Characterization of Krishna Valley breed of cattle (Bos indicus) in south India using microsatellite markers

S M K Karthickeyan, R Saravanan and P Thangaraju

Department of Animal Genetics and Breeding, Madras Veterinary College, Chennai - 600 007, Tamil Nadu, India
kannikarthi@yahoo.co.in

Abstract

With the help of 25 microsatellite markers, a total of 50 Krishna Valley cattle were screened.

The mean number of alleles was found to be 4.72 ± 0.25 per microsatellite locus with the range of 3 to 7. The range in the allele size was from 94 (CSRM060) to 300 (ILSTS006) bp. These microsatellite alleles distributed at a minimum frequency of 0.0116 (ILSTS054) to a maximum of 0.8128 (ILSTS030). The mean polymorphism information content was found to be 0.6209 ± 0.03 ranging from 0.2583 (ILSTS030) to 0.7975 (INRA035). The overall means for observed and expected heterozygosities were 0.6683 ± 0.06 and 0.6569 ± 0.03 respectively.

The markers used in the study were highly informative and the high heterozygosity value is indicative of the higher amount of genetic variability that can be exploited even in populations of small size.

Keywords: Allele frequency, cattle, Krishna Valley, microsatellites, PIC

Introduction

KrishnaValley is the draught breed of cattle, braving extreme hot, humid climatic conditions and is able to work well in the black cotton soil in the valleys of Krishna river in Karnataka state in India. It was reported that the kings of Southern Mahratta country, in the watershed areas of the rivers Krishna, Ghataprabha and Malaprabha, tried to evolve a powerful bullock for agricultural purposes in the sticky black cotton soil during the last two decades of the nineteenth century (Joshi and Phillips 1953). It was claimed that Gir and possibly Kankrej cattle from Gujarat state, Ongole cattle from Andhra Pradesh state and local cattle having Mysore-type blood were used to evolve the Krishna Valley breed. The king of Sangli, a well-known breeder of Krishna Valley, contributed substantially in making judicious use of all these strains to produce the desired type of animal.

Earlier, the distribution of Krishna Valley cattle was wide, including the districts of Satara, Sangali and Solapur in Maharashtra; and Belgaum, Bijapur and Raichur districts of Karnataka states (Nivsarkar et al 2000). But a shift in the breeding tract of this breed from Maharashtra and Karnataka states to northern Karnataka alone was reported in a pilot survey conducted by Ramesha et al (2001). At present, only a few hundred animals true to type are available in and around few villages of Jamkhandi, Mudhol and Athani taluks of northern parts of Karnataka. The reasons for the decline in number are selling of animals of Krishna Valley due to continuous drought in the tract and preference of the farmers for Khillari breed which is more attractive and massive in appearance resulted in lack of Krishna Valley breeding bulls.

The first step towards conservation of livestock genetic resources is the genetic characterization with respect to phenotypic parameters, unique qualities and utility. Subsequently finding out the genetic architecture through molecular means and evolutionary relationship with other related breeds would provide valuable information about the breed for taking up conservation measures. The physical characterization had already been done by Ramesha et al (2001) in the native tract. Considering these facts, the present study has been carried out to characterize the Krishna Valley breed of cattle using the molecular markers, such as microsatellites.

Materials and methods

DNA samples

The microsatellite analysis was carried out in a sample of 50 unrelated Krishna Valley cattle reared in the villages of Jamkhandi Taluk (part of its breeding tract) in Karnataka State, India. The samples were collected at random form different villages of the tract. The DNA for the study was isolated from peripheral blood by a rapid, non-enzymatic method as described by Lahiri and Nurnberger (1991). The quantity and quality of the isolated DNA samples were tested by spectrophotometric measurements for subsequent analysis.

Microsatellite analysis

As per the secondary guidelines of Food and Agriculture Organisation of United Nations (FAO 2004), a total of 25 microsatellite markers were selected to screen the population of Krishna Valley cattle. The amplification of DNA was carried out using thermal cycler (MJ Research) with the PCR reaction mixture of 20ml. The mixture was prepared by adding 50-100ng of template DNA; 1.5mM MgCl₂; 5 picomoles each of forward and reverse primers; 0.75 units of Taq DNA Polymerase and 100mM dNTPs. Amplification was carried out with annealing temperatures ranging from 51°C to 60°C for different primers for 30 cycles. Amplified PCR products were resolved through a 6% denaturing PAGE along with a single stranded 10 bp DNA ladder (Invitrogen, USA) as marker and the PCR products were sized after silver-staining procedure as recommended by Comincini et al (1995).

The microsatellite alleles were sized using Diversity Database software (BioRad, USA) and followed by manual verification. Effective number of alleles, allele frequencies and heterozygosity were estimated using the software POPGENE 32. The polymorphism information content (PIC) was analysed using Nei's formula (1978).

