Genetic diversity analysis of Mongolian native cattle and other cattle breeds based on microsatellite marker
Received: August 28, 2019
Accepted: September 13, 2019
Published: September 17, 2019
Microsatellite; Genetic diversity; Phylogenetic tree; Mongolian cattle
In developing countries, genetic resources for livestock greatly contribute to the sustainable development of livelihood, security, and food safety by reducing hunger and poverty (Ben Sassi-Zaidy et al., 2015). Cattle are one of the most economically important livestock in Mongolia as they are main source of major export products such as meat and milk. Out of 1.57 million Mongolian cattle, 1.55 million supposedly belong to three indigenous Bos taurus cattle breeds which are Mongol (M), Selenge (S) and Khalkhun Golun. These breeds herd under broad pastoral systems. Mongolian native breed (MNB) generally is strong and sturdy, but have small body size. By far the M breed is the most common, with 1.53 million animals, and it is found throughout the most parts of the country (Lkhagvaa et al., 2003). According to the 2017 census, Mongolia supported approximately 3.4 million heads of cattle and 6.6% of all livestock.
In 1949, Mongolian indigenous cattle began to improve by crossbreeding with European breeds. Thus, the current breeds are numerous, but they are not known to be genetically distinct. The S breed numbering 19.2 thousand heads, was developed by crossing the Kazakh white headed breed with indigenous Mongolian cattle. The Kazakh white head cattle are a beef cattle breed from Kazakhstan and Russia. The breed was developed by crossing Hereford (H) cattle with Kazakh and Kalmyk cattle (Dankvert et al., 2007; Cherekaev and Cherekaeva, 1973) and was used as a base improver since 1950 to improve meat productivity of Indigenous Mongolian cattle. By 2015, 41.5 thousand Kazakh white head pure (KP) and Kazakh white head cross (KC) breeds were counted in Mongolia. Although the census of cattle breeds was done on yearly basis, there are no information is available on the genetic relationship between the M breeds (National Statistical office., 2001).
Microsatellite (MS) are widely used as genetic markers for genetic diversity analysis and breeding programs in developing countries as they are low cost and relatively simple to use in such analyses (Rege et al., 2011); MS markers using of genetic analysis this has yet to be conducted among Mongolian cattle; therefore, our research would be the first of its kind, especially when considering the use of a crossbreed cattle hybrid since 1949. As cattle herders are concerned about the quantity of livestock rather than the quality, genetic distance analysis is crucial to determine varying genetic distances. Hence, we used MS markers to study the genetic diversity of MNB and Foreign Breeds (FB). These molecular genetic markers can be used to assess genetic diversity as well as track the species origin and identification. In this study, we have determined genetic distance and polymorphisms of MNB and FB. Study on genetic diversity of MNB and FB is expected to provide scientific information for designing breeding strategies.
Materials and Methods
Blood sample and DNA collection
In the present study, whole blood samples were collected from two native Mongolian breeds (S, M) and three foreign breeds (H, KP, KC) from Selenge Aimag, Zuunburen Sum; Dundgovi Aimag, Adaatsag Sum; and Tov Aimag, Onjuul Sum in Mongolia, as shown in Table 1. DNA was extracted from the blood samples using QuickGene 810 following the manufacturer’s instruction method. The extracted genomic DNA was used for experiments after measuring the concentration and purity using the ND-1000 UV-Vis spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) (Figures 1 and 2).
|Population||The number of Sample|
|Selenge breed [S]||38|
|Mongol native breed [M]||40|
|Kazakh white head purebred [KP]||40|
|Kazakh white head crossbreed [KC]||30|
|Hereford breed [H]||40|
Table 1. Description of the 5 cattle breeds in the present study.
Information on the microsatellite marker
In this study, we chose 11 MS markers based on the guidelines of the International Society of Animal Genetics (ISAG) and United Nations Food and Agriculture Organization (FAO) whereas the previously reported (Choy et., al 2015) (Table 2).
|MS Marker||Ch.||Size range||Primer Sequence|
MS, Microsatellite; Ch, Chromosome; R, Reverse; F, Forward.
