Aim: To assess the reproductive performance and managemental advantages of Artificial Insemination of swine. Materials and Methods:Large White Yorkshire sows were grouped into two batches (10 each) for AI and natural mating. AI 9 group was given two inseminations with semen extended with Beltsville Thawing Solution (BTS,3 x 10 spermatozoa per dose), at standing heat. Similarly, for natural mating group, triple mating was followed. The reproductive performance was studied after maintaining the sows under optimal managemental conditions. Results:The results indicated that AI and natural mating practices showed 100% conception rate. The litter size of AI group was 8.36±0.28 and that of the natural mating group was 10.6±0.64, that varied with high significance. The still birth rate was 0.7±0.26, which was significantly higher in natural mating group. The pre-weaning mortality was 4.34% and 7.5% for AI group and natural mating group respectively. The time consumed during mating per sow also varied highly significantly which was 11.46±0.47 minutes and 51.2±2.08 minutes for the AI group and natural mating group respectively. Conclusion:It was found that AI was found to be time and labor saving. The reduced litter size in AI group could be improved by ensuring that inseminations occur at an optimum time resulting in a high farrowing rate and litter size. AI can be successfully introduced in field conditions with some fine tuning.

Aim:The present study was thus undertaken to analyze the genetic diversity of Kilakarsal and Vembur sheep breeds using single-nucleotide polymorphism (SNP) markers within Toll-like receptor (TLR) 3, 5, 6, 9, and 10 genes.Materials and Methods:Competitive allele-specific polymerase chain reaction (PCR)-based end-point genotyping was performed using real-time PCR to type the SNPs. Allele discrimination module implemented in real-time PCR was utilized to call the genotypes based on fluorescence intensity recorded for each of the two alleles. Basic diversity indices, namely, gene frequencies, observed heterozygosity, expected heterozygosity, and inbreeding coefficient (FIS), and testing for Hardy–Weinberg equilibrium (HWE) were estimated using package for elementary analysis of SNP data software program.Results:Of the 25 SNPs, 22 were found to be polymorphic, whereas two SNPs, namely, TLR3_1081_AC and TLR9_2036_CT, were monomorphic in both Kilakarsal and Vembur sheep populations. The SNP TLR10_1180_AG was monomorphic in Kilakarsal but polymorphic in Vembur sheep. The observed heterozygosities were estimated as 0.289 and 0.309 in Kilakarsal and Vembur sheep, respectively, whereas the expected heterozygosity values were 0.305 and 0.309 in the two breeds, respectively. The overall mean FIS was 0.107 ranging from −0.005 to 0.241 in Kilakarsal sheep and −0.047 ranging from −0.005 to 0.255 in Vembur sheep. In Kilakarsal sheep, the test for HWE revealed TLR9_1308_GC SNP locus with significant deviation (p<0.05) due to heterozygosity deficit. In Vembur sheep, TLR10_82_CT and TLR10_292_CG loci showed significant deviation (p<0.05) due to heterozygosity excess. Other SNP loci did not deviate from HWE (p>0.05) revealing that the population was in HWE proportions.Conclusions:The SNP markers within five TLR genes (TLR3, TLR5, TLR6, TLR9, and TLR10) utilized for genotyping in this study were highly polymorphic in Kilakarsal and Vembur breeds of sheep. This study on the genetic diversity analysis of the Kilakarsal and Vembur sheep breeds revealed considerable genetic variation within the breeds and it can be utilized to improve desirable traits.

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