Genetic Structure and Differentiation of Different Strains of Nellore Sheep

The aim of present study was to assess the genetic diversity, genetic distance and establish genetic relationship between Palla, Jodipi, Nellore Brown and Macherla brown strains of Nellore sheep breed from their breeding tracts in Andhra Pradesh, India based on 24 ovine specific microsatellite markers so as to support breed conservation and improvement decisions. All used microsatellites were amplified well and exhibited polymorphism. A total of 200 unrelated DNA samples from Palla, Jodipi, Nellore brown and Macherla brown strains of Nellore sheep breed were genotyped to find out within and between strain genetic diversity indices. The mean number of alleles (11.71); effective number of alleles (8.74) reflected the existence of substantial amount of diversity among the strains. The mean value of Shannon index is 2.25, which clearly indicates high gene diversity within populations. Observed and expected heterozygosity in the populations were found to be 0.35 and 0.88 respectively. The mean estimates of FIS, FST and FIT were 0.890, 0.039 and 0.895 respectively. The Nei’s standard and D-genetic estimates using UPGMA method revealed low genetic distance and high genetic identity among the strains of Nellore sheep. All the four strains were genetically distinct and divided into three clusters with low degree of admixture at k = 4 based on Structure analysis. Ewans-Watterson test was conducted to test the neutrality of microsatellites. The rate of gene flow (Nm) between different strains of Nellore sheep was found to be 5.72.

There are forty two indigenous breeds of sheep in India reared for meat and wool which play an important role in the biodiversity and livelihood of a large proportion of small and landless labourers. Nellore sheep is a tallest and best mutton producing breed of India known for heat tolerance, disease resistance and thrives well in harsh conditions. There are different strains of Nellore sheep distributed in Nellore, Chittoor, Kadapa, Kurnool, Anantapur, Prakasam, Guntur, Krishna and other north coastal districts of Andhra Pradesh. Considering the importance of meat in the area in which it is located, efforts have been initiated to conserve different strains of Nellore breed of sheep at molecular level using microsatellites to understand the genetic structure, relationship and differentiation in between them which will be helpful for the breeders to formulate breeding strategy for the improvement of the breed.

Sampling and PCR based profiling
A total of 50 number blood samples were collected from each strain of Nellore sheep unrelated by ancestry from their home tract and genomic DNA was isolated as per the standard procedure of Sambrook and Russell (2001). A total of 24 microsatellite markers chosen randomly from the list recommended by FAO were amplified using a thermal cycler with a PCR reaction mixture (25μ1) containing 25 mM Mgcl 2 , 10mM dNTPs, 10x buffer, 60 pM of each primer, 50 ng of template DNA and 1 unit of Taq DNA polymerase. The PCR products were genotyped using 6% denaturing polyacrylamaide gel and then visualized after silver staining. The allele sizes were determined with the help of 50 bp DNA marker. Samples were scored manually either as homo or heterozygote for each loci.

Statistical analysis
Allelic profile was calculated using the POPGENE 1.31 software version (Yeh et al., 1999). Shannon index was calculated for determining diversity index (Shannon and Weaver, 1949). Polymorphism information content was calculated using PIC calculator. Nei's genetic distance was calculated using UPGMA method. Genetic structure and the degree of admixture of four sheep populations were studied using the Bayesian clustering procedure of STRUCTURE ver.2.3 (Pritchard et al., 2000). Ten independent runs for each 'K' value ranging from 2 to 10 were carried out to identify the most probable 'K' value that best fit the data. Structure harvester (Earl and Von Holdt, 2011) which implements the Evanno method (Evanno et al., 2005) was used.

