Genomic Prediction Accuracy via Optimized Estimation Data Sets
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Solution Overview
Problem
Current genomic prediction methods in plant and animal breeding face challenges in achieving high accuracy due to limitations in the relatedness between training individuals and selection candidates, as well as inefficiencies in data utilization.
Innovation Solution
The method involves constructing an optimized estimation data set by selecting candidates for phenotyping based on their genomic estimated breeding value accuracy, which is higher than that of other candidates, and iteratively adding them to the data set until optimized, thereby improving the accuracy of genomic prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional phenotypic selection or marker-assisted selection is used, then the breeding process is simpler, but the accuracy of selection is lower
Solution Approach 1:
The patent performs preliminary genotyping of parents and construction of genomic relationship matrices before phenotypic data is available. This allows the prediction model to be prepared in advance, and phenotypes are only needed to update the prediction, significantly reducing the time and complexity of the breeding process while maintaining high accuracy
Solution Approach 2:
The patent introduces genomic relationship matrices as an intermediary between traditional phenotypic selection and modern genomic selection. This intermediary structure allows the integration of genotypic information from parents with phenotypic data, enabling accurate predictions without requiring extensive phenotypic data collection on all candidates
2Quantity of substance
If all available phenotypes are used in the training data set, then more data is available for estimation, but the accuracy for certain families decreases
Solution Approach 1:
The patent applies local quality by allowing different subsets of phenotypic data to be used for different prediction targets. The system can selectively include or exclude certain families' phenotypes based on the specific prediction needs, ensuring that the training data is optimally matched to the prediction target rather than using a uniform approach for all cases
3Ease of manufacture
If the training data set does not match the prediction target, then data collection is easier, but the accuracy of genomic prediction decreases
Solution Approach 1:
The patent performs preliminary genotyping of parents and construction of population-specific genomic relationship matrices before phenotypic data is available. This allows the prediction model to be tailored to specific prediction targets in advance, ensuring that the training data will be appropriately matched when collected, thereby maintaining high accuracy without complicating the data collection process
Data Source
AI summary
Methods to improve the selection of breeding individuals as part of a breeding program are provided in which optimized estimation data sets are constructed by selecting candidates for phenotyping, for which genotypic information is also available, from a candidate set and inputting them into the estimation data set and then evaluating accuracy of genomic estimated breeding values for each candidate (i.e. genomic prediction accuracy). The optimized estimation data set is then used as a model to determine genomic estimated breeding values of breeding individuals based purely on genotypic information.