Indian Journal of Animal Research

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Research Article

Indian Journal of Animal Research, volume 55 issue 4 (april 2021) : 378-383

Single Nucleotide Polymorphism of CDC37, AHSA1 and STIP1 Gene in Three Cattle Breeds using SNaPshot Technology

Xiao Wang1,2, Guang-Xin E1, Ri-Su Na1, Cheng-Li Liu1, Ze-Hui Guo1, Shu-Zhu Cheng1, Bai-Gao Yang1, Yong-Fu Huang1,*
1College of Animal Science and Technology, Chongqing Key Laboratory of Forage and Herbivore, Chongqing Engineering Research Centre for Herbivores Resource Protection and Utilization, Southwest University, Chongqing, 400716, China.
2Animal Husbandry and Veterinary Center, Kongtong District, Gansu Province, Gansu Kongtong, 744000, China.
Cite article:- Wang Xiao, E Guang-Xin, Na Ri-Su, Liu Cheng-Li, Guo Ze-Hui, Cheng Shu-Zhu, Yang Bai-Gao, Huang Yong-Fu (2021). Single Nucleotide Polymorphism of CDC37, AHSA1 and STIP1 Gene in Three Cattle Breeds using SNaPshot Technology . Indian Journal of Animal Research. 55(4): 378-383. doi: 10.18805/IJAR.B-1266.

ABSTRACT

Background: Heat stress in domestic animals has become a major limit factor for livestock production in tropical and subtropical regions. These traits that adapt to torrid environment are important in livestock breeding.

Methods: In this study, we identified and genotyped six Single nucleotide polymorphism for the CDC37, AHSA1 and STIP1 gene in the Droughtmaster, Angus and Simmental cattle breeds using the SNaPshot Multiplex system. 

Result: Result of pair-wise differences (FST) revealed three SNP locus (CDC37-6 (A16154247/G), CDC37-7 (C16157867/G), AHSA1-10 (G89722567/A) were significantly different in the Droughtmaster population than Angus and Simmental cattle breeds. Moreover, it was found that CDC37-7 (C16157867/G) locus deviated from Hardy-Weinberg equilibrium, suggesting that the CDC37-7 (C16157867/G) genes have been influenced by the selective breeding of the Droughtmaster breed. Therefore, CDC37-7 (C16157867/G) locus could be used as a marker-assisted candidate gene locus of heat tolerance. This study provides valuable information, concerning marker-assisted selection in the breeding of heat stress resistant cattle. 

INTRODUCTION

Southern China is characterized by a humid tropical subtropical monsoon climate and is affected by higher ambient temperature and relative humidity. With global warming and the long duration of high temperatures and high humidity in summer, heat stress has become an important factor that threatens livestock production (Cai et al., 2014). Heat stress refers to systemic indications in which the animal, affected by high temperatures, experiences rises in body temperature and physiological reactions occur in the hypothalamus, pituitary and adrenal cortex systems (Dikmen et al., 2009). When heat stress occurs, the productivity and quality of milk products from dairy cows decline (West et al., 2003; Liu et al., 2017; Chanda et al., 2018), heat stress may also cause disorders with the immune system making the cattle prone to infection by microorganisms or other diseases (Silanikove et al., 2015; Alemu et al., 2018); In addition, heat stress can also lead to low fertilization and decreased reproduction rates in cows (Andrade et al., 2008; Rahman et al., 2018). At the same time, parasitic diseases are widespread in high temperature and high humidity environments, which could potentially bring huge economic losses to certain cattle livestock industries.
 
In recent years, studies on the heat resistance of beef cattle has gained importance. A large number of related genes have been reported, among them, the H8H8 haplotype combination was found to be beneficial to the heat tolerance of Holstein cattle in China by PPAR alpha genotyping (Fang et al., 2014). In the same year, eight kinds of miRNA (miR-19a, miR-19b, miR-27b, miR-30a-5p, miR-181a, miR-181b, miR-345-3p and miR-124) related to heat stress in Holstein cows were identified (Zheng et al., 2014).
 
