Genetic Diversity between Bali Cattle (Bos javanicus) and It’s Hybrids Using Microsatellite Markers

Iranian Journal of Applied Animal Science

دوره 10، شماره 3، آذر 2020، صفحه 453-460   

نویسندگان

J. Jakaria^{* 1}؛ A. Alwiyah²؛ F. Saputra³؛ M. Baihaqi¹؛ R.R. Noor¹

¹Department of Animal Production and Technology, Faculty of Animal Science, Institut Pertanian Bogor University, Bogor, Indonesia

²Goat Research Station, Sei Putih, North Sumatera, Indonesia

³Indonesian Research Institute for Animal Production, Bogor, Indonesia

چکیده

The aim of this study was to evaluate the Bali cattle genetic diversity and hybrid cattle using microsatellite markers. Blood samples (n=192) were collected from various cattle breed, i.e. Bali (n=96), Madura (n=48), and Peranakan Ongole (PO) Kebumen (n=48). The microsatellite locus used for assessing the genetic variation was INRA035, ILSTS006, ETH225, and HEL9, while the genetic profile was described using GenAlEX, Cervus, MEGA6, structure and R programs. As a result, 46 alleles were found at four microsatellite loci studied. The genetic diversity of Bali cattle from Bali island (H_o=0.337) and Nusa Penida island (H_o=0.375) were recorded lower than that of the hybrids, i.e. Madura (H_o=0.747) and PO Kebumen (H_o=0.567) cattle breeds. Specifically, we found 283 bp (locus ILSTS006), 194 bp (locus ETH225), 147 bp and 151 bp (locus HEL9) demonstrating the distinctive alleles for Bali cattle. Also, our experimental data showed that microsatellite markers used allowed us to produce an obvious differentiation of the cattle cluster between Bali cattle and the hybrids, which was meaningful for future cattle breeding program.

کلیدواژه‌ها

Bali cattle؛ genetic diversity؛ microsatellite marker

اصل مقاله

INTRODUCTION

Bali cattle, an Indonesian native cattle, is a domesticated descendant of banteng (Bos javanicus) (Martojo, 2012) and constitutes a beef cattle breed. The population is estimated to reach 27% (5 millionheads) of total cattle in Indonesia (Purwantara et al. 2012). The adaptive features of Bali cattle in marginal land are favorable for small holder farmers, while the reproductivity of the cattle is also high (Mohamad et al. 2009). Besides, Madura and PO Kebumen cattle breeds are also popular in small holder farmers; some studies reported that both cattle breeds were the hybrids of Bali cattle (Nijman et al. 2003; Hartati et al. 2015; Sutarno and Setyawan, 2016). The existence of Bali, Madura, and PO Kebumen cattle as Indonesian native cattle breed has been legalized through the Indonesian Ministry of Agriculture. The genetic variation of Bali cattle and it’s hybrid seemed to be partially documented. For further studies, microsatellite markers could be a noticeable approach in conducting the exploration of genetic diversity (Viryanski, 2019). Close breeding policy in Indonesia for Bali cattle in Bali and Nusa Penida island aims for maintaining the purity of Bali cattle in Indonesia. Madura cattle are the result of a crossbreeding between Zebu and Bali. Madura cattle have a native geographical distribution in Madura island and surroundings. Sapudi island is an isolated island that is concentrated as a close breeding area for Madura cattle. PO Kebumen cattle are the result of selection in Kebumen Regency, Central Java. In 1806, Ongole cattle (Bos indicus) were brought by traders to East Java and mated with Javanese cattle (Bos javanicus) (Sutarno and Setyawan, 2016). Many areas have extensively used microsatellite markers for evolution studies and genetic relationships in of cattle, including Bos taurus and Bos indicus (MacHugh et al. 1997), Niger cattle (Bos indicus) (Grema et al. 2017), Brazilian cattle (De Oliveira et al. 2012), Latin-American Creole (Bos indicus) (Delgado et al. 2012), Sanga cattle (Gororo et al. 2018), Blanco Orejinegro cattle (Martínez et al. 2013), and Vietnamese indigenous cattle (Pham et al. 2013). The approach is also used for conducting pedigree verification (Jevrosima et al. 2009) and investigating the association with carcass traits in Hanwoo cattle (Choi et al. 2006). The method has favorable features such as locus-specific, co-dominant, highly polymorphic, rapid, reproducible, while it is also possible to conduct at various scales from individual to population (Viryanski, 2019). Although the use of microsatellite markers on Bali cattle has been previously reported by researchers (Handiwirawan et al. 2003; Nijman et al. 2003; Sutarno et al. 2015), the number of samples and the methodology used seems to be limited. In terms of the method, there is a shifting from polyacrylamide gel electrophoresis (PAGE) to fragment analysis (Viryanski, 2019). Currently, the microsatellite markers have been applied for molecular investigation of Indonesian beef cattle, including Bali, Madura, and PO cattle breeds (Agung et al. 2019). However, the study needs improvement, particularly focusing on the use of locus recommended by Measurement of Domestic Animal Diversity (MoDAD), International Society of Animal Genetics (ISAG) FAO with totally reaching 30 loci especially INRA035 and HEL9 due to their high diversity. Therefore, genetic diversity of Bali cattle (domesticated at Bali and Nusa Penida islands) and their hybrids (Madura and PO Kebumen) were investigated in this study using microsatellite markers.

