Genetic diversity and population structure of Mongolian regional horses with 14 microsatellite markers

Objective This study aimed to identify the genetic diversity and population structure of Mongolian horse populations according to the province of residence (Khentii, KTP; Uvs, USP; Omnogovi and Dundgovi, GOP; Khovsgol, KGP) using 14 microsatellite (MS) markers. Methods A total of 269 whole blood samples were obtained from the four populations (KTP, USP, GOP, KGP) geographically distinct provinces. Multiplex polymerase chain reaction (PCR) was conducted using 14 MS markers (AHT4, ASB2, ASB17, ASB23, CA425, HMS1, HMS2, HMS3, HMS6, HMS7, HTG4, HTG6, HTG7, and VHL20), as recommended by the International Society for Animal Genetics. Capillary electrophoresis was conducted using the amplified PCR products, alleles were determined. Alleles were used for statistical analysis of genetic variability, Nei’s DA genetic distance, principal coordinate analysis (PCoA), factorial corresponding analysis (FCA), and population structure. Results On average, the number of alleles, expected heterozygosity (HExp), observed heterozygosity (HObs), and polymorphic information content among all populations were 11.43, 0.772, 0.757, and 0.737, respectively. In the PCoA and FCA, GOP, and KGP were genetically distinct from other populations, and the KTP and USP showed a close relationship. The two clusters identified using Nei’s DA genetic distance analysis and population structure highlighted the presence of structurally clear genetic separation. Conclusion Overall, the results of this study suggest that genetic diversity between KTP and USP was low, and that between GOP and KGP was high. It is thought that these results will help in the effective preservation and improvement of Mongolian horses through genetic diversity analysis and phylogenetic relationships.


INTRODUCTION
Horses (Equus caballus) have been domesticated in steppes and have played an important role in the development of several civilizations. In Mongolia, horses are one of the five livestock species, and according to [1], as of 2020, of the approximately 67.07 million live stock in Mongolia, 4.09 million are horses. The Mongolian horse is one of the most ancient breeds in the world and has adapted to Mongolia' s climate and environment. The Mongolians were able to move easily using horses to find better grasslands, increase the number of livestock, and expand foreign relations. Therefore, Mongolian horses occupy an important place in Mongolia's nomadic lives.
The ancient wild Mongolian horse is known as Przewalskii [2,3]. Though the ancient Mongolian horse may have been the ancestor of several modern horse breeds, the pro tection and management of Mongolian horse's genetic resources is still insufficient. As the importance of livestock genetic resources increases worldwide, various studies are being conducted on the molecular genetic properties of genetic resources in order to preserve their value. Studies on genetic diversity are essential for the management of genetic resources through genetic characteristic analysis, breeding, and discovery of useful traits.
Microsatellites (MS) are used as molecular markers for genetic diversity analysis and breeding programs [4,5]. These molecular markers can be used to obtain information on the phylogenetic relationships or genetic variation. Microsatellite markers were first characterized in horses by Ellegren et al [6], Marklund et al [7]. These have since been used extensively to investigate the genetic diversity and breed characteristics of horse populations. As some horse breeds were domesti cated in the steppes of Mongolia, it was predicted that there would be a high genetic diversity [8]. However, genetic analysis using MS markers is yet to be conducted among Mongolian horses. To study livestock genetic resources in Mongolia, it is necessary to analyze the genetic diversity and genetic rela tionship between Mongolian horse populations using an efficient MS marker.
In Mongolia, various breeds of horses inhabit the climate and topographical characteristics of each province. Accord ing to Wright [9] and Ganbold et al [10], Mongolian horses mainly inhabit steppes and dry areas such as Gobi. The ap pearance of Mongolian horses varies greatly depending on their habitat. Genetic characteristics also appear to be different. Khentii Province is a grassland region located in the eastern part of Mongolia, where various plants grow naturally. The Uvs province is located in the west of Mongolia, and the Omnogovi and Dundgovi provinces comprise the steppes in southern Mongolia. The Khovsgol province is a pasture located in northern Mongolia and has a cold climate.
As such, Mongolian horses have different traits depend ing on the province where they live, but the genetic diversity and correlations using MS markers have not yet been verified.
Therefore, this study aimed to identify the genetic charac teristics of Mongolian horses according to the province of residence using 14 MS markers published by the Interna tional Society of Animal Genetics (ISAG). We analyzed the genetic relationships and genetic diversity of horses raised in each of the five provinces (Khentii, Uvs, Omnogovi, Dundgovi, and Khovsgol) in Mongolia, which were divided into four populations. Genetic diversity analysis is expected to help in the effective protection and management of Mongolian horse genetic resources. In addition, the genetic structure and phylogenetic relationships of the Mongolian horse populations were also identified, and can be used as basic data for research on genetic resources of not only horses but also other livestock in Mongolia.

