Open Access

Genomic conservation of cattle microsatellite loci in wild gaur (Bos gaurus) and current genetic status of this species in Vietnam

  • Trung Thanh Nguyen1,
  • Sem Genini2,
  • Linh Chi Bui1,
  • Peter Voegeli3,
  • Gerald Stranzinger3,
  • Jean-Paul Renard4,
  • Jean-Charles Maillard5 and
  • Bui Xuan Nguyen1Email author
Contributed equally
BMC Genetics20078:77

https://doi.org/10.1186/1471-2156-8-77

Received: 28 May 2007

Accepted: 06 November 2007

Published: 06 November 2007

Abstract

Background

The wild gaur (Bos gaurus) is an endangered wild cattle species. In Vietnam, the total number of wild gaurs is estimated at a maximum of 500 individuals. Inbreeding and genetic drift are current relevant threats to this small population size. Therefore, information about the genetic status of the Vietnamese wild gaur population is essential to develop strategies for conservation and effective long-term management for this species. In the present study, we performed cross-species amplification of 130 bovine microsatellite markers, in order to evaluate the applicability and conservation of cattle microsatellite loci in the wild gaur genome. The genetic diversity of Vietnamese wild gaur was also investigated, based on data collected from the 117 successfully amplified loci.

Results

One hundred-thirty cattle microsatellite markers were tested on a panel of 11 animals. Efficient amplifications were observed for 117 markers (90%) with a total of 264 alleles, and of these, 68 (58.1%) gave polymorphic band patterns. The number of alleles per locus among the polymorphic markers ranged from two to six. Thirteen loci (BM1314, BM2304, BM6017, BMC2228, BMS332, BMS911, CSSM023, ETH123, HAUT14, HEL11, HEL5, ILSTS005 and INRA189) distributed on nine different cattle chromosomes failed to amplify wild gaur genomic DNA. Three cattle Y-chromosome specific microsatellite markers (INRA124, INRA126 and BM861) were also highly specific in wild gaur, only displaying an amplification product in the males. Genotype data collected from the 117 successfully amplified microsatellites were used to assess the genetic diversity of this species in Vietnam. Polymorphic Information Content (PIC) values varied between 0.083 and 0.767 with a mean of 0.252 while observed heterozygosities (H o ) ranged from 0.091 to 0.909 (mean of 0.269). Nei's unbiased mean heterozygosity and the mean allele number across loci were 0.298 and 2.2, respectively.

Conclusion

Extensive conservation of cattle microsatellite loci in the wild gaur genome, as shown by our results, indicated a high applicability of bovine microsatellites for genetic characterization and population genetic studies of this species. Moreover, the low genetic diversity observed in Vietnamese wild gaur further underlines the necessity of specific strategies and appropriate management plans to preserve this endangered species from extinction.

Background

The wild gaur, also known as the Indian bison or seladang, is a member of the subfamily Bovinae and is currently classified among endangered species and listed as vulnerable by International Union for Conservation of Nature and Natural Resources [1]. According to the Asian Wild Cattle Conservation Assessment and Management Plan (CAMP – [2]), three wild subspecies are generally recognized, including Bos gaurus laosiensis (Myanmar to China), Bos gaurus hubbacki (Thailand and Malaysia) and Bos gaurus gaurus (India and Nepal). Recently, the species name Bos gaurus was suggested for wild gaur instead of Bibos gauris or Bos frontalis by the International Commission on Zoological Nomenclature [3]; this name is currently used.

The gaur is one of the most impressive and largest of the wild cattle. A typical adult wild gaur bull may measure up to two meters at the shoulders and 900 kg in weight [4]. Gaurs are gregarious animals that live in hilly terrains below an altitude of 1,800 meters in herds ranging from 6 to 40 individuals. The distribution of wild gaur includes areas of southern and south-eastern Asia, from India to peninsular Malaysia, occurring in India, Nepal, Bhutan, Bangladesh, Myanmar, Thailand, China, Laos, Cambodia, Vietnam and Malaysia [5, 6]. In India, wild gaurs have been probably domesticated about 2500 years ago [7], mainly for work and meat [8]. Domesticated gaurs are referred to as "gayal" or "mithan" (Bos frontalis) and are completely interfertile with their wild relatives [9], which display a karyotype of 2n = 58 [10]. Furthermore, herders breed mithans or cross them with cattle to obtain offspring with enhanced production and performance, however usually only F1 females are fertile and can be used for further breeding purposes.