 

MATERIALS AND METHODS

Sample collection and total DNA extraction

A blood sample (3-5 mL) of 192 individuals was collected through the jugular vein by a veterinarian (Table 1), using vacuum venojectcontaining anti-coagulant EDTA K3 (BD, United State). The DNA extraction was performed through standard procedures of DNA Mini Kit (GenAid protocol Cat. No. GB100).

 

Primer, amplification, fragment analysis

The four loci of microsatellite used in this study are presented in Table 2. Polymerase chain reaction (PCR) amplification of microsatellite primer was made in a final volume of 28 µL containing 2 × GoTaq® Green Master Mix (Promega, United States), primer (forward and reverse,25 ng/μL primer), 7.7 μL nuclease-free water, and DNA sample (25 to 50 ng/μL). PCR program (Eppendorf, Germany) was operated as the following procedure. The initial denaturation was at 95 ˚C for 5 min (1 cycle). The amplification was conducted by 35 cycles: (1) denaturation 95 ˚C for 10 s, (2) annealing at 55-60 ˚C for 20 s (depending on microsatellite locus), and (3) extension at 72 ˚C for 30 s, and (4) finally elongation at 72 ˚C for 5 min. The PCR products were then observed by electrophoresis using 1.5% agarose gel. Multiplex fragment analysis was performed on fragment analysis services on 1^st base (http://www.base-asia.com/fragment_analysis/).

 

Data analysis

Each microsatellite locus was determined for calculating the allele number (na) and effective allele number (ne), allele frequency, observed heterozygosity (H_o) and expected heterozygosity (H_e), F statistic (F_IS, F_IT, F_ST). Hardy-Weinberg (HW) equilibrium test and molecular variance analysis (AMOVA) were analyzed using GenAlEx 6.5 (Peakall and Smouse, 2012), while the polymorphic informative content (PIC) was analyzed using CERVUS version 3.0.7 (Kalinowski et al. 2007). Cluster differentiation among populations, genetic distance as well as the genetic tree ware analyzed using MEGA version 6 (Tamura et al. 2013). Genetic structure and genetic admixture in cattle species were analyzed by using the procedure of Bayesian clustering in STRUCTURE version 2.2 (Pritchard et al. 2000). This study employed a total of 10 independent runs for each K between 2 and 10. A burn-in period used was 1000000 iterations, then followed by 1000000 iterations of the Markov chain Monte Carlo algorithm. The optimum K value was determined using Structure Harvester (Earl and vonHoldt, 2012), adopted from the Evanno method (Evanno et al. 2005). Finally, this study used the principal component analysis (PCA) using R version 3.2.0. (Jombart, 2008) for data analysis.

 

RESULTS AND DISCUSSION

Microsatellite diversity

The study successfully identified 46 alleles of the four loci, i.e. 8 alleles (INRA035), 12 alleles (ILSTS006), 12 alleles (ETH225), and 14 alleles (HEL9) (Table 1).

 

Table 1 Location of cattle breeds studied

 

N: number of individual and VBC: village breeding centre.

 

Table 2 The description of microsatellite markers used

 

^* Microsatellite marker recommended by MoDAD, ISAG FAO; Chr.: chromosome; Access number GenBank ¹X68049, ²L23482, ³Z14043 and ⁴X65214; bp: base pair and Ta: temperature annealing.