Results and discussion

The percentage of polymorphic loci obtained was 96 since all microsatellite loci, except ILSTS030 (only 2 alleles), screened in Krishna Valley cattle exhibited polymorphism. The microsatellite allele number, size and frequency, polymorphism information content and heterozygosity values are presented in Table 1.

Microsatellite alleles

The mean number of alleles was found to be 4.72 ± 0.25 per microsatellite locus. The number of alleles was in the range of 3 to 7. These polymorphic loci generated a total of 118 alleles in the breed. In general, the number and sizes of microsatellite alleles observed in this study fall within the range mentioned in the Secondary Guidelines for Development of National Farm Animal Genetic Resources Management Plans, published by FAO (2004). The mean number of alleles observed in the study is less than that reported in other Indian breeds of cattle such as Sahiwal (5.2) and Deoni (5.9) (Mukesh et al 2004) using the same microsatellites; and more than the averages for Ongole (4.5) and Deoni (4.1) cattle for different set of markers (Metta et al 2004). The allele sizes observed for the loci ILSTS005, ILSTS006, ILSTS011 and ILSTS033 are in accordance with the sizes reported for Bos taurus cattle (Kemp et al 1995) and Spanish native cattle breeds (Martin-Burriel et al 1999).

The frequencies of microsatellite alleles in some representative loci are shown in figure 1.

The allele sizes were ranging from 94 (CSRM060) to 300 (ILSTS006) bp. These microsatellite alleles occurred at a minimum frequency of 0.0116 (140 bp allele in ILSTS054) to a maximum of 0.8128 (152 bp allele in ILSTS030). Apart from 152 bp allele, 194 bp allele in ETH152 locus occurred at higher frequency of 77 per cent. This is followed by 262 bp allele in ILSTS011 (70 per cent), 178 bp allele in CSSM066 (50 per cent), 260 bp allele in BM 1818 and 116 bp allele in ETH003 (49 per cent).

Polymorphism information content (PIC)

The statistical assessment of informativeness of a marker, as denoted by PIC value, was ranging from 0.2583 (ILSTS030) to 0.7975 (INRA035) with a mean PIC value of 0.6209 ± 0.03. The high polymorphism information contents noticed in this study are in agreement with Belgian cattle breeds for loci ETH003, ETH010, ETH225 and BM1818 (Peelman et al 1998). The PIC values observed in most of the loci are comparable with those observed in other Indian cattle breeds such as Deoni, Hariana and Sahiwal. The PIC values for loci ILSTS005 (0.6954), ILSTS011 (0.4140) and ILSTS033 (0.7036) were slightly different from the PIC (0.59, 0.67 and 0.77 respectively) reported by Kemp et al (1995) in cattle while ILSTS006 locus had similar PIC value (0.72). Except ILSTS030 and ETH152, all other loci possessed high PIC values indicating that these markers are highly informative for characterization of Krishna Valley cattle.

Hardy-Weinberg equilibrium

The Chi-square (c²) test for Hardy-Weinberg equilibrium revealed that except in 7 loci (ILSTS005, ILSTS006, ILSTS030, ETH152, HEL001, INRA063 and HAUT027), the Krishna Valley population was not in equilibrium. The disequilibrium proportion observed in the population is attributed to the existence of null alleles, inherently high mutation rate of microsatellites and size homoplasy of loci, besides small population size as a result of shrinkage of breeding tract and availability of lesser number of bulls.

Within-population genetic variability

The overall means for observed and expected heterozygosities were 0.6683 ± 0.06 and 0.6569 ± 0.03 respectively with the ranges of 0.0930 (ETH225) to 1.000 (ETH003, INRA035 and BM2113) and 0.3047 (ILSTS030) to 0.8220 (INRA035). The mean expected heterozygosity value is comparable to that of Sahiwal (0.61), Hariana (0.66) and Deoni (0.70), the other Indian cattle breeds studied by Mukesh et al (2004). Though few loci exhibited lower heterozygosity values, majority of the loci had relatively higher expected heterozygosity, which reflects the existence of variation in spite of declining number of Krishna Valley in the breeding tract.

The high heterozygosity values observed indicate more number of polymorphic loci in Krishna Valley cattle. This implies the higher amount of genetic variability that can be exploited even in population of small sizes.

Conclusions

• A large number of polymorphic loci was revealed in Krishna Valley breed with respect to 25 microsatellite markers screened in the study.

• The overall mean polymorphism information of 62 per cent suggests that these markers are highly informative for characterization of Krishna Valley breed. It also opens up the scope for exploiting the genetic variability in the population for conservation.

• Detailed studies on comparative analysis with other Indian draught cattle breeds will determine the genetic distance and relationship of Krishna Valley breed.

Acknowledgements

We express our sincere gratitude to the National Bureau of Animal Genetic Resources, Karnal for the financial support through the ICAR Network Projects - Core Laboratory.

References

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Received 9 September 2006; Accepted 21 September 2006; Published 6 December 2006

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