Table 2. Primers of the 11 microsatellite markers.
Multiplex PCR composition and methods
The total reaction volume of 15 μL containing 1 μL genomic DNA (20–50 ng/μL), 0.2 μL Hot Start Taq DNA Polymerase (Genetbio, Nonsan, Korea), 0.5 μL of each primer (forward and reverse), 1.5 μL dNTPs, and 1.8 μL 10x buffer was used to perform PCR using the GeneAmp PCR system 9700 (Applied Biosystems, Foster City, CA, USA). The PCR amplification was conducted using following conditions: pre-denaturation at 95°C for 10 minutes followed by 30 cycles of 95°C for 30 seconds, 58°C for 30 seconds, and 72°C for 30 seconds. After 30 minutes of extension at 72°C, the reaction was terminated at 4°C.
Microsatellite genotype analysis
The genotyping mixture contained 1 μL PCR product, 8.9 μL Hi-Di formamide (Applied Biosystems, Foster City, CA, USA), and 0.1 μL GeneScan ™ 500LIZ size standard (Applied Biosystems, Foster City, CA, USA). Fragment analysis was performed using the Genetic Analyzer 3730xl (Applied Biosystems, Foster City, CA, USA) by subjecting fragments to capillary electrophoresis, and allele sizes were used to determine each MS marker using GeneMapper version 4.1 (Applied Biosystems, Foster City, CA, USA). The determined alleles were collected via Microsoft Excel (Microsoft, Redmond, WA, USA) and then applied for statistical analysis.
MS Toolkit software (Park SDE et al., 2001) was used to calculate the number of alleles, HExp, HObs, and PIC. The homozygosity (H0) and heterozygosity (Hi) are expressed according to Eq. 1.
Pi is the frequency of each allele in the Microsatellite Marker. In addition, the mean heterozygosity of all MS markers analyzed and the heterozygosity of the ith MS marker H was calculated with Eq. 2.
PIC values of each group were calculated according to Eq. 3. In this equation, PI and PJ represent the probability that the ith and jth allele appear. Principal coordinate analysis (PCoA) and factorial component analysis (FCA) were performed by GenAlEx 6.4 (Peakall et al., 2006) and Genetix (Belkhir et al., 2004) using each marker-specific allele frequency to identify genetic correlations between groups. The Nei’s standart genetic distance (Nei et al., 1983) was calculated and Neighbor - joined trees were estimated using with DISPAN program (Ota, 1993).
In this study, genetic distance was examined among MNB and FB in Mongolian regions using genetic diversity analysis on MS markers. Analyses of the genetic diversity and genetic relationships of 188 cattle were carried out using 11 MS markers.
Polymorphism of microsatellite marker, within and between populations
The evaluated by the number of alleles, HObs, HExp, and PIC for 11 MS markers were calculated and are reported in Table 3. Polymorphisms of MS markers are determined using the following criteria: if the sum of HExp is ≥ 0.6 and PIC is ≥ 0.5, then the marker was determined to be highly polymorphic (Seo et al., 2017).
|Name of breeds||NA||MNA||HExp||HObs||PIC|
|Kazakh white head purebreed||70||6.363||0.726||0.706||0.674|
|Kazakh white head crossbreed||78||7.090||0.758||0.793||0.710|
Table 3. Genetic Diversity analysis in Mongolian native and foreign breeds.
In the present study, the average HExp value of 11 microsatellite markers was found to be 0.745 with values ranging from 0.726 to 0.777. The highest value, 0.777, was found for the HExp of the M breed, while the lowest value of 0.726 corresponded to the KP breed. HObs ranged from 0.706 to 0.793 with an average of 0.753; the highest HObs were found in KC at 0.793, and the lowest was detected at 0.706 in the KP breed. The M and KC breeds showed the most probable heterozygosity, and the KP breed showed the lowest known heterozygosity among each of the five breeds. PIC ranged from 0.674 to 0.736 with an average of 0.697; the value was highest in the M breed at 0.736 and lowest in the KP breed at 0.674. The M breed showed the highest polymorphism among the 5 breeds, and KP exhibited the lowest. The 11 MS loci from the entire population were analysed and 392 alleles consisting of 72 alleles detected in the S breed, 94 alleles in the M breed, 70 alleles in the KP, 78 alleles in the KC, and 78 alleles in the H breed. The number of alleles per locus ranged from 6 (BM1824) to (TGLA112), with a mean of 10.5 in all.