Secondly, research finding CDC37 protein can interact with Spc1, which is very important for maintaining the stability of Spc1 protein and promoting the stress signal transduction from Wis1 MAPKK to Spc1 SAPK (Shipley et al., 2003). Interestingly, the AHSA1 activator is the molecular chaperone of HSP90 and stimulates the ATPase activity of HSP90 (Shao et al., 2016), which may act as an autonomous chaperone in preventing the aggregation of stress proteins. Clinical studies have shown that increased STIP1 protein expression may be a sign of ovarian cancer (Chao et al., 2013). STIP1 can also be used as a potential biomarker of bile duct cell carcinoma and hepatocellular carcinoma (Padden et al., 2014; Sun et al., 2007).
 
In this study a selectively bred heat-resistant Droughtmaster cattle group was the object of study and the Angus and Simmental cattle were used as a control group. Six SNP loci from CDC37, AHSA1 and STIP1 genes were genotyped using the SNaPshot multiplex system and we then sought to find out whether the genotype frequencies of these loci in the Droughtmaster cattle population are different from those in the other cattle breeds that have not undergone selective breeding to increase heat tolerance. This study seeks to find new heat resistant strains of beef cattle and provides scientific reference and theoretical support for future studies.

MATERIALS AND METHODS

Total of 190 individuals were collected from the three yellow cattle populations (Droughtmaster, Angus cattle and Simmental cattle), 1 mL of venous blood of all individuals were collected and DNA was extracted by genomic DNA extraction kit (Tiangen, Beijing, China).
 
The primers were designed according to the location information of 6 SNP sites in the bovine genome (gcf_000003055.6, bos_taurus_umd_3.1.1), as shown in Table 2.
 

Table 1: Description of detail sampling in current study.


 

Table 2: Primer information of six gene locus in current study.


 
The amplification system included 1μL of the DNA template, 5μL 2×Taq PCR Master Mix, 1μL of PrimerMix and 3μL of dH2O, for a total volume of 10μL. The amplification conditions were 95°C for 5 min, followed by 95°C for 30 sec, 56°C for 30 sec and 72°C for 30 sec, followed by 40 cycles of extension at 72°C. 2μL of EX-SAP enzyme was then added to the 4μL of PCR products prepared in advance and the PCR product was purified using a SAP digestion system (shrimp enzyme purification method). The digestive system components included 0.75μL of dH2O, 0.5μL of SAP (1U/μL), 0.15μL of ExoI (5U/μL), 0.6μL of 10×SAP buffer and 4μL of the PCR product, for a total volume of 6μL. Finally, the digestive incubation was carried out at 37°C for 40 min; 85°C for 5 min and stored at 4°C.
 
The mixed PCR product template was purified and identified by 1% electrophoresis, then diluted quantitatively according to the concentration. The diluted PCR product was used as a template for the SNaPshot reaction. The SNaPshot reaction system included 0.5μL of SNaPshot Mix, 3μL of Pooled PCR Products, 1μL of Pooled Primer and 0.5μL of dH2O, for a total volume of 5μL. SNaPshot reaction programs were 95°C for 2 min, followed by 40 cycles of 95°C for 10 sec, 52°C for 5 sec and 60°C for 30 sec and then 4°C forever. Finally, the SNaPshot product was purified: 2μL of the digested SNaPshot reaction product was added to 8μL of deionized formamide containing 0.4% LIZ120 and denatured at 95 °C for 5 min. It was then quenched at -20°C and then sequenced on 3730 XL.
 
Genotype frequency and allele gene frequency of six SNP loci (CDC37-6 (A16154247/G), CDC37-7 (C16157867/G), AHSA1-8 (C89716722/T), AHSA1-9 (T89718093/A), AHSA1-10(G89722567/A), STIP1-11 (T43118737/C)) was estimated by Microsoft Excel 2010 software. The pairwise difference of populations (FST) was displayed using Arlequin software 3.5.1.3 (Excoffier et al., 2010). Hardy-Weinberg equilibrium (HWE) was estimated using GENEPOP 3.4 by Raymond et al., (1995).