The global population of wild gaur ranges from 13,000 to 30,000 with a population of mature individuals between 5,200 and 18,000. In the last decades, the number of wild gaurs decreased dramatically due to the loss of suitable habitat (in favour of agriculture and its domestic counterpart), hunting or hybridization with domestic cattle [11]. The latter threat also caused the transmission and outbreak of various devastating diseases, such as foot-and-mouth, rinderpest and anthrax [12]. In Vietnam, the total number of wild gaurs is estimated at a maximum of 500 individuals of which 10% distributed in the Cat Tien National Park, localized close to the Ho Chi Minh City in the south of the country. During 1991–1995, 120 wild gaurs were reported to be killed (more than one generation [1]). Thus, information about the current genetic status of the Vietnamese wild gaur population is important and necessary to develop strategies for conservation and effective long-term management for this species.

Successful amplification and extensive conservation of cattle microsatellite sequences in several species of Bovidae and Cervidae families have been documented in numerous works [13, 14], thus allowing possible population genetic studies on related Bovidae species for which microsatellites have not been developed [1518]. Furthermore, cross-species amplification was also applied to the study of population variations in geographically isolated or endangered species [19, 20]. These studies suggest that a characterization of wild gaur, as a member of the subfamily Bovinae, with bovine microsatellite markers is highly pertinent and suitable.

Previous genetic studies were carried out on gaur [21, 22], however they were limited to a domesticated group of Bos frontalis and only a low number of cattle microsatellites were analyzed. Therefore, the questions about the conservation of cattle microsatellite DNA sequences, as well as the applicability of these markers for population genetic studies in Bos gaurus remain open.

The principal aims of this study were (1) to evaluate the applicability and conservation of cattle microsatellite DNA sequences in the wild gaur genome and (2) to estimate the current genetic status of this species in Vietnam.

Results and discussion

One hundred-thirty cattle microsatellite markers were tested for amplification of genomic DNA from a panel of 11 wild gaurs. Three Brown Swiss cattles (Bos taurus) were used as positive control. Although some amplification failures were observed, 90% of the microsatellites from cattle could be successfully amplified by PCR on gaur genomic DNA, of which 68 markers (58.1%) were polymorphic. A total of 264 alleles were detected across the 117 amplified loci with the number of alleles ranging from one to six (Table 1) with a mean of 2.2 alleles per locus. Thirteen microsatellites (10%) distributed on cattle chromosomes 8 (BM2304), 10 (ILSTS005), 18 (HAUT14), 21 (HEL5), 24 (CSSM023), 26 (BM1314, BMS332 and HEL11), 29 (BMC2228), X (BM6017, BMS911 and ETH123) and Y (INRA189), respectively, failed to amplify in wild gaur. Notably, the non-amplification of locus ILSTS005 indicated the absence of this sequence in both wild gaur and mithan [22]. As expected, all the microsatellite markers could be successfully amplified in the positive control samples (Bos taurus), with 92% of them being polymorphic.
Table 1

Characterisation of 130 bovine microsatellites tested on a panel of 11 wild gaurs

Marker

Chromosome no. in cattle

Allele size range (bp)