The result genetic distance analysis result showed that the genetic distance between H breed and KP breed was the lowest. In contrast, the distance between the KP and M breed was the highest (Table 3). This suggests that the specific heterozygous genotypes are distributed at a high frequency in this breed and may be attributed to them. Altogether, these results suggest that 11 microsatellite markers are sufficient for use as polymorphic markers in polymorphism analysis of MNB.
Genetic differentiation among populations
The Neighbor - joining tree (NJ tree) showing the genetic distances between populations (Figure 3). Three FB and two MNB cluster into two groups. The H, KP and KC breed in the first group; M and S breed in the second group. KC breed was established by crossing H and KP breeds. The clustering of breeds into 2 groups by Nei’s DA genetic distance analysis highlights the presence of clear genetic separation between breeds. As phylogenetic tree may not take into account the effects of admixture between breeds, we therefore performed PCoA as an alternative approach to understand the genetic relationship among breeds.
Figure 3. Neighbour – Joined tree showing the genetic distances among the five breeds using Nei’s DA genetic distance on the basis of alleles frequencies from the 11 microsatellite loci. The number in the branch indicates the percentage of occurrence in 1000 bootstrap replicates. S- Selenge, M-Mongol, KP – Kazakh white head purebred, KC – Kazakh white head crossbreed and H-Hereford
PCoA was performed including all populations and loci using allele frequencies to summarize relationship between breeds (Figure 4). The first, second, third Principal coordinate (PCo) represented 42.34%, 32.23% and 17.22% of the total variation, respectively. The first three PCo account for 91.09% of the total variation and the incorporation of five PCo explains all the variation (data not shown). The analysis indicated a grouping at the three foreign breeds (H, KP and KC).
The FCA analysis revealed the very clear separation between the MNB and FB (Figure 5). About 85.33% of the variance was accounted for the first to three dimensions of the FCA Axis 1 (38.84% of total variance explained), which separated S and M from the MNB. Axis 2 (29.23%) further separated KP, KC and H from foreign breeds. Axis 3 (17.26%) distinctly separated M and S breed.
In Asia, totally 258 cattle breeds were reported, 11% of these breeds are recognized as being at the risk of extinction (Scherf, 2000). Currently, much attention is focused on the issue of preserving biological diversity in livestock (Zeng et al., 2010). The purpose of this study is to determine the genetic diversity and relationships of five cattle population using 11 MS marker. The results of genetic diversity analysis (Table 3), the NJ tree (Figure 3), PCoA (Figure 4), and FCA (Figure 5) provide genetic evidence for the differentiation of the five breeds, and polymorphism was observed in all regions. The level of variation depicted by the number of alleles at each locus serves as a measure of genetic variability having direct impact on differentiation of breeds within a species (Buchanan et al., 1994). KP breed exhibited a lower degree of genetic diversity (mean number of alleles [MNA] = 6.363, HExp = 0.726, HObs = 0.706, PIC = 0.674) than all other breeds in all measures of genetic diversity whereas a high degree of genetic diversity was observed in M breed (MNA = 8.545, HExp = 0.777, HObs = 0.775, PIC = 0.736). The M breeds are reportedly similar or higher than those of Mongolian, British and Spanish cattle breeds. (HExp = 0.658 to 0.69, HObs = 0.660 to 0.726) (Lkhagvaa et al., 2003; Wiener et al., 2004; Martin-Burriel et al., 2007; Padilla et al., 2009). Heterozygosity was observed for KP breed as quite low compared to other breeds which may be high genetic relationship between foreign breeds. High diversity in M breed may be attributed to breeding among large number of individuals in throughout most of the country.
