SINGLE NUCLEOTIDE POLYMORPHISM DATA COMPARISON FOR GENETIC DIVERSITY AND GROUP STRUCTURE OF KOREAN NATIVE BLACK GOATS AND CROSSBRED GOATS

K. W. Kim¹, J. Lee¹, E. D. Lee¹, S. Kim¹, S. S. Lee¹, H. T. Lim^2,3 andS. H. Lee¹*

¹Animal Genetic Resources Research Center, National Institute of Animal Science, Rural Development Administration, Hamyang 50000, Korea

²Department of Animal Science, Gyeongsang National University, Jinju 52828, Korea

³Institute of Agriculture and Life Science, Gyeongsang National University, Jinju 52828, Korea

* Corresponding author’s email: sanghoon@korea.kr

ABSTRACT

We used single nucleotide polymorphism (SNP) data to investigate the genetic structure, diversity, and relationship between native and foreign cross bred goats. The Korean native black goat (KNBG) has four different strains; however, this differentiation is based solely on external factors. To differentiate KNBGs from foreign crossbred goats (CGs), we used the Illumina Goat SNP50K BeadChip to perform genome analysis. We found an SNP marker that could distinguish between breeds and strains of KNBGs, as well as between KNBGs and CGs. We extracted genetic data from 506 goats and identified 45,836 common SNPs. To identify the distinguishing SNPs, we calculated the allele frequency difference for each breed, and analyzed the absolute value of the frequency difference between randomly selected breeds using the top 10, 20, 30, 50, and 150 SNPs. The data were used to represent the genetic structure of KNBGs and CGs goats, and principal component analysis revealed a distinguishing marker between them. As the SNP value increased, the markers became more distinct. Our findings can provide insights into the genetic information about the KNBGs strains, and SNP data will serve as the basis for future genetic selection.

https://doi.org/10.36899/JAPS.2022.6.0560
Published first online June 11, 2022

INTRODUCTION

Archaeological evidence shows that goats (Capra hircus) were among the first animals to be domesticated. Domestic goats are widely distributed worldwide (Porter, 1996; Zeder and Hesse, 2000; MacHugh and Bradley, 2001), and are therefore exposed to different production characteristics and climates in different regions. The goats in each region have adapted to these different conditions, which has resulted in diverse and important genetic mutations (Shrestha and Fahmy, 2005).

Domestic animal genetic resources contain information on different species of animals, including goats, and their genetics. They have been increasingly valued as the basis of the bioindustry (Choi et al., 2012), and their importance continues to rise (Suh et al., 2012). Since the Convention on Biological Diversity in 1992, these genetic resources are considered a country’s inherent property.

Single nucleotide polymorphism (SNP) analysis can be safely used for comprehensive genome research. It is therefore an appropriate tool for investigating relationships and genetic mutations in domestic animals (Lin et al. 2013; Lashmar et al. 2016; Brito et al. 2017; Onzima et al. 2018). The SNP technique is important in the classification of genetic and intra-population variations (Kijas et al. 2012; Grasso et al. 2014).

Recently, the use of SNP chip analysis in goats has facilitated active research on the origin and genetic marker of native goats. Seven breeds of Spanish goats (Malaguena, Murciano-Granadina, Florida, Palmera, Mallorquina, Bermeya, and Blanca de Rasquera) have been analyzed using the Illumina Goat SNP50K BeadChip and were showed to derivefrom crossbreeds of goats from Europe (Saanen and Carpathina) and Africa (Tunisian, Djallonke, and Sahel) (Manunza et al., 2016).

In the Netherlands, a medium scale SNP chip was used to determine the genetic characteristics and origin of six breeds of goat (Boer, Karamojong, Kigezi, Mubende, Small East African, and Sebei). The results revealed that all six breeds had one common ancestor, with some geographical differentiation (Onzima et al., 2017). Historical evidence suggests that goat breeding started in South Korea approximately 2,000 years ago, and native goats might have originated in China or Mongolia (Kang, 1967; Kim et al., 2011). South Korea’s native black goat (KNBG) is registered in the Domestic Animal Diversity Information System as a unique breed with four distinct strains (Dangjin, Jangsu, Tongyeong, and Gyeongsang National University), which are differentiated by external characteristics. Research needs to be conducted to develop a more precise differentiation marker for these strains.

The aim of this study was to identify a clear differentiation marker between KNBGs and foreign crossbred goats (CGs) using the Illumina Goat SNP50K BeadChip and conducted a genome analysis. The extracted SNP marker can then be used to further differentiate between strains of native goat in South Korea.

MATERIALS AND METHODS

Experimental Animals: This study followed the animal protection laws of the Animal Care and Use Protocols of the Rural Development Administration of the National Institute of Animal Science and was approved by the Ethical Committee on Animal Experimentation (Approval Number: 2019-320).