Number of alleles

H E

H o

PIC

AGLA17

1

217–221

3

0.385

0.273

0.326

AGLA293

5

231–231

1

-

-

-

BL1029

14

151–155

2

0.091

0.091

0.083

BL1038

6

109–109

1

-

-

-

BL1040

26

96–108

3

0.255

0.273

0.228

BL1043

7

100–104

3

0.177

0.182

0.163

BL1071

13

179–195

4

0.680

0.636

0.594

BL1095

15

164–174

3

0.385

0.455

0.326

BL25

28

171–185

2

0.247

0.273

0.208

BM1314*

26

-

-

-

-

-

BM1818

23

264–264

1

-

-

-

BM1824

1

187–187

1

-

-

-

BM1862

17

201–213

3

0.567

0.727

0.463

BM188

26

108–108

1

-

-

-

BM203

27

211–213

2

0.312

0.182

0.253

BM2113

2

129–129

1

-

-

-

BM2304*

8

-

-

-

-

-

BM3020

3

159–159

1

-

-

-

BM4005

25

107–107

1

-

-

-

BM4602

29

128–130

2

0.519

-

0.373

BM4621

6

131–131

1

-

-

-

BM6017*

X

-

-

-

-

-

BM6425

14

167–195

6

0.823

0.818

0.751

BM6438

1

256–256

1

-

-

-

BM6465

3

122–122

1

-

-

-

BM8139

1

110–116

3

0.394

0.273

0.344

BM8151

18

157–161

3

0.589

0.545

0.476

BM861

Y

135–135

1

-

-

-

BM875

10

107–119

2

0.519

0.364

0.373

BMC1410

4

215–219

3

0.593

0.636

0.504

BMC2228*

29

-

-

-

-

-

BMC6020

28

177–177

1

-

-

-

BMC6021

X

141–141

1

-

-

-

BMS1074

4

157–157

1

-

-

-

BMS1120

20

123–137

6

0.835

0.909

0.767

BMS1128

20

80–82

2

0.091

0.091

0.083

BMS1244

29

103–105

2

0.173

0.182

0.152

BMS1247

7

111–121

3

0.537

0.364

0.444

BMS1282

20

151–165

4

0.333

0.273

0.302

BMS1322

18

117–121

3

0.498

0.091

0.419

BMS1353

25

95–103

2

0.368

0.091

0.290

BMS1355

18

154–160

4

0.697

0.818

0.607

BMS1616

X

65–65

1

-

-

-

BMS1714

28

120–122

2

0.416

0.545

0.318

BMS1825

17

191–191

1

-

-

-

BMS1857

29

155–165

4

0.675

0.545

0.575

BMS1926

24

132–136

3

0.394

0.091

0.344

BMS1928

1

141–161

4

0.576

0.636

0.511

BMS1948

29

93–93

1

-

-

-

BMS1979

7

95–99

3

0.498

0.636

0.419

BMS2213

18

112–120

2

0.524

0.455

0.375

BMS2252

12

158–164

4

0.697

0.455

0.604

BMS2270

24

57–63

2

0.485

0.545

0.356

BMS2526

24

135–159

4

0.762

0.636

0.678

BMS2639

18

160–160

1

-

-

-

BMS3024

24

142–142

1

-

-

-

BMS332*

26

-

-

-

-

-

BMS4015

1

144–152

4

0.688

0.636

0.606

BMS424B

11

256–258

2

0.091

0.091

0.083

BMS522

7

134–134

1

-

-

-

BMS574

1

131–131

1

-

-

-

BMS631

X

146–146

1

-

-

-

BMS650

19

141–141

1

-

-

-

BMS672

22

143–143

1

-

-

-

BMS711

1

102–102

1

-

-

-

BMS745

19

109–109

1

-

-

-

BMS779

4

191–195

2

0.312

0.364

0.253

BMS911*

X

-

-

-

-

-

BR4206

18

110–110

1

-

-

-

BR4406

18

114–114

1

-

-

-

CSRM60

10

86–114

2

0.368

0.273

0.290

CSSM023*

24

-

-

-

-

-

CSSM66

14

182–202

3

0.593

0.727

0.504

ETH10

5

207–213

3

0.450

0.455

0.385

ETH11

16

204–212

4

0.688

0.636

0.593

ETH121

2

182–210

3

0.498

0.455

0.419

ETH123*

X

-

-

-

-

-

ETH152

5

198–198

1

-

-

-

ETH185

17

219–219

1

-

-

-

ETH225

9

145–159

3

0.636

0.636

0.524

ETH3

19

127–131

3

0.654

0.545

0.553

HAUT14*

18

-

-

-

-

-

HAUT24

22

120–120

1

-

-

-

HAUT27

26

145–145

1

-

-

-

HEL1

15

108–120

3

0.628

0.636

0.519

HEL11*

26

-

-

-

-

-

HEL13

11

193–203

3

0.325

0.364

0.282

HEL5*

21

-

-

-

-

-

HEL9

8

146–152

4

0.610

0.545

0.533

IDVGA59

26

250–254

3

0.437

0.364

0.360

IDVGA90

7

194–194

1

-

-

-

ILSTS005*

10

-

-

-

-

-

ILSTS006

7

275–281

2

0.173

 

