Ovine SNP Genotyping for Pre-Slaughter Meat Quality Selection
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Solution Overview
Problem
Existing methods for measuring intramuscular fat (IMF), fat melting point (FMP), and omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) in sheep meat are inaccurate and can only be determined post-slaughter, leading to inefficiencies and wastage in livestock industries.
Innovation Solution
A SNP-based diagnostic test that utilizes minimally invasive muscle biopsy sampling and next-generation sequencing (NGS) to identify functional SNPs associated with desirable meat-eating quality traits, such as IMF, FMP, and n-3 LC-PUFA, in live ovine animals, particularly Tattykeel Australian White sheep, for use in breeding programs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laboratory-based fat extraction, slip point and gas chromatography methods are used, then measurement accuracy of IMF, FMP and n-3 LC-PUFA is improved, but measurement time and cost increase, and selection decisions must be made post-slaughter
Solution Approach 1:
The patent applies preliminary action by performing SNP genotyping on live animals before slaughter to predict meat quality traits. This allows selection decisions to be made in advance based on genetic markers associated with IMF, FMP, and n-3 LC-PUFA, eliminating the time loss of waiting for post-slaughter analysis while maintaining prediction accuracy through validated genetic markers.
Solution Approach 2:
The patent replaces the mechanical/chemical measurement system (fat extraction, slip point, gas chromatography) with a molecular biology-based genetic testing system. By substituting direct chemical analysis with SNP genotyping and predictive modeling, the system achieves comparable measurement accuracy while enabling pre-slaughter selection, thus resolving the time loss contradiction.
2Productivity
If near infra-red based regression equations are used to predict IMF and composition characteristics, then measurement speed is improved, but measurement accuracy and consistency deteriorate
Solution Approach 1:
The patent replaces the optical measurement system (near infra-red spectroscopy) with a molecular biology-based SNP genotyping system. This substitution maintains the speed advantage of non-destructive testing while improving prediction accuracy by using validated genetic markers with known associations with meat quality traits, eliminating the inconsistency and low accuracy of NIR methods.
Solution Approach 2:
The patent changes the measurement parameter from optical properties (NIR reflectance) to genetic markers (SNP genotypes). This parameter change enables both rapid measurement (through high-throughput genotyping) and high accuracy (through validated marker-trait associations), resolving the contradiction between productivity and measurement precision.
3Loss of information
If visual marbling score and meat imaging camera marbling systems are used, then post-slaughter assessment capability is improved, but precision and accuracy deteriorate
Solution Approach 1:
The patent applies preliminary action by assessing genetic potential for marbling (IMF deposition) in live animals through SNP genotyping before slaughter. This provides meat quality information in advance, eliminating the loss of information for breeding decisions while avoiding the precision limitations of visual and imaging camera assessments through the use of validated genetic markers.
4Productivity
If selection for lean meat yield is pursued, then productivity is improved, but meat eating quality deteriorates
Solution Approach 1:
The patent applies local quality by enabling independent selection for different traits through separate SNP markers. Breeders can simultaneously select for lean meat yield (through growth and composition markers) and maintain eating quality (through IMF, FMP, and fatty acid composition markers) by making coordinated selection decisions based on multiple genetic parameters rather than prioritizing one trait.
Solution Approach 2:
The patent creates a universal genetic testing system that assesses multiple meat quality traits (IMF, FMP, n-3 LC-PUFA, lean meat yield) simultaneously through SNP genotyping. This multi-functional approach allows breeders to optimize for both productivity and eating quality together, eliminating the trade-off by providing comprehensive genetic evaluation in a single testing framework.
Data Source
AI summary
The present disclosure relates generally to methods and test kits for identifying SNPs associated with desirable meat eating quality traits in ovine animals. In particular, the present disclosure relates to a SNP-based diagnostic test and method for identifying ovine animals with desirable fat melting point (FMP), intramuscular fat (IMF) and omega-3 long chain polyunsaturated fatty acids (n-3 LC PUFAs) which are characteristic of Australian White sheep or Lamb (e.g., Tattykeel Australian White Lamb), and the use of those tests and methods in animal breeding programs.