SNP Chip Data: This study analyzed 354 KNBGs (Dangjin, Jangsu, Tongyeong, and Gyeongsang National University) from the Rural Development Administration of the National Institute of Animal Science, and 152 CGs that were bred in farmhouses (Table 1). We used the Illumina Goat SNP50K BeadChip (Illumina, Inc., San Diego, CA, USA) to determine the genetic information of all 506 goats.

Table 1. Description of the goat populations used in this study

Quality Control: The quality of data for approximately 50,000 SNPs collected from the Illumina Goat SNP50K BeadChip was assessed using PLINK software version 1.90 (Purcell et al., 2007). To increase the accuracy of the genetic information, the quality control process removed subjects with an SNP call rate less than 95%. If the minor allele frequency (MAF) was lower than 1% and the Hardy–Weinberg equilibrium (HWE) p-value was lower than 10^-6 in these subjects, the SNP data were removed from the study.

Table 2. Quality control removal criteria used in this study

SNP Selection: After the SNP quality control, 45,836 complementary SNPs were available. From these we were able to select SNPs that could be used to differentiate the native breed from the foreign breed. We calculated the allele frequencies of these complementary SNPs, as well as the differences in frequency value and absolute values between breeds. Among the allele frequency differences, we selected the top 150 SNPs, and the top 10, 20, 30, 50, 100, and 150 SNPs were investigated separately.

Difference in Genetic Structure and Principle Component Analysis (PCA): We used STRUCTURE software (Alexander et al., 2009) to determine the differences in genetic structure and to estimate the actual distribution between breeds. Furthermore, to investigate the genetic relationship through clustering of the two breeds, we used PLINK version 1.90 to perform PCA.

RESULTS AND DISCUSSION

Quality Control Results: From the 50,618 SNPs from the Illumina Goat SNP50K BeadChip, 4,648 SNPs were removed. Therefore 45,836 common SNPs were used in this experiment (Table 3).

Table 3. Number of SNPs removed for quality control and common SNPs between Korean native goat and crossbred goat in Illumina Goat SNP50K BeadChip

SNP Selection (Top 10 Allele Frequency Difference Sample Illustration): To analyze the difference between the KNBGs and CGs breeds, we used the 150 SNPs with the highest frequency difference. These frequency differences ranged from 0.551 to 0.687 (average 0.587). Table 4 shows the SNP information for the top 10 allele frequency differences.

Table 4. SNP data for the top 10 allele frequency differences between Korean native goats and foreign crossbred goatsusing the selected common SNP

Genetic Structure and PCA: Figure 1 shows the STRUCTURE software results for the genetic structural differences between KNBGs and CGs. When the SNP data of the top 10 allele frequency difference were used, a genetic structural difference was detected between the KNBGs and CGs breeds, and more significant variations were observed within the top 20 allele frequency differences. This can be explained by the inclusion of foreign genetic information during the initial stages of breed composition. Additional research, such as using pedigrees to investigate kinship, is required to determine the genetic structure between these breeds. The PCA revealed a genetic correlation using clustering in PLINK 1.90 (Figure 2). When SNP data of the top 10 allele frequency difference were used, markers between the KNBGs and CGs breeds were differed, which was consistent with the results showing genetic structure. Furthermore, this result corroborated the findings of Suh et al. (2014) and Park et al. (2019), who demonstrated a structural genetic difference between KNBGs and CGs (Saanen, Toggenburg, and Boer) using a microsatellite marker. Additionally, this result was consistent with the findings of Berihulay et al. (2019), who showed that genetic structural differences could be determined using SNP data from six breeds of Chinese goats. When SNP data of the top 20 allele frequency difference were used, a more distinct variation was observed between these KNBGs and CGs breeds. The three-dimensional (3D) PCA results for more specific breed differentiation are shown in Figure 3. The 3D PCA provided a clearer distinction between the data points with noise than the 2D PCA did.

Conclusions: This study used data obtained from a commercialized SNP panel (Illumina Goat SNP50K BeadChip) to identify genetic differences between KNBGs and CGs using genetic structural analysis and PCA. With the further use of more SNP data, breed differentiation became more apparent. However, additional research is required to determine whether foreign breeds can be differentiated from each other. In conclusion, the findings of this study can be used for the preservation and differentiation of KNBGs, and our SNP data can be used for genomic selection and to enhance our understanding of KNBGs.

Acknowledgments: This work was supported by the Cooperative Research Program for Agriculture Science and Technology Development (grant number PJ01431501) and the Fellowship Program of the National Institute of Animal Science, Rural Development Administration, Republic of Korea.

Conflict of interest: The authors declare no conflicts of interest.

Author contributions: Kwan-Woo Kim, Jinwook Lee, Sung-Soo Lee, and Sang-Hoon Lee planned the experiments and interpreted the results. Kwan-Woo Kim and Sang-Hoon Lee wrote the manuscript, statistically analyzed the data, and created illustrations.