Genomic DNA extraction
The experimental methods were approved by the Hankyong National University Animal Ethics Committee, Anseong, Republic of Korea (No.20211). A total of 269 whole blood samples were obtained from the four populations of the five geographically distinct provinces (Table 1, Figure 1). Sampling sites included i) East Mongolia Khentii Province (KTP, n = 53); ii) West Mongolia Uvs Province (USP, n = 43);  iii) Southern Mongolia Omnogovi and Dundgovi provinces (GOP, n = 133); and iv) Northern Mongolia Khovsgol province (KGP, n = 40). Genomic DNA was extracted from blood samples using the methods described for QuickGene 810 (Kurabo, Osaka, Japan). The concentration and purity of the extracted genomic DNA were evaluated using an ND1000 UVVis spectrophotometer (NanoDrop Tech nologies, Wilmington, DE, USA).

Composition of multiplex-polymerase chain reaction and the polymerase chain reaction procedure
Multiplex polymerase chain reaction (PCR) was conducted using the Equine Genotypes Panel 1.1 Kit (Thermo Fisher Scientific, Waltham, MA, USA) for genotyping of the 14 MS markers. Following the manufacturer's instructions, the re action mixture was prepared using 2 μL genomic DNA (1.0 ng/μL), 9 μL master mix, and 9 μL primer mix, obtaining a total volume of 20 μL. The PCR was conducted using a GeneAmp PCR system 9700 (Applied Biosystems, Waltham, MA, USA). The PCR amplification was conducted using the following conditions: predenaturation at 98°C for 3 min followed by 30 cycles of 15 s at 98°C, 75 s at 60°C, and 1 cycle of 30 s at 72°C. The final extension step was performed at 72°C for 5 min and the mixture was cooled to 4°C.

Genotyping of microsatellite
Using HiDi formamide, amplified PCR products were di luted 50 to 100 times, and the diluted PCR products (1 μL) were further diluted using a mixture of 9 μL HiDi formamide and GeneScan 500LIZ size standard (Applied Biosystems, USA). After denaturation at 95°C for 3 min, capillary elec trophoresis was conducted using an ABI 3730xl Genetic Analyzer (Applied Biosystems, USA). The size of each MS marker was determined using GeneMapper ver 5.0 (Applied Biosystems, USA). The determined alleles were collated using Microsoft Excel (Microsoft, Redmond, WA, USA) and used for statistical analysis.

Statistical analysis of data
The MS Toolkit software [11] was used to calculate the number of alleles, expected and observed heterozygosity (H Exp and H Obs , respectively), and polymorphism informa tion content (PIC) values. To identify genetic correlations between populations, allele frequencies for each marker were confirmed using GenAlEx 6.4 [12] and Genetix software [13]. For this, principal coordinate analysis (PCoA) was conducted using GenAlEx 6.4 to display the twodimen sional coordinates. Factorial component analysis (FCA) was conducted using Genetix to display the threedimensional coordinates. The genetic distance between populations was calculated based on allele frequencies according to Nei's DA genetic distance [14] using POPTREE2 [15]. A phylogenetic tree was estimated from the genetic distances using the neigh borjoining method [16] with the DISPAN program [17]. Population structure [18,19] was used to estimate the uni formity of the population, and the K value was set to estimate the number of distinct populations (ΔK). To calculate the average estimate and standard deviation of each K value, the length of the burnin period and the number of Markov chain Monte Carlo (MCMC) repetitions after the burnin frequency were set, and the optimal K value and genetic uniformity for each cluster were calculated The results were applied to the Structure harvester [20] using the Evanno method [21].

Microsatellite polymorphism
The

Genetic distance and phylogenetic analysis
The genetic divergences among the four Mongolian horse populations based on allele frequencies were calculated ac cording to Nei's DA genetic distance [16]. The phylogenetic relationships among these Mongolian horse populations were determined using the neighborjoining tree ( Figure 2). Grouping values were determined by 1,000 repetitive "boot strap" tests to determine the reliability of the neighborjoining tree and were specified at the branching points of the tree. The smaller the estimated genetic distance is, the closer each population is genetically. In Nei's DA genetic distance, the KTP and USP populations were the closest (DA = 0.0535), and the largest difference was calculated for the GOP and KGP populations (DA = 0.1797) (Supplementary Table S1).
In the phylogenetic tree, the Mongolian horse populations was mainly divided into two clusters. The KTP and GOP populations formed the first cluster, and the KGP popula tion formed the second cluster. The USP breed was located between the two clusters. The division of the populations into two distinct clusters highlighted the presence of clear genetic separation between each province.

