Molecular Identification of Indian Bovine Genetic Resources through Cox Gene-Based Barcode and QR Code

Objective: The objective of this study was to map Indian Bovine species based on DNA Barcoding and Big data analytics. Methods: 5 Indian Bovine species blood samples were collected and performed molecular study. The whole DNA was isolated and the mitochondrial CoX gene was amplified in each species using Universal primers. The generated sequences were submitted to the BOLD Database to generate DNA Barcodes. The data was examined by the database and the respective DNA Barcodes were generated. Based on DNA Barcodes, using Python code, unique QR codes were generated. Further, based on the Morphological features, molecular features, DNA Barcodes, QR codes, and image data analysis were performed. Results: The isolated DNA was validated using Agarose Gel Electrophoresis. The PCR conditions for mitochondrial CoX gene amplification were standardized and purified followed by DNA Sequencing. 5DNABarcodes for Indian Bovine species were generated and uploaded to the BOLD database. QR codes were generated and Bid data analysis was performed using models for authenticated identification of Bovine species. Conclusion: In conclusion, the molecular mapping of Indian bovine genetic resources using DNA-based techniques such as bar coding, QR code technology, and big-data analysis provides a powerful framework for understanding and conserving the genetic diversity of bovine populations in India. The integration of DNA barcoding enables precise identification and classification of bovine breeds, while QR code technology offers an ovel and efficient means of tracking and monitoring genetic data in real time. The application of big-data analysis further strengthens the ability to detect patterns of genetic variation, assess breed composition, and identify areas of genetic erosion or introgression, which are crucial for breed conservation and improvement programs.