0.152

ILSTS015

29

265–265

1

-

-

-

ILSTS017

X

117–117

1

-

-

-

ILSTS021

18

116–116

1

-

-

-

ILSTS102

25

146–146

1

-

-

-

INRA005

12

135–141

4

0.697

0.818

0.600

INRA023

3

207–217

4

0.710

0.636

0.623

INRA032

11

169–181

5

0.753

0.727

0.674

INRA035

16

108–108

1

-

-

-

INRA037

10

126–132

4

0.727

0.636

0.637

INRA063

18

173–187

5

0.758

0.636

0.675

INRA081

26

145–153

3

0.567

0.545

0.463

INRA117

1

91–97

2

0.173

0.182

0.152

INRA121

18

114–136

4

0.710

0.545

0.615

INRA124

Y

132–132

1

-

-

-

INRA126

Y

182–182

1

-

-

-

INRA133

6

221–231

3

0.437

0.364

0.360

INRA183

27

117–117

1

-

-

-

INRA189*

Y

-

-

-

-

-

MB054

18

123–123

1

-

-

-

MB085

15

198–202

3

0.593

0.455

0.505

MHCII

23

213–225

4

0.723

0.636

0.633

MM12E6

9

108–108

1

-

-

-

RM026

26

81–81

1

-

-

-

RM372

8

128–134

3

0.450

0.364

0.385

SPS115

15

253–253

1

-

-

-

TEXAN10

18

145–151

4

0.706

0.818

0.613

TGLA122

21

166–168

2

0.455

0.455

0.340

TGLA126

20

121–125

3

0.498

0.091

0.419

TGLA179

27

89–103

3

0.697

0.636

0.591

TGLA227

18

72–84

3

0.584

0.455

0.490

TGLA23

13

100–104

3

0.567

0.818

0.436

TGLA49

1

115–117

2

0.247

0.273

0.208

TGLA53

16

151–175

5

0.701

0.727

0.606

TGLA73

9

116–126

4

0.749

0.727

0.663

UWCA25

13

102–102

1

-

-

-

XBM11

X

182–182

1

-

-

-

XBM7

X

174–174

1

-

-

-

* = markers not amplified

H E = expected heterozygosity

H o = observed heterozygosity

PIC = polymorphism Information Content

The 28 microsatellites with PIC value > 0.5 are bold-faced. Information concerning the bovine microsatellite markers used can be acquired from internet sites [32-34].

The applicability of bovine microsatellite markers for genetic studies in several Bovidae species has been reported in different studies and demonstrated extensive genomic conservation of cattle DNA microsatellite sequences during evolution. However, this conservation varies consistently within the Bovidae subfamilies and species (Table 2), as one can also expect by phylogenetic analyses. Additionally, percentage variations of conserved and polymorphic loci also depend on experimental conditions; specifically the number and the identity of the specific set of markers, as well as the number of animals tested play essential roles. This explains the variable levels of marker conservation in water buffalo, goat and sheep obtained from different studies (see Table 2 for references). The average conservation of cattle microsatellite loci across Caprinae species was generally lower than for Bovinae; in fact goat [23] and sheep [13] showed the lowest among all Bovidae. However, these results do not completely account for the experimental differences discussed above, which might influence the finding. With the same set of cattle microsatellites used in this study, our data suggest that Bos indicus is more closely related to Bos taurus than either Bos gaurus, Poephagus grunniens or Pseudoryx nghetinhensis (Table 2 and references therein). Within the Bovini, a close relationship between wild gaur and banteng (Bos javanicus) could be expected, as 90% and 94% of cattle microsatellites were conserved in their genomes, respectively (Table 2). These results were in line with recent taxonomy classifications of Bovidae based on molecular phylogenetic analyses [24, 25] and AFLP data [26]. Additionally, genomic conservation of cattle microsatellites has been tested on Cervidae, whereas 73.7% and 74.1% of bovine markers could be successfully amplified in sika deer (Cervus nippon) and red deer (Cervus elaphus), respectively [14]. Within species of Bos, wild gaur showed the lowest proportion of polymorphic markers (Table 2). This finding was in agreement and is possibly related to the small effective population size of Vietnamese wild gaurs, compared to other bovid species. The average allele sizes of most successful amplified markers in wild gaur were smaller compared to those obtained in cattle. This was expected [27] and in agreement with previous studies using cross-species amplification [15, 17].
Table 2

Genomic conservation of cattle microsatellite loci within the Bovidae and Cervidae families using cross species amplification

Taxon

Species – common name

Conserved loci

Polymorphic loci

References

Bovidae, Bovinae

    

   Bovini, Bovina

Bos gaurus – Wild gaur

90%

58.1%

this study

 

Bos indicus – Zebu

97.6%

87.3%

Nguyen – person. comm.

 

Bos javanicus – Banteng

94%

75%

Hishida et al. [40]

 

Poephagus grunniens – Yak

94.6%

94.3%

Nguyen et al. [18]

   Bovini, Bubalina

Bubalus bubalis – Water buffalo

70%

82%

Moore et al. [19]

  

75%

56%

Navani et al. [16]

  

85%

57%

Hishida et al. [40]

 

Syncerus caffer – African buffalo

83%

90%

van Hooft et al. [15]

   Bovini, Pseudoryina

Pseudoryx nghetinhensis – Saola

96.8%

59.3%

Nguyen et al. [20]

Bovidae, Caprinae

    

   Caprini

Capra hircus – Goat

57%

33%

Kemp et al. [23]

  

79.4%

81.5%

Kim et al. [17]

 

Ovis aries – Sheep

58%

67%

de Gortari et al. [13]

  

73.4%

42.5%

Slate et al. [14]

   Naemorhedini

Naemorhedus caudatus – Korean goral

85.3%

55.2%

Kim et al. [17]

Cervidae, Cervinae

    

   Cervus

Cervus elaphus – Red deer

74.1%

55.8%

Slate et al. [14]

 

Cervus nippon – Sika deer

73.7%

37.3%

Slate et al. [14]