The PCoA analysis indicated a grouping at the three foreign breeds (H, KP and KC). The MNB formed two groups. MNB were distant from the FB in the scatter diagram of first and third principal coordinates. Both the NJ tree and the PCoA analysis showed that the M breed is highly distinct from the other breeds analysed. The FCA results showed that individuals from H, KP and KC were slightly mixed, suggesting a closer relationship between them. This may be due to the improvement of the Kazakh white head cattle from Hereford cattle in the 1950 (Dankvert et al., 2007; Cherekaev and Cherekaeva, 1973).
The results indicated that MNB show a high level of genetic diversity. In analysis of genetic relationship and clustering, MNB were genetically differentiated from the FB. These analyses were important to preserve the genetic differentiation and purity of other cultivars as well as to utilize the basic data to improve the ability of each cultivar. Genetic diversity information is needed for establishing protection programs, especially for local Mongolian cattle resources, and to provide a suitable method for farmers to develop animal breeding programs.
In conclusion, our results indicated M breed has high genetic diversity and genetically distinct from other breeds. These findings may be used to develop individual traceability systems as well as aid generating strategies for conservation and breeding programs for the Mongolian cattle population. In the present study, we have used MS markers to clarify genetic diversity and relationship between 5 breeds. Despite the fact that the MS markers are high polymorphic, the MS typing technique is becoming limited use. Especially, because of the technical limit, the labor intensive and the cost of the experiment (Choi et al., 2018). In comparison, the single nucleotide polymorphism (SNP) analysis method has many advantages in terms of cost, accuracy of analyzing, time-consuming. Also, array-based full automated analysis system is used to identify allele genotypes (Vignal et al., 2002). The Mitochondrial DNA (mtDNA) has no recombination and lack of rapid nucleotide substitutions, making it suitable for genetic diversity studies and evolutionary studies (Hoque et al., 2013). So for further studies SNP and mtDNA markers are needed to be done.
This work was supported by a grant from the Next-Generation BioGreen 21 Program (Project No. PJ013322012019), Rural Development Administration, Republic of Korea. We are grateful to Dr. O. Baatartsogt and Dr. B. Bat-erdene (School of Animal Science & Biotechnology, Mongolian University of Life sciences) for collecting blood samples from Mongolia.
The study was approved by the Hankyong National University Animal Ethics Committee (No.2019-2)
About the Authors
Department of Biotechnology, Hankyong National University, Anseong, Korea
- [email protected]
- Agung PP, Saputra F, Zein MSA, Wulandari AS, et al. (2019) Genetic diversity of Indonesian cattle breeds based on microsatellite markers. Asian-Australas. J Anim 32: 467-476. https://doi.org/10.5713/ajas.18.0283
- Belkhir KP, Borsa P, Chikhi L, Raufaste N et al. (1996-2004) GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université de Montpellier II, Montpellier (France).