 

The Bali cattle (from Bali and Nusa Penida islands) possessed a lower number of alleles compared to the Madura and PO Kebumen cattle, especially in INRA035 and HEL9 loci (Table 3). Clearly, the HEL9 served as the private allele in Bali cattle, i.e. 147 bp and 151 bp, specifically 147 bp with the highest allele frequency compared to151 bp. This private allele was not found in both Madura and PO Kebumen cattle breeds. Furthermore, Bali cattle from Nusa Penida island tend to have a higher uniformity compared to that from Bali island. Based on the observation on INRA035, ILSTS006 and ETH225 loci, the number of alleles in Bali cattle from Nusa Penida island was lower than that of Bali island (Table 4). In addition, the H_o and H_e values of Bali cattle from Nusa Penida island were the lowest, i.e. 0.375 ± 0.181 and 0.398 ± 0.170, respectively. On the contrary, the highest score of the H_o and H_ewas attributed to the Madura cattle, i.e. 0.747 ± 0.111 and 0.763 ± 0.044. Regarding the total population, there was no difference between H_o (0.516±0.075) and H_e (0.579±0.073), with the exception of the scores of PO Kebumen, i.e. 0.567 ± 0.109 and 0.739 ± 0.070 (Table 4). The population differentiation due to genetic structure (F_ST), inbreeding coefficient of individual relative to the total population (F_IT) and inbreeding coefficient of individual within-population (F_IS) and polymorphism information content (PIC) values were 0.246 ± 0.067, 0.316 ± 0.081, 0.070 ± 0.132 and 0.738 ± 0.102, respectively (Table 5). This indicates that all microsatellite loci contribute to the genetic differentiation (F_ST=24.6%), primarily on the INRA035 and HEL9 loci. Based on F_IT= 31.6%, the ILST006 and HEL9 loci greatly account for the deficiency of heterozygote (inbreeding coefficient) among populations reaching up to 49.1% and 39.1%, while, within-population (F_IS=7.0%), the ILSTS006 and HEL9 loci also contributed to deficiency of heterozygote, except for the INRA035 and ETH225 contributing to excess of heterozygote. Based on the PIC analyses, all microsatellite markers were informative and in this study, the ETH225 was the most informative locus with the highest score of PIC (0.804). Meanwhile, the HW equilibrium analysis showed that all microsatellite markers studied were in disequilibrium status (P<0.001).

 

Population structure and phylogenetic tree

Based on genetic distance analysis, the four cattle populations showed a different genetic distance (Table 6). The genetic tree shows that Bali cattle from Bali island and Nusa Penida islands differed, although they have high similarity. In contrast, the Bali cattle had different cluster groups with Madura cattle and PO Kebumen populations. The results show two main clusters: Bos javanicus and Bos indicus (Figure 1). In addition, Structure Harvester's analysis exhibited the optimum value at K= 3, demonstrating that the Bali cattle from Bali and Nusa Penida islands possessed genetic similarities (red). On the other hand, Madura cattle (blue) and PO Kebumen cattle (green) located in different clusters (Figure 2).

 

Table 3 Frequency of allele and allele size (bp) for the four microsatellite markers^*

 

^* Underline is a specific allele.

N: number of individuals.

 

Similarly, PCA analysis also demonstrated two main clusters, i.e. Bos javanicus (Bali cattle of Bali and Nusa Penida islands) and Bos indicus (Madura and PO Kebumen cattle), shown in Figure 3.Additionally, the AMOVA analysis results show that the between-population variation was 29.4% (P<0.000), shown in Table 7.

 

Table 4 Alleles number (Na), effective alleles number (Ne), heterozygosity (H_o) and expected heterozygosity (H_e)

 

SE: standard error.

 

Table 5 F-statistic (F_ST, F_IS, F_IT), PIC and HW test in Bali-1, Bali-2, Madura and Peranakan Ongole (PO) Kebumen cattle populations

 

Na: number of allele; PIC: polymorphic informative content and HW: Hardy-Weinberg equilibrium.

** (P<0.001).

SE: standard error.