The conservation of DNA sequences flanking microsatellites in the sex chromosomes among cattle and wild gaur was evaluated by testing the amplification of nine microsatellite loci, which mapped to BTAX (BM6017, BMC6021, BMS1616, BMS631, BMS911, ETH123, ILSTS017, XBM11 and XBM7) and four additional loci (INRA124, INRA126, INRA189 and BM861), which mapped to BTAY. All these sex-specific microsatellite markers were monomorphic. The loci BM6017, BMS911, ETH123 and INRA189 failed to amplify sex-chromosome specific DNA in wild gaur. Recently, it has also been reported that locus BM6017 could not be amplified in yaks [18]. This could be attributed to the absence of homologous sequences in both species. Moreover, studies demonstrated that BM861 and INRA126 successfully amplified from both sexes in yak [18, 21] and saola (Pseudoryx nghetinhensis – [20]), suggesting that they are not Y-specific. These findings indicated that yak and saola X chromosome retained a homologous segment of the Y chromosome, which contains both BM861 and INRA126 microsatellite markers. Contrary to these studies, we could amplify INRA124, INRA126 and BM861 only in male wild gaurs, indicating that they are Y specific markers in this species. Hanotte et al. [28] also tried to amplify locus INRA124 in two males of mithan but failed to obtain an amplification product. Even though we could not find any polymorphism for INRA124, INRA126 and BM861, these three microsatellites were polymorphic in several bovid species, including domestic cattle, bison, mithan, swamp buffalo and yak [21, 28]. This may be due to the relative small number (7) of male wild gaurs analyzed, which may have limited the informative content of this marker. In addition, the significant difference in allele size of locus BM861 between wild (135 bp) and domestic gaur (mithan, 150–156 bp -[21]) might be explained by the introgressive hybridisation of mithan, leading to the loss of the 135 bp allele from its wild ancestor.

Finally, genotype data collected from the 117 successfully amplified microsatellites were used for genetic studies of the Vietnamese wild gaur population. The expected heterozygosity value per locus across the population varied between 0.091 (BL1029, BMS1128 and BMS424B) and 0.835 (BMS1120) (Table 1). Accordingly, markers BL1029, BMS1128 and BMS424B showed the lowest PIC value (0.083), whereas BMS1120 had the highest (0.767) with a mean of 0.252. In addition, the observed heterozygosities (H o ) ranged from 0.091 to 0.909. Twenty-eight microsatellites (BL1071, BM6425, BMC1410, BMS1120, BMS1355, BMS1857, BMS1928, BMS2252, BMS2526, BMS4015, CSSM66, ETH11, ETH225, ETH3, HEL1, HEL9, INRA005, INRA023, INRA032, INRA037, INRA063, INRA121, MB085, MHCII, TEXAN10, TGLA179, TGLA53 and TGLA73; bold-faced in Table 1) showed good level of informativeness, having a PIC value higher than the threshold of 0.5 that is considered the value from which markers begin to be informative and therefore they would be the most suitable for diversity studies. Among these 28 most informative microsatellites, ten (CSSM66, ETH225, ETH3, HEL1, HEL9, INRA023, INRA032, INRA037, INRA063 and TGLA53) are also in the FAO standard panel of 30 microsatellites for diversity studies, allowing the study of introgression.

The average observed heterozygosity value (H o = 0.269) was lower than the average expected heterozygosity (Nei's unbiased mean heterozygosity; H E = 0.298) and this difference was statistically significant. Eleven (BM4602, BMS1322, BMS1353, BMS1926, ILSTS006, INRA037, INRA063, MHCII, TEXAN10, TGLA126 and TGLA73) out of 117 loci (9.4%) showed significant deviation from the Hardy-Weinberg equilibrium at p < 0.05. Over all loci, departure from Hardy Weinberg equilibrium was statistically highly significant (p < 0.001), reflecting the deviation in the direction of heterozygote deficit. These results indicate a frequent portion of homozygous individuals in the Vietnamese wild gaur population, resulting in an inbreeding coefficient value [F = (H E - H o )/H E ] of 0.10. Deviations from Hardy-Weinberg equilibrium of the population studied might be the results of inbreeding, but could also have been caused by the presence of non-amplifying (null) alleles, which could have contributed to the heterozygote deficiencies. In addition, the low average heterozygosity of wild gaurs may also be the consequence of the use of cattle derived microsatellite markers, which are expected to perform less in related species, having a higher fraction of null alleles and being less polymorphic.

Conclusion

The degree of polymorphism in the high number of microsatellite markers tested provides important information about the current genetic status of Vietnamese wild gaur. Its small population size would be dramatically adversely affected by high inbreeding and genetic drift. Therefore, the use of cattle microsatellites is adequate and recommended for further population genetic analyses, aimed to develop effective long-term conservation plans and strategies for this threatened species in Asia, especially in Vietnam. The reported low level of genetic diversity in wild gaur possibly reflects a bottleneck effect following the dramatic population reduction that occurred in this country during 1991–1995.

