Single nucleotide polymorphism (SNP) high-density chips are now serving as important bioinformatics tools for improvement and development of various livestock species. Major constraint being the high cost of protocol which is not feasible at the population level. Hence, in the present study, we have tried to reduce the SNP panel to a fewer number of informative markers which will be very much cost-effective. The 50K Illumina BeadChip genotypic data obtained from online Dryad repository for six indigenous cattle breeds, namely Tharparkar, Hariana, Red Sindhi, Sahiwal, Gir and Kankrej were merged with three exotic breeds mainly used in Indian condition, i.e., Holstein-Friesian, Jersey and Brown Swiss. Various quality parameters (MAF-0.36, hwe-0.001, geno-0.95) and statistical operations (FST, LD values) were applied by different bioinformatics tools. Later, best possible SNPs with an average FST value of >0.8 were analysed using STRUCTURE 2.3.4 software and we have found perfect clustering among the nine breeds comprising a total of 536 SNPs referring to 158 individuals from nine breeds. Later, breed-specific SNPs were filtered from the set of 536 SNPs using Venny 2.1.0 software.