Multi-parent Genomic Selection for Crop Trait Improvement
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Solution Overview
Problem
Current genomic selection methods in plant and animal breeding primarily focus on selecting individual parents based on their genome-wide estimated breeding values, overlooking the long-term impact of allele combinations, which can limit genetic improvement by missing opportunities for introducing favorable alleles from other parents.
Innovation Solution
The method involves selecting combinations of at least three individuals based on Combined Genome-Wide Estimated Breeding Values, considering recombination probabilities to identify subsets that can produce the best performing offspring by combining complementary haplotypes, thereby enhancing genetic diversity and improving phenotypic traits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional genomic selection focuses on selecting individual parents based on their genome-wide estimated breeding values, then the selection process is simple and computationally efficient, but the long-term genetic improvement is limited due to missing opportunities for introducing favorable alleles from other parents
Solution Approach 1:
The patent merges the selection of multiple parents (at least three) into a single integrated selection unit rather than selecting individuals independently. This combining approach allows the system to evaluate and select parent combinations that collectively provide superior allele diversity and complementary haplotypes, thereby accelerating long-term genetic improvement while managing complexity through unified evaluation metrics.
Solution Approach 2:
The patent transitions from one-dimensional individual selection (based on single parent GEBV) to multi-dimensional combination selection (evaluating parent sets based on combined GEBV, allele diversity, and haplotype complementarity). This dimensional expansion enables capturing synergistic effects among multiple parents that cannot be achieved through individual selection alone.
2Measurement precision
If combinations of at least three individuals are selected based on Combined Genome-Wide Estimated Breeding Values considering recombination probabilities, then the genetic improvement and phenotypic trait enhancement are significantly improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary calculations of Combined Genome-Wide Estimated Breