeding options, and improve species improvement (Agarwal et al., 2014). This article demonstrates the connection between IGF-1 SNPs and tilapia growth. These collected data demonstrate the importance of genetic research and exploring the regulatory roles of other fish growth genes. Nile tilapia performed well for marker-assisted sample selection.

Acknowledgments

This research was funded by the Development of software for data collection and analysis of growth rate according to environment factor of (semi) circulation filtration system (20180352).

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