 

Table 6 Nei's genetic identity (above diagonal) and genetic distance (below diagonal)

 

 

Variation in microsatellite markers

Based on the listed of microsatellite markers in MoDAD ISAG FAO, the four studies out of the 30 recommended loci exhibited high polymorphisms in the Bali cattle and it’s hybrids (Madura and PO Kebumen cattle). Meanwhile, the high value of PIC was found in all loci, i.e INRA035 (0.586), ILSTS006 (0.793), ETH225 (0.804) and HEL9 (0.767) (Table 5). Agung et al. (2019) reported that the PIC of ILSTS006 and ETH225 was 0.869 and 0.935, respectively, which was applied to 10 Indonesian cattle, including Bali, Madura, and PO cattle. Gororo et al. (2018) also asserted the PIC of ILSTS006 and ETH225 reached 0.748 and 0.661, investigated in three Zimbabwean Sanga cattle breeds. Kale et al. (2010) also found the PIC of INRA035, ILSTS006, and ETH225, with a value of 0.684, 0.749 and 0.602 in three Indian cattle breeds (Gir, Deoni and Kankrej). PIC from various loci was also reported by Sodhi et al. (2007), with scores of INRA035 (0.815), ILSTS006 (0.555), ETH225 (0.554), and HEL9 (0.817) studied in Indian Kankrej cattle breeds.

 

Table 7 Analysis of molecular variance (AMOVA) among cattle breed populations

 

Df: degree of freedom; SS: sum of squares; MS: mean of square and Var. comp.: variance component.

 

Figure 1 Dendogram of Bali cattle domesticated at Bali island (Bali-1), Bali cattle domesticated at Nusa Penida island (Bali-2), Madura cattle and PO Kebumen cattle using UPGMA method

 

 

Figure 2 Genetic structures of the four population cattle breeds

K= 3 represents optimal genetic structure for Bali cattle (red), Madura cattle (blue), and PO Kebumen cattle (green)

 

 

Based on these findings, PIC obtained at loci could differ due to some factors, including the number of samples and cattle breeds. However, in this study, four microsatellite markers are considered as an ideal marker to investigate genetic diversity since they are informative and have high diversity, as represented by their high value of PIC, which is more than 0.5 (Viryanski, 2019).

 

Genetic diversity of Bali cattle and the hybrids

Microsatellite markers applied in Bali cattle (Bos javanaicus) and the hybrids demonstrated noticeable differences in genetic diversity, observed in both total populations and within the population for each microsatellite marker locus. The INRA035, ETH225, and HEL9 loci are a specific locus for Bali cattle which is not present in Madura and PO Kebumen cattle, especially HEL9 allele 147 bp possessing the highest frequency. Previously, locus INRA035 and HEL9 were found as the specific allele for Bali cattle, primarily in HEL9 allele A (Handiwirawan et al. 2003), but the determination of allele for each locus was carried out by PAGE analysis, without using comparative cattle breeds in Indonesia. The low rate of genetic diversity of Bali cattle (domesticated at Bali and Nusa Penida islands) compared to the hybrids may result from an artificial insemination (AI) program. This is evidenced by the results of the HW equilibrium test, showing the imbalance for each locus (P<0.001), high inbreeding depression (in F_IS and F_IT), as described in Table 5. Interestingly, such HW non-equilibrium and inbreeding depression were always found in commercial livestock, especially beef cattle (Grema et al. 2017; Gororo et al. 2018; Agung et al. 2019).

 

Figure 3 Principle component analysis (PCA) plot of four populations. (1) Madura cattle; (2) PO Kebumen cattle; (3) Bali cattle domesticated at Bali island and (4) Bali cattle domesticated at Nusa Penida island

 

 

Studies on genetic diversity of cattle are recommended to employ a larger quantity of microsatellite loci, as previously reported by Grema et al. (2017) using 27 loci, Gororo et al. (2018) using 16 loci, Agung et al. (2019) using 12 loci, Ilie et al. (2015) using 11 loci, and Özşensoy et al. (2014) using 7 loci. In this work, although the number of the locus in four microsatellite markers is relatively small the microsatellite enables to differentiation of the cluster clearly between the Bos javanicus cluster and the hybrids, using the genetic tree of UPGMA, genetic structure, and PCA analysis. Moreover, the result from D-loop analysis showed the same cluster for PO and Madura cattle (Abdullah et al. 2012). This study could produce satisfying information that can be meaningful for cattle breeding strategies in the future, mainly related to the conservation, utilization, and breeding of Bali cattle and it’s hybrids.