Methods

Sample collection

Eleven wild gaur samples (7 males and 4 females) were randomly collected in South Vietnam from the Chu Mom Ray Nature Reserve, Kon Tum province and Thao Cam Vien (Zoo and Botanical Garden), Ho Chi Minh City. Genomic DNA was extracted from tissue samples, fibroblast cells and bone fragments following standard methods [29, 30] with minor modifications. DNA from three Brown Swiss cattles (Bos taurus) was obtained from EDTA-anticoagulated whole blood [31] and used as positive control.

Microsatellite analysis

The same set of 130 bovine microsatellite markers analyzed by Nguyen et al. [18], excluded BPLP, and distributed across the entire cattle genome (Table 1) was tested for PCR amplification on wild gaur genomic DNA. The primer pairs, which show extensive polymorphism in cattle, were selected from internet sites [3234]. The forward primer of each microsatellite was 5'-labeled with either FAM, JOE, TAMRA, HEX or TET fluorescent tag. PCR amplification was carried out, as described by Nguyen et al. [18], in a total reaction volume of 25 μl containing 20–30 ng DNA template, 1× PCR buffer (10 mM Tris-HCl, pH 8.3, 50 mM KCl, 1.5 mM MgCl2), 1.25 mM of dNTP mix, 20 μM of each primer and 1.25 units of Taq polymerase (SIGMA, Buchs, Switzerland). Samples were cycled in a PCR Express Machine (Thermocycler PCR Express, Hybaid) at 95°C for 5 min, followed by 35 cycles of 95°C for 30 s, 52–60°C annealing temperature (depending on the microsatellite used) for 30 s and 72°C for 30 s. The final elongation was at 72°C for 7 min. Gel electrophoresis was performed with a 377 ABI sequencer (Applied Biosystems, Rotkreuz, Switzerland) with Genescan-350 TAMRA or ROX as internal standards. Fragment sizing and analysis were done using ABI 672 Genescan software and Genotyper (version 2.1) software (Applied Biosystems).

Statistical analysis

Genotypes were assigned for each individual based on allele size data. Allele frequencies, expected heterozygosity (H E = 1 - ∑ Pi2, where Pi = frequency of allele i), observed heterozygosity (H o ) for all loci were computed using the Microsatellite Toolkit version 3.1 [35]. Genetic diversity was estimated according to Nei [36], using the average heterozygosity across all loci. Probability tests of Hardy-Weinberg equilibrium [37] based on Markov chain approaches (5000 iterations) were performed using the GENEPOP package version 3.4 [38]. The polymorphism information content (PIC) was calculated using the following formula:
PIC = 1 i = 1 P i 2 i = 1 j = i + 1 P i 2 P j 2 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xI8qiVKYPFjYdHaVhbbf9v8qqaqFr0xc9vqFj0dXdbba91qpepeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaeeiuaaLaeeysaKKaee4qamKaeyypa0JaeGymaeJaeyOeI0YaaabuaeaacqqGqbaudaqhaaWcbaGaeeyAaKgabaGaeGOmaidaaaqaaiabbMgaPjabg2da9iabigdaXaqab0GaeyyeIuoakiabgkHiTmaaqafabaWaaabuaeaacqqGqbaudaqhaaWcbaGaeeyAaKgabaGaeGOmaidaaOGaeeiuaa1aa0baaSqaaiabbQgaQbqaaiabikdaYaaaaeaacqqGQbGAcqGH9aqpcqqGPbqAcqGHRaWkcqaIXaqmaeqaniabggHiLdaaleaacqqGPbqAcqGH9aqpcqaIXaqmaeqaniabggHiLdaaaa@50AE@

where Pi and Pj are frequencies of ith and jth alleles [39].

Notes

Declarations

Acknowledgements

We are grateful to Dr Do Tuoc, Forest Inventory and Planning Institute, Ministry of Forestry, Hanoi, Vietnam for the bone samples. We also thank Dr Uoc NT for sample collection and preparation. The gaur fibroblast cells were provided by the Laboratory of Embryotechnology, Vietnamese Academy of Science and Technology, Hanoi, Vietnam. This work was supported by BIODIVA-VAST project and the Swiss Federal Institute of Technology (ETH), Zurich.