- Ben Sassi-Zaidy Y, Maretto F, Charfi-Cheikhrouha F, Mohamed-Brahmi A, et al. (2015) Contribution of microsatellites markers in the clarification of the origin, genetic risk factors, and implications for conservation of Tunisian native sheep breeds. Genet Mol Res 15: gmr7059. https://doi.org/10.4238/gmr.15017059
- Buchanan FC, Adams LJ, Littlejohn RP, Maddox JF, et al. (1994) Determination of evolutionary relationships among sheep breeds using microsatellites. Genomics 22: 397-403. https://doi.org/10.1006/geno.1994.1401
- Cherekaev AV, and Cherekaeva IA (1973) Beef cattle breeding. Alma-Ata Kainar
- Choi N, Seo D, Manjula P, and Lee JH (2018) Genetic diversity studies using molecular genetic markers. Journal of Animal Breeding and Genomics 2: 021-027. https://doi.org/10.12972/jabng.20180017
- Choy YH, Seo JH, Park BH, Lee SS, et al. (2015) Studies on genetic diversity and phylogenetic relationships of Chikso (Korea Native Brindle Cattle) Using the microsatellite marker. Korean Society of Life Science 25: 624-630. https://doi.org/10.5352/jls.2015.25.6.624
- Dankvert SA, Kholmanov AM, and Osadchaya, OY (2007) Cattle Breeding Worldwide. Moscow
- Hoque MR, Choi NR, Sultana H, Kang BS, et al. (2013) Phylogenetic analysis of a privately-owned Korean native chicken population using mtDNA D-loop variations. Asian-Australas J Anim Sci 26: 157-162. https://doi.org/10.5713/ajas.2012.12459
- Lkhagvaa B, Ochienga JW, Yoonc DH, Hanottea O, et al. (2003) Genetic diversity and differentiation of Mongolian indigenous cattle populations. Book of Extended Synopses, FAO (Food and Agricultural Organization)/IAEA International Symposium on applications of gene-based technologies for improving animal production and health in developing countries. Vienna, Austria, 6-10 October 2003
- Mannen H, Kohno M, Nagata Y, Tsuji S, et al. (2004) Independent mitochondrial origin and historical genetic differentiation in North Eastern Asian cattle. Molecular Phylogenetics and Evolution 32: 539-544. https://doi.org/10.1016/j.ympev.2004.01.010
- Martin-Burriel I, Rodellar C, Lenstra JA, Sanz A, et al. (2007) Genetic diversity and relationships of endangered Spanish cattle breeds. Journal of Heredity 98: 687-691. https://doi.org/10.1093/jhered/esm096
- National Statistical office (2001) Statistical Year book. Ulaanbaatar, Mongolia.
- Nei M, Tajima F, and Tateno Y. (1983) Accuracy of estimated phylogenetic trees from molecular data. Journal of Molecular Evolution 19:153-170. https://doi.org/10.1007/bf02300753
- Ota T (1993) Dispan: Genetic distance and phylogenetic analysis. Pennsylvania State University Park, State college PA, USA.
- Padilla JÁ, Sansinforiano. E, Parejo J. C, Rabasco. A et al. (2009) Inference of admixture in the endangered Blanca Cacereña bovine breed by microsatellite analyses. Livestock science 122: 314-322. https://doi.org/10.1016/j.livsci.2008.09.016
- Park SDE (2001) Trypanotolerance in West African cattle and the population genetic effects of selection. Ph.D. thesis, University of Dublin, Dublin, Ireland.
- Peakall R and Smouse PE (2006) GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288-295. https://doi.org/10.1111/j.1471-8286.2005.01155.x
- Rege JEO, Marshall K, Notenbaertb A, Ojango JMK (2011) Pro-poor animal improvement and breeding—What can science do? Livestock science. 136: 15-28. https://doi.org/10.1016/j.livsci.2010.09.003
- Scherf BD (2000). World Watch List for Domestic Animal Diversity. 3rd edn. (FAO) Food and Agriculture Organization of the United Unions FAO, Rome. https://doi.org/10.18356/25c78cba-en
- Seo D, Md. Bhuiyan SA, Sultana H, Heo JM, et al. (2016) Genetic diversity analysis of South and East Asian Duck populations using highly polymorphic microsatellite markers. Asian-Australas. J Anim 29: 471-478. https://doi.org/10.5713/ajas.15.0915
- Vignal A, Milan D, SanCristobal M, Eggen A. (2002) A review on SNP and other types of molecular markers and their use in animal genetics. Genetics Selection Evolution 34: 275-305. https://doi.org/10.1186/1297-9686-34-3-275
- Wiener P, Burton D and Williams JL (2004) Breed relationships and definition in British cattle: A genetic analysis. Heredity 93: 597-602. https://doi.org/10.1038/sj.hdy.6800566
- Zeng XC, Chen HY, Hui WQ, Jia B et al. (2010) Genetic Diversity Measures of 8 Local Sheep Breeds in Northwest of China for Genetic Resource Conservation. Asian-Australas. J Anim Sci 23: 1552 -1556. https://doi.org/10.5713/ajas.2010.10132
- Share This