 

CONCLUSION

Four microsatellite markers (INRA035, ILSTS006, ETH225, and HEL9) used in this research found 46 alleles. Furthermore, 283 bp of ILSTS006 locus, 194 bp of ETH225 locus and 147 and 151 bp of HEL9 locus were private alleles in Bali cattle that were not found in Madura and PO Kebumen cattle breeds. Microsatellite markers of INRA035, ILSTS006, ETH225, and HEL9 loci were informative and use full loci in genetic diversity study especially for Bali cattle and their hybrid.

 

ACKNOWLEDGEMENT

The authors acknowledge the Head of Breeding Center for Bali cattle (BPTU-HPT) and the Head of Artificial Insemination (BIBD) of Bali province, Indonesia for facilitating blood sampling in this research. This project was supported by the PDUPT Research Grant number: 1757/IT3.11/PN/2018 from the Ministry of Research, Technology, and Higher Education, Indonesia.

مراجع

Abdullah M., Martojo H., Noor R. and Solihin D. (2012). Genetic characterization of the aceh cattle using phenotypic, mitochondrial DNA of D-loop region and microsatellite DNA analyses . Reprod. Domest. Anim. 47, 15-17.

Agung P.P., Saputra F., Zein M.S.A., Wulandari A.S., Putra W.P.B., Said S. and Jakaria J. (2019). Genetic diversity of Indonesian cattle breeds based on microsatellite markers. Asian-Australasian J. Anim. Sci. 32, 467-476.

Choi I.S., Kong H.S., Oh J.D., Yoon D.H., Cho B.W., Choi Y.H., Kim K.S., Choi K.D., Lee H.K. and Jeon G.J. (2006). Analysis of microsatellite markers on bovine chromosomes 1 and 14 for potential allelic association with carcass traits in Hanwoo (Korean cattle). Asian-Australasian J. Anim. Sci. 19, 927-930.

De Oliveira A.P.F., De Carvalho J.H., Miretti M.M., Lara M.A.C. and Contel E.P.B. (2012). Genetic diversity of the Brazilian creole cattle pé-duro assessed by microsatellites and mitochondrial DNA. Rev. Bras. Zootec. 41, 2316-2322.

Delgado J.V., Martínez A.M., Acosta A., Álvarez L.A., Armstrong E., Camacho E., Cañõn J., Cortés O., Dunner S., Landi V., Marques J.R., Martín-Burriel I., Martínez O.R., Martínez R.D., Melucci L., Muñoz J.E., Penedo M.C.T., Postiglioni A., Quirõz J., Rodellar C., Sponenberg P., Uffo O., Ulloa-Arvizu R., Vega-Pla J.L., Villalobos A., Zambrano D., Zaragoza P., Gama L.T. and Ginja C. (2012). Genetic characterization of Latin-American Creole cattle using microsatellite markers. Anim. Genet. 43, 2-10.

Earl D.A. and vonHoldt B.M. (2012). STRUCTURE HARVESTER: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359-361.

Evanno G., Regnaut S. and Goudet J. (2005). Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611-2620.

Gororo E., Makuza S.M., Chatiza F.P., Chidzwondo F. and Sanyika T.W. (2018). Genetic diversity in Zimbabwean Sanga cattle breeds using microsatellite markers. South Africa J. Anim. Sci. 48, 128-141.

Grema M., Traoré A., Issa M., Hamani M., Abdou M., Soudré A., Sanou M., Pichler R., Tamboura H.H., Alhassane Y. and Periasamy K. (2017). Short tandem repeat (STR) based genetic diversity and relationship of indigenous Niger cattle. Arch. Anim. Breed. 60, 399-408.

Handiwirawan E., Noor R.R., Muladno and Schüler L. (2003). The use of HEL9 and INRA035 microsatellites as specific markers for Bali cattle. Arch. Anim. Breed. 46, 503-512.

Hartati H., Utsunomiya Y.T., Sonstegard T.S., Garcia J.F., Jakaria J. and Muladno M. (2015). Evidence of Bos javanicus × Bos indicus hybridization and major QTLs for birth weight in Indonesian Peranakan Ongole cattle. BMC Genet. 16, 1-9.

Ilie D.E., Cean A., Cziszter L.T., Gavojdian D., Ivan A. and Kusza S. (2015). Microsatellite and mitochondrial DNA study of native eastern European cattle populations: The case of the Romanian Grey. PLoS One. 10, e0138736.