Authors’ Affiliations

(1)
Vietnamese Academy of Sciences and Technology
(2)
Parco Tecnologico Padano (PTP), CERSA
(3)
Institute of Animal Sciences, Breeding Biology, Swiss Federal Institute of Technology
(4)
UMR Biologie du Développement et de la Reproduction. INRA
(5)
Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD)

References

  1. IUCN Red List of Threatened Species. [http://www.iucnredlist.org/]
  2. Byers O, Hedges S, Seal US: Asian Wild Cattle Conservation Assessment and Management Plan workshop. Working Document. 1995, Apple Valley, MN, USA: IUCN/SSC Conservation Breeding Specialist GroupGoogle Scholar
  3. ICZN: Opinion 2027 (Case 3010). Usage of 17 specific names based on wild species, which are pre-dated by or contemporary with those based on domestic animals (Lepidoptera, Osteichthyes, Mammalia): conserved. Bull Zool Nomencl. 2003, 60: 81-84.Google Scholar
  4. Prater PH: The Book of India Animals. 1980, Bombay, India: Bombay National History SocietyGoogle Scholar
  5. Ellerman JR, Morrison-Scott TCS: Checklist of Palaearctic and Indian Mammals 1758 to 1946. 1951, London: British MuseumGoogle Scholar
  6. Corbet GB, Hill JE: The Mammals of the Indomalayan Region: a Systematic Review. 1992, Oxford: Oxford University PressGoogle Scholar
  7. Felius M: Cattle Breeds – An Encyclopedia. 1995, Doetinchem: MissetGoogle Scholar
  8. Simoons FJ: Gayal or mithan. Evolution of Domesticated Animals. Edited by: Mason IL. 1984, London: Longman, 34-39.Google Scholar
  9. Payne WJA: Domestication: a forward step in civilization. Cattle Genetic Resources. Edited by: Hickman CG. 1991, Amsterdam: Elsevier, 51-72.Google Scholar
  10. Gallagher DS, Womack JE: Chromosome conservation in the Bovidae. J Hered. 1992, 83: 287-298.PubMedGoogle Scholar
  11. National Research Council: Little known Asian animals with a Promising Economic Future. 1983, Washington, D.C: National Academy PressGoogle Scholar
  12. Choudhury A: Distribution and conservation of the Gaur Bos gaurus in the Indian Subcontinent. Mam Rev. 2002, 32: 199-226. 10.1046/j.1365-2907.2002.00107.x.View ArticleGoogle Scholar
  13. de Gortari MJ, Freking BA, Kappes SM, Leymaster KA, Crawford AM, Stone RT, Beattie CW: Extensive genomic conservation of cattle microsatellite heterozygosity in sheep. Anim Genet. 1997, 28: 274-290. 10.1111/j.1365-2052.1997.00153.x.View ArticlePubMedGoogle Scholar
  14. Slate J, Coltman DW, Goodman SJ, MacLean I, Pemberton JM, Williams JL: Bovine microsatellite loci are highly conserved in red deer (Cervus elaphus), sika deer (Cervus nippon) and Soay sheep (Ovis aries). Anim Genet. 1998, 29: 307-315. 10.1046/j.1365-2052.1998.00347.x.View ArticlePubMedGoogle Scholar
  15. van Hooft WF, Hanotte O, Wenink PW, Groen AF, Sugimoto Y, Prins HH, Teale A: Applicability of bovine microsatellite markers for population genetic studies on African buffalo (Syncerus caffer). Anim Genet. 1999, 30: 214-220. 10.1046/j.1365-2052.1999.00453.x.View ArticlePubMedGoogle Scholar
  16. Navani N, Jain PK, Gupta S, Sisodia BS, Kumar S: A set of cattle microsatellite DNA markers for genome analysis of riverine buffalo (Bubalus bubalis). Anim Genet. 2002, 33: 149-154. 10.1046/j.1365-2052.2002.00823.x.View ArticlePubMedGoogle Scholar
  17. Kim KS, Min MS, An JH, Lee H: Cross-species amplification of Bovidae microsatellites and low diversity of the endangered Korean goral. J Hered. 2004, 95: 521-525. 10.1093/jhered/esh082.View ArticlePubMedGoogle Scholar
  18. Nguyen TT, Genini S, Menetrey F, Malek M, Vogeli P, Goe MR, Stranzinger G: Application of bovine microsatellite markers for genetic diversity analysis of Swiss yak (Poephagus grunniens). Anim Genet. 2005, 36: 484-489.View ArticlePubMedGoogle Scholar
  19. Moore SS, Evans D, Byrne K, Barker JS, Tan SG, Vankan D, Hetzel DJ: A set of polymorphic DNA microsatellites useful in swamp and river buffalo (Bubalus bubalis). Anim Genet. 1995, 26: 355-359.View ArticlePubMedGoogle Scholar