RESULTS AND DISCUSSION

The genotyping results of the three yellow cattle populations in this study are shown in Table 4 and Appendix. The classification results are clear, which ensures the reliability of the follow-up research results. For example, the Angus and Simmental contained two genotypes AA and GA and the GG genotypes were only found in the Droughtmaster atthe locus of CDC37-6 (A16154247/G). Similarly, there were two genotypes CC and GC on Angus and Simmental at locus CDC37-7 (C16157867/G) and GG were found in Droughtmaster. In addition, the Angus and Simmental breeds had only one genotype TT at AHSA1-9 (T89718093/A) and STIP1-11(T43118737/C) and Droughtmaster had three genotypes. Although the Angus and Simmental breeds also contain three genotypes at the AHSA1-8 (C89716722/T) and AHSA1-10 (G89722567/A) loci, they have a low frequency of genotypes TT and AA and have no significant differences. On the whole, the Droughtmaster breed has three genotypes at these loci. For the Hardy-Weinberg equilibrium (Table 4), it was found that the Droughtmaster deviated from the Hardy-Weinberg equilibrium at the CDC37-7 (C16157867/G) and STIP1-11 (T43118737/C) and Simmental is also the same at the AHSA1-8 (C89716722/T) locus. A total of three loci in the 3 populations deviated from the Hardy-Weinberg equilibrium, including two sites in Droughtmaster (CDC37-7(C16157867/G), STIP1-11 (T43118737/C)) and one site in Simmental ((AHSA1-8 (C89716722/T)). For a single locus, there is one population deviation from Hardy-Weinberg equilibrium at the CDC37-7 (C16157867/G), STIP1-11 (T43118737/C) and AHSA1-8 (C89716722/T). Aside from these, no populations deviate at other loci.
 

Table 3: Description of detail SNP loci of CDC37, AHSA1 and STIP1 genes in droughtmaster in current study.


 

Table 4: Population genetic analysis of six gene locus in different cattle breeds.


 
FST is an inter-group genetic differentiation index that can be used to judge the genetic differentiation between populations. The FST values of the three cattle populations and each point were calculated based on the genomic markers (Table 1 and Table 5). The FST values ranged from 0 to 0.5 between populations and the range of FST was larger. The FST was 0.10986 between the Angus and Droughtmaster breeds and the FST was 0.10073 between Angus and Simmental, indicating moderate genetic differentiation between populations. The FST was 0.31454 between the Droughtmaster and Simmental breeds, indicating a high degree of genetic differentiation between populations, with the largest genetic distance being between the Droughtmaster and Simmental breeds. For the FST value of a single locus, it was found that the Droughtmaster, Angus and Simmental breeds showed significant differences in the genotype frequencies of all the tested sites (P<0.05), except in the STIP1-11 (T-43118737/C) locus, where the difference between the Droughtmaster cattle and the Angus cattle was not significant (P>0.05).
 

Table 5: The differentiation coefficient (FST) for each bit point.


 
The Droughtmaster cattle breed was selectively bred in the north Queensland of Australia in the early 20th century through the cross-breeding Brahman cattle and short-horned cattle. This combined the ability of Brahman cattle to adapt to tropical climates with the high meat yield of short horn cattle, creating a new breed that did well in the heat but still produced a fair amount of meat. The Droughtmaster cattle breed was first introduced into Chongqing, China in the late 1970s. Judging from the production results in recent years, the Droughtmaster has not only kept its original features of fast growth, high meat yield, strong fertility and ability to eat crude feed, but can also adapt to the high temperatures in Chongqing due to its high tolerance of heat and resistance to heat stress. However, for the Angus and Simmental breeds originating in Europe, who were not selectively bred for heat stress resistance, they are highly prone to heat stress in high temperatures and experience irreversible damage to their bodies in such conditions (Hammond et al., 1996; Wang et al., 2018).
 
