Ultra-small SNP panels to uniquely identify individuals in thousands of samples
S. Dominik
A F , C. J. Duff B , A. I. Byrne B , H. Daetwyler C D and A. Reverter E
A CSIRO Agriculture and Food, FD McMasters Laboratories, 9308 New England Highway, Armidale,NSW 2350, Australia.
B Angus Australia, 86 Glen Innes Road, Armidale, NSW, 2350, Australia.
C Agriculture Victoria, AgriBio Centre, 5 Ring Road, Bundoora, Vic. 3083, Australia.
D La Trobe University, Plenty Road and Kingsbury Drive, Bundoora, Vic. 3083, Australia.
E CSIRO Agriculture and Food, Queensland Bioprecinct, 306 Carmody Road, St Lucia, Qld 4067, Australia.
F Corresponding author. Email: sonja.dominik@csiro.au
Animal Production Science 61(18) 1796-1800 https://doi.org/10.1071/AN21123
Submitted: 5 March 2021 Accepted: 29 April 2021 Published: 16 July 2021
Journal compilation © CSIRO 2021 Open Access CC BY-NC-ND
Abstract
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 ~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.
Implications: Genomic tools could enhance supply-chain traceability.
Keywords: supply-chain traceability, provenance, genomics, beef.
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