Ultra-small SNP panels to uniquely identify individuals in thousands of samples

Context. Genomic profiles are the only information source that can uniquely identify an individual but have not yet been strongly considered in the context of paddock to plate traceability due to the lack of value proposition. Aim. The aim of this study was to define the minimum number of single nucleotide polymorphisms (SNP) required to distinguish a unique genotype profile for each individual sample within a large given population. At the same time, ad hoc approaches were explored to reduce SNP density, and therefore, the size of the dataset to improve computing efficiency and storage requirements while maintaining informativeness to distinguish individuals. Methods. Data for this study included two datasets. One included 78 411 high-density SNP genotypes from commercial Angus cattle and the other 2107 from a research data (1000-bull genome data). In a stepwise approach, different-size SNP panels were explored, with the last step being a successive removal resulting in the smallest set of SNPs that still produced the maximum number of unique genotypes. Key results. First study that has demonstrated for large datasets, that ultra-small SNP panels with 20-23 SNPs can generate unique genotypes for up to similar to 80 000 individuals, allowing for 100% matching accuracy. Conclusions. Ultra-small SNP panels could provide an efficient method to approach the large-scale task of the traceability of beef products through the beef supply chain.