Jevrosima S., Stanimirovic Z., Dimitrijevic V., Stojic V., Natalija F. and Lazarevic M. (2009). Microsatellite DNA polymorphism and its usefulness for pedigree verification in Simmental cattle from Serbia. Acta Vet. Brno. 59, 621-631.

Jombart T. (2008). Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics.24, 1403-1405.

Kale D.S., Rank D.N., Joshi C.G., Yadav B.R., Koringa P.G., Thakkar K.M., TolenkhombaT.C. and Solanki J.V. (2010). Genetic diversity among Indian Gir, Deoni and Kankrej cattle breeds based on microsatellite markers. Indian J. Biotechnol. 9, 126-130.

Kalinowski S.T., Taper M.L. and Marshall T.C. (2007). Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 19, 1099-1106.

MacHugh D.E., Shriver M.D., Loftus R.T., Cunningham P. and Bradley D.G. (1997). Microsatellite DNA variation and the evolution, domestication and phylogeography of taurine and zebu cattle (Bos taurus and Bos indicus). Genetics. 146, 1071-1086.

Martínez R., Llinás A.P. and Rocha J.F.M. (2013). Genetic variability in Blanco Orejinegro breed cattle populations in Colombia. Genet. Mol. Res. 12, 1083-1094.

Martojo H. (2012). Indigenous Bali cattle is most suitable for sustainable small farming in Indonesia. Reprod. Domest. Anim. 47, 10-14.

Mohamad K., Olsson M., van Tol H.T.A., Mikko S., Vlamings B.H., Andersson G., Rodríguez-Martínez H., Purwantara B., Paling R.W., Colenbrander B. and Lenstra J.A. (2009). On the origin of Indonesian cattle. PLoS One. 4, 1-6.

Nijman I.J., Otsen M., Verkaar E.L.C., De Ruijter C., Hanekamp E., Ochieng J.W., Shamshad S., Rege J.E.O., Hanotte O., Barwegen M.W., Sulawati T. and Lenstra J.A. (2003). Hybridization of banteng (Bos javanicus) and zebu (Bos indicus) revealed by mitochondrial DNA, satellite DNA, AFLP, and microsatellites. Heredity. 90, 10-16.

Özşensoy Y., Kurar E., Bulut Z. and Nizamlioǧlu M. (2014). Y chromosome analysis of native Turkish cattle breeds by microsatellite markers. Turkish J. Biol. 38, 388-395.

Peakall R. and Smouse P.E. (2012). GenALEx 6.5: Genetic analysis in excel. Population genetic software for teaching and research-an update. Bioinformatics. 28, 2537-2539.

Pham L.D., Do D.N., Binh N.T., Nam L.Q., Van Ba N., Thuy T.T.T., Hoan T.X., Cuong V.C. and Kadarmideen H.N. (2013). Assessment of genetic diversity and population structure of Vietnamese indigenous cattle populations by microsatellites. Livest. Sci. 155, 17-22.

Pritchard J.K., Stephens M. and Donnelly P. (2000). Inference of population structure using multi locus genotype data. Genetics. 155, 945-959.

Purwantara B., Noor R.R., Andersson G. and Rodriguez-Martinez H. (2012). Banteng and Bali cattle in Indonesia: Status and forecasts. Reprod. Domest. Anim. 47, 2-6.

Sodhi M., Mukesh M., Prakash B., Mishra B.P., Sobti R.C., Singh K.P. and Ahlawat S.P.S. (2007). Microsatellite marker based characterization of genetic diversity in kankrej cattle. J. Appl. Anim. Res. 31, 153-158.

Sutarno S. and Setyawan A.D. (2016). The diversity of local cattle in Indonesia and the efforts to develop superior indigenous cattle breeds. Biodiversitas J. Biol. Divers. 17, 275-295.

Sutarno S., Setyawan A.D. and Lymbery A.J. (2015). Genetic diversity of five Indonesian native cattle breeds at microsatellite loci. Asian J. Anim. Sci. 9, 57-64.

Tamura K., Stecher G., Peterson D., Filipski A. and Kumar S. (2013). MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30, 2725-2729.

Viryanski D. (2019). Microsatellite markers – a tool for molecular characterization of cattle genetic resources. Bulgarian J. Agric. Sci. 25, 158-165.