At present, there are many ways to alleviate heat stress, such as lowering the ambient temperature (Guo et al., 2007) and improving the ratio of feed (Aréchiga et al., 1998; Huber et al., 1994; Brijesh et al., 2018), However, the most effective method is to find genes or genetic marker sites associated with heat tolerance and to breed individuals with genetic resistance to heat stress through molecular breeding techniques (West et al., 2003; Hansen et al., 2001).
 
In this study, six SNPs from three heat-tolerant candidate genes (CDC37, AHSA1 and STIP1) were genotyped and genotypic frequencies were statistically analyzed. The Droughtmaster breed has a unique genotype GG compared to the Angus and Simmental breeds in CDC37. It is well known that heat stress proteins (Hsp90) play an important role in reducing thermal damage and enhancing heat resistance (Bharati et al., 2017; Lalrengpuii et al., 2016). However, it has been reported that CDC37 can be involved in the regulation of protein kinases as a molecular chaperone of Hsp90 (Scholz et al., 2000; Calderwood et al., 2015). In addition, Ota et al., (2011) also found that Cdc37 / Hsp90 protein mediates the stress response of the endoplasmic reticulum of ins-1 cells and helps regulate the activity of IRE1 protein in insulin synthesis under physiological stimulation (Ota et al., 2011). Meanwhile, insulin can directly modulate hypothalamic neurons that regulate thermogenesis and CBT and this indicates that insulin plays an important role in coupling metabolism and thermoregulation at the level of the anterior hypothalamus (Sanchez-Alavez et al., 2010).
 
Secondly, the latest study found that CHU_1110 may be involved in the stress response of bacteria to heavy metal ions, while CHU_1110 contains three α-helices and an anti-parallel β-sheet, forming a large cavity in the protein center, which is consistent with the structural features of the AHSA1 protein family, so the researchers speculated that AHSA1 and CHU_1110 have the same function during the stress response process (Liang et al., 2018). This study found that two of the three SNPs of the AHSA1 gene (AHSA1-8 (C89716722/T), AHSA1-10 (G89722567/A)) have no species-specific genotypes, but the genotypes frequency of the two SNPs was significantly different (P<0.05) in the Droughtmaster compared to the Angus and Simmental populations, implying that the gene frequency of the locus was altered due to artificial selection. From the STIP11 (T43118737/C) locus genotype frequency of STIP1 gene, it was found that there were 2 unique genotypes CC and CT in the Droughtmaster, while the other population only carried TT type. Almost all studies on the STIP1 gene have focused on cancer and found that STIP1 promotes the growth and migration of cancer cells (Luo et al., 2018; Chen et al., 2017). Therefore, although there have been no reports on the direct relationship between the STIP1 gene and heat stress in related studies, from the difference in genotype frequency of this locus in the cattle population in this study, it can be inferred that this locus may be having an important role concerning the heat-tolerant potential of the Droughtmaster breed.

​CONCLUSION

In this study, 6 SNP loci from CDC37, AHSA1 and STIP1 genes were studied and found that CDC37-7(C16157867/G) SNP loci were significantly different in the Droughtmaster breed compared with other two breeds, suggesting that the high frequency or unique genotype of CDC37-7(C16157867/G) in Droughtmaster was a heat resistant marker. The results of this study provide data for the development of the marker-assisted breeding of new heat-resistant beef cattle breeds and scientific reference for future studies.

ACKNOWLEDGEMENT

This work was supported by the Characteristic Germplasm Resources Population Selection and Innovation on Mutton Sheep and Goats (No. 2015BAD03B05), Special Key Research and Development Projects of Scientific and Technological Innovation for Social Undertakings and People’s Livelihood Guarantee in Chongqing (No.cstc2017 shms-zdyfx0059), National Natural Science Foundation of China (No.31172195), People’s Livelihood Special Innovation Projects of CQ CSTC (No. cstc2016shmszx 80064) and the Innovation Team Building Program in Chongqing universities (CXTDG201602004), Fundamental Research Funds for the Central Universities (XDJK2017 A003).

CONFLICTS OF INTEREST

The authors declare no conflicts of interest.

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