Intra population genetic variation
All the 24 ovine specific microsatellite markers were amplified well and all of them were found to be polymorphic. The observed, effective number of alleles, Shannon's index, observed and expected heterozygosity were presented in Table 1. A total of 281 alleles were observed across all loci in all the four strains studied. The observed number of alleles ranged from 9 (OarCP34, OarVH72) to 16 (OarCP49) with a mean of 11.71 ± 1.92. The effective number of alleles across all the loci ranged from 5.47 (OarVH72) to12 (OarCP49) with a mean of 8.74 ± 1.36. Some of the alleles screened for microsatellite markers were found to be specific to a particular strain with low frequency. 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 strains within a breed. The results were in agreement with those of other sheep breeds in India Pramod et al., 2009;Ramachandran et al., 2015).
The observed heterozygosity for different strains in the present study ranged from 0.11 (OarHH64) to 0.52 (MAF214) with a mean of 0.35. Takezaki and Nei (1996) stated that for markers to be useful for measuring genetic variation, these should have an average heterozygosity ranging from 0.3 to 0.8 in the populations. This again confirmed that these markers were sufficient to measure the genetic variation. The average expected heterozygosity (0.88) was found to be higher than the average observed heterozygosity (0.35) which revealed that the population had retained the presence of several alleles although at lower frequencies.  (OarHH64) across all loci. The highest degree of genetic uniformity between different strains of Nellore sheep was found to be supported by relatively high level of gene flow (6.033) between these strains. The high homogeneity or lack of heterozygotes among these strains might be due to inbreeding or non random mating as evidenced by overall positive F-value. Moreover due to uncontrolled mating in India sheep populations at the farmer level, a breeding group most likely comprises a dominant male generally excludes subordinates males, and presumably sire most of the offspring. In addition, the breeding groups will be expected to be inbred with the unequal sex ratio of breeding animals causing inbreeding to accumulate. Farmers should put efforts to avoid as much as possible, by exchanging rams frequently from other flocks. The results are similar to those reported for other breeds (Dashaba et al., 2011). Nei's standard (D S ) genetic distance and genetic identity (D A ) values showed lowest degree of divergence between the four strains of Nellore breed (Table 3). Nei's original measure of genetic distance was calculated using UPGMA method. The D A based genetic distance values revealed high levels of uniformity between the four strains of Nellore sheep. Neighbour joining tree based on pairwise Nei's genetic distance was presented in Fig. 1. Genetic distance estimates were used to calculate the divergence time ('t' in generation) between the four strains as calculated as D=2αt, whereas 'D' is the standard genetic distance of Nei and 'α' is the assumed mutation rates (1.2×10 -3 ) of microsatellite loci (Weber and Wong, 1993).
Assuming a constant rate of divergence and a generation interval of 3 to 4 years, the estimated time of divergence between Palla with Jodipi, Nellore brown and Macherla brown, Jodipi with Nellore brown and Macherla brown and Nellore brown with Macherla brown based on Nei's genetic distance were 170.42, 124.08, 259.1, 177.50, 146.67 and 139.17 generations (Table 4).  Based on highest 'K' value obtained in the structure analysis according to evanno et al. (2005) revealed that four strains should be divided into three clusters (Fig. 2). From the structure analysis, the true 'K' value obtained is four. i.e., at K = 4, all the four strains were genetically distinct with relatively lower degree of admixture. Nellore brown and Macherla brown were placed in one cluster whereas Palla and Jodipi were grouped in different clusters. Proportion of membership coefficients in each of the inferred clusters with different runs of structure program are presented in Table 5. The strains were clustered based on their geographical location and genetic identity.  (Evanno et al., 2005) Ewens-Watterson test was performed to test the neutrality for microsatellite markers. The F-statistics (sum of squares of allele frequency) and limits (upper and lower) at 95% confidence region for the test were calculated using the algorithm by Manly method utilizing 1000 simulations and implemented in Popgene software. The overall test for neutrality across the four populations revealed that Mean F-values all the loci were within the lower and upper limits of the 95% confidence interval (Table 6).

CONCLUSION
In conclusion the present study is an attempt to understand the genetic structure, diversity and to establish the relationship among different strains of Nellore sheep using microsatellite DNA markers and there is a need of genetic management to reduce the inbreeding and intermixing. Further investigations would be required to clarify the relationship between the strains of Nellore sheep breed of Andhra Pradesh.