  20. Nguyen TT, Menetrey F, Genini S, Nguyen VL, Vogeli P, Nguyen BX, Stranzinger G: Application of bovine microsatellite markers on Saola (Pseudoryx nghetinhensis). J Anim Breed Genet. 2005, 122: 195-198. 10.1111/j.1439-0388.2005.00511.x.View ArticlePubMedGoogle Scholar
  21. Edwards CJ, Gaillard C, Bradley DG, MacHugh DE: Y-specific microsatellite polymorphisms in a range of bovid species. Anim Genet. 2000, 31: 127-130. 10.1046/j.1365-2052.2000.00602.x.View ArticlePubMedGoogle Scholar
  22. Ritz LR, Glowatzki-Mullis ML, MacHugh DE, Gaillard C: Phylogenetic analysis of the tribe Bovini using microsatellites. Anim Genet. 2000, 31: 178-185. 10.1046/j.1365-2052.2000.00621.x.View ArticlePubMedGoogle Scholar
  23. Kemp SJ, Hishida O, Wambugu J, Rink A, Longeri ML, Ma RZ, Da Y, Lewin HA, Barendse W, Teale AJ: A panel of polymorphic bovine, ovine and caprine microsatellite markers. Anim Genet. 1995, 26: 299-306.View ArticlePubMedGoogle Scholar
  24. Hassanin A, Ropiquet A: Molecular phylogeny of the tribe Bovini (Bovidae, Bovinae) and the taxonomic status of the Kouprey, Bos sauveli Urbain 1937. Mol Phylogenet Evol. 2004, 33: 896-907. 10.1016/j.ympev.2004.08.009.View ArticlePubMedGoogle Scholar
  25. Verkaar EL, Nijman IJ, Beeke M, Hanekamp E, Lenstra JA: Maternal and paternal lineages in cross-breeding bovine species. Has wisent a hybrid origin?. Mol Biol Evol. 2004, 21: 1165-1170. 10.1093/molbev/msh064.View ArticlePubMedGoogle Scholar
  26. Buntjer JB, Otsen M, Nijman IJ, Kuiper MT, Lenstra JA: Phylogeny of bovine species based on AFLP fingerprinting. Heredity. 2002, 88: 46-51. 10.1038/sj.hdy.6800007.View ArticlePubMedGoogle Scholar
  27. Ellegren H, Moore S, Robinson N, Byrne K, Ward W, Sheldon BC: Microsatellite evolution – a reciprocal study of repeat lengths at homologous loci in cattle and sheep. Mol Biol Evol. 1997, 14: 854-860.View ArticlePubMedGoogle Scholar
  28. Hanotte O, Okomo M, Verjee Y, Rege E, Teale A: A polymorphic Y chromosome microsatellite locus in cattle. Anim Genet. 1997, 28: 318-319.PubMedGoogle Scholar
  29. Laird PW, Zijderveld A, Linders K, Rudnicki MA, Jaenisch R, Berns A: Simplified mammalian DNA isolation procedure. Nucleic Acids Res. 1991, 19: 4293-10.1093/nar/19.15.4293.PubMed CentralView ArticlePubMedGoogle Scholar
  30. Hassanin A, Pasquet E, Vigne JD: Molecular systematics of the subfamily Caprinae (Artiodactyla, Bovidae) as determined from cytochrome b sequences. J Mamm Evol. 1998, 5: 217-236. 10.1023/A:1020560412929.View ArticleGoogle Scholar
  31. Higuchi R: Rapid, efficient DNA extraction for PCR from cells or blood. Amplifications. 1989, 2: 1-3.Google Scholar
  32. The Cattle Diversity Database. [http://www.projects.roslin.ac.uk/cdiv/accessdb.html]
  33. The Cattle Genome Mapping Project database. [http://www.marc.usda.gov/genome/genome.html]
  34. The BOVMAP database. [http://locus.jouy.inra.fr/cgi-bin/bovmap/intro2.pl]
  35. The Microsatellite Toolkit. [http://animalgenomics.ucd.ie/sdepark/ms-toolkit/]
  36. Nei M: Estimation of Average Heterozygosity and Genetic Distance from a Small Number of Individuals. Genetics. 1978, 89: 583-590.PubMed CentralPubMedGoogle Scholar
  37. Guo SW, Thompson EA: Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics. 1992, 48: 361-372. 10.2307/2532296.View ArticlePubMedGoogle Scholar
  38. Raymond M, Rousset F: GENEPOP: population genetics software for exact tests and ecumenicism. J Hered. 1995, 86: 248-249.Google Scholar
  39. Botstein D, White RL, Skolnick M, Davis RW: Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 1980, 32: 314-331.PubMed CentralPubMedGoogle Scholar
  40. Hishida O, Hanotte O, Verjee Y, Tanaka K, Namikawa T, Teale A, Rege JEO: Crossspecies amplification and polymorphism of microsatellite loci in Asian bovidae. Proceedings of the 8th AAAP Animal Science Congress: 13–18 October 1996; Tokyo, Japan. 1996, Japanese Society of Zootechnical Science, 354-355.Google Scholar

Copyright

© Nguyen et al; licensee BioMed Central Ltd. 2007

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.