REFERENCES

1. Berihulay, H., Y. Li, X. Liu, G. Gebreselassie, R. Islam, W. Liu, L. Jiang and Y. Ma (2019). Genetic diversity and population structure in multiple Chinese goat populations using a SNP panel. Anim. Genet. 50: 242–249.
2. Brito, L. F., J. W. Kijas, R. V. Ventura, M. Sargolzaei,L. R. Porto-Neto, A. Cánovas, Z. Feng and F. S. Jafarikia Mand Schenkel (2017). Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers. BMC Genomics. 18: 229.
3. Choi, S. B., M. J. Byun, Y. S. Kim, M. J. Kim, Y. H. Choy, D. H. Kim, E. G. Jeong, K. S. Kang, K. H. Kim and J. H.Kim (2012). National management System for conservation of livestock genetic resources: an overview. Ann. Anim. Resour. Sci. 23: 142–148.
4. Grasso, A. N., V. Goldberg, E. A. Navajas, W. Iriarte, D. Gimeno, I. Aguilar, J. F. Medrano, G. Rincon and G. Ciappesoni (2014). Genomic variation and population structure detected by single nucleotide polymorphism arrays in Corriedale, Merino and Creole sheep. Genet. Mol. Biol. 37: 389–
5. Kang, M. H. (1967). Studies on the origin of Korean native goat. Korean J. Anim. Sci. 9: 5–
6. Kijas, J. W., J. A. Lenstra, B. Hayes, S. Boitard, L. R. P. Neto, M. San Cristobal, B. Servin, R. Mcculloch, V. Whan, and K. Gietzen (2012). Genome-wide analysis of the world’s sheep breeds reveals high levels of historic mixture and strong recent selection. PLoS Biol. 10: e1001258.
7. Kim, J. H., C. Y. Cho, S. B. Choi, Y. M. Cho, S. H. Yeon and B. S. Yang (2011). mtDNA diversity and phylogenetic analysis of Korean native goats. J. Life Sci. 21: 1329–
8. Lashmar, S. F., C. Visser and E. V. Marle-Köster (2016). SNP-based genetic diversity of South African commercial dairy and fiber goat breeds. Small Rumin. Res. 136: 65–71.
9. Lin, B. Z., T. Kato, M. Kaneda, H. Matsumoto, S. Sasazaki and H. Mannen (2013). Genetic diversity and structure in Asian native goat analyzed by newly developed SNP markers. Animal Sci. J. 84: 579–
10. MacHugh, D. E., and D. G. Bradley (2001). Livestock genetic origins: goats buck the trend. Proc. Natl. Acad. Sci. USA 98(10): 5382–5384.
11. Manunza, A., A. Noce, J. M. Serradilla, F. Goyache, A. Martínez, J. Capote, J. V. Delgado, J. Jordana, E. Muñoz, A. Molina and V. Landi (2016). A genome-wide perspective about the diversity and demographic history of seven Spanish goat breeds. Genet. Sel. Evol, 48: 52.
12. Onzima, R. B., R. Mukiibi, A. Ampaire, K. K. Benda, and E. Kanis (2017). Between-breed variations in resistance/resilience to gastrointestinal nematodes among indigenous goat breeds in Uganda. Trop. Anim. Health Prod. 49: 1763–1769.
13. Onzima, R. B., M. R. Upadhyay, R. Mukiibi, E. Kanis, M. A. M Groenen and R. P. M. A. Crooijmans (2018). Genome-wide population structure and admixture analysis reveals weak differentiation among Ugandan goat breeds. Anim. Genet. 49: 59–
14. Park, B. K., Y. S. Kim, J. Seong and H. S. Kong (2019). Analysis of genetic diversity and relationships of Korean native black goat using microsatellite markers. J. Anim. Reprod. Biotechnol. 34: 183–189.
15. Porter, V., (1996). Goats of the world. Farming Press, Ipswich, UK.
16. Purcell, S., B. Neale, K. Todd-Brown, L. Thomas, M. A. Ferreira, D. Bender, J. Maller, P. Sklar, P. I. de Bakker, M. J. Daly and P. C. Sham (2007). PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81 (3): 559–575.
17. Shrestha, J. N. B. and M. H. Fahmy (2005). Breeding goats for meat production: A review. 1. Genetics resources, management and breed evaluation. Small Rumin. Res. 58: 93–
18. Suh, S., C. Y. Cho, M. J. Byun, S. B. Choi, Y. S. Kim, M. J. Kim, Y. G. Ko, D. H. Kim, H. T. Lim and J. H. Kim (2014). Establishment of a microsatellite marker set for individual identification in goat. JALS. 48: 157–
19. Suh, S. W., M. J. Byun, Y. S. Kim, M. J. Kim, S. B. Choi, Y. J. Ko, D. H. Kim, H. T. Lim and J. H. Kim (2012). Analysis of genetic diversity and relationships of Korean Native Goat populations by microsatellite markers. J. Life Sci. 22(11): 1493–1499.
20. Zeder, M. A., and B. Hesse (2000). The initial domestication of goats (Capra hircus) in the Zagros Mountain 10,000 years ago. Science 287(5461): 2254–2257.