Principal coordinates analysis and factorial component analysis
As the phylogenetic tree may not take into account the effects of admixture among the four populations, we conducted PCoA and FCA, using allele frequencies of the 14 MS markers, as an alternative approach to understand the genetic relation ships among populations. The PCoA contributed to 100% of the variation, including the third ingredient. The first three principal coordinates represented 60.13%, 29.75%, and 10.12% of the total variation, respectively. The KGP and GOP popu lations were distinct from the other populations ( Figure 3). In contrast, the KTP and USP populations were located be tween the closest genetic distances. The FCA analysis revealed that the three dimensions contributed to a total of 100 with Axis 1 (56.08), Axis 2 (29.86), and Axis 3 (14.06). The KTP and GOP populations were genetically differentiated from other populations and showed a close relationship among certain populations, including KTP and USP ( Figure 4). Thus, results of the PCoA analysis were consistent with those of the FCA.

Uniformity of horse population
A Bayesian clustering method and population structure were used for clustering algorithms of multi-locus genotypes to identify the population structure and pattern of admixture within the populations. Population structure was used to es timate the number of groups that were classified by the group surveyed. The Bayes analysis set K values from 2 to 4 and examined the formation of colonies by group ( Figure 5). The bar plot in Figure 5 confirms that the KGP and GOP popu lations showed different clusters from the other two Mongolian horse populations in all cases from the set K values. The re maining two populations showed similar patterns. The KGP and GOP populations were separated into different clusters when K3 and the KTP and USP populations were represent ed as a mixture with among. When the K value reached 4, the KGP and GOP populations were still separated into dif  ferent clusters, but the KTP and USP populations primarily clustered with each other. Burnin and MCMC repetitions (200,000 times and 1,000,000 times each, respectively) were used to estimate the optimal number of groups (ΔK values) when classifying groups between 2 and 4, which were re peated 10 times by setting the K values from 2 to 4, and the ΔK value was estimated using a structure harvester. The high est ΔK value (1.375%) was obtained from K value 3, which uses allele frequency data calculated with the 14 MS markers and distinguishes the three groups when the group is divided (Supplementary Table S2). This indicates that it is the most appropriate method.

DISCUSSION
The purpose of this study was to verify the genetic diversity and correlation of Mongolian horses raised in five provinces using 14 MS markers. MS markers have been used to study the genetic diversity and population structure of horse breeds [23] and are commonly used in many countries for individual identification and parentage testing of horses. The results of genetic variability, Nei's DA genetic dis tance, PCoA, FCA, and population structure provided genetic evidence for the differentiation of the population, and polymorphism was observed in all provinces. A total  Our estimate of genetic diversity (H Exp = 0.772, H Obs = 0.757, and PIC = 0.737) in the Mongolian horse populations was found to be similar to that reported by Cho [24] (H Exp = 0.773, H Obs = 0.696, and PIC = 0.742). Tozaki et al [25] found that the average heterozygosity within each population of Mon golian horses was between 0.75 and 0.77. A higher value than our study was observed by Cho [26] (H Exp = 0.809, H Obs = 0.833, and PIC = 0.761) and Dorji et al [27] (H Exp = 0.78, H Obs = 0.79, and PIC = 0.77). Lower values were reported by Giacomoni et al [23] (H Exp = 0.74, H Obs = 0.628, and PIC = 0.706). The average number of alleles in our study was 11.43 in the 14 MS loci. This is higher than that reported by Cho [26], in which the MNA of the Mongolian horse populations using 11 MS loci was 8.18 alleles per locus. These MNA values were higher than the data published for other horse breeds and are similar to the study of Zuccaro et al [28], who ob Nei' s DA genetic distance analysis highlighted the presence of a clear genetic separation between each province. The KTP and USP populations were the closest (DA = 0.0535), and the largest difference was calculated for the GOP and KGP populations (DA = 0.1797). The same results were ob tained for PCoA, FCA, and the population structure. The KTP and USP populations had the closest genetic distances. This is possibly because they were each intercrossed with each other. In contrast, KGP and GOP populations were ge netically differentiated from other provinces and suggest that both populations do not lose specific alleles unique. The population structure results also confirmed that the KGP and GOP populations were separated into different clusters in all cases.
According to Seo et al [29] and Dierks et al [30], MS markers are highly polymorphic when the sum of H Exp ≥0.6 and PIC≥0.5. Therefore, the results of this study suggest that MS markers, except the HTG4 marker, can be used to aid the conservation, traceability, and improved abilities of the horse populations in Mongolia. Consequently, the Mon golian horses in this study showed a high level of genetic diversity. It is essential to secure genetic resources to ana lyze the genetic diversity of livestock and to identify their genetic relationships. While horses are economically im portant animals in Mongolia, only a few molecular genetic studies have been conducted on the genetic resources of Mongolian horses. Therefore, individual management of Mongolian horses based on genetic differences between them seems to be necessary. Finally, it is expected that this study can be used as basic data for the preservation and improvement of Mongolian horses and the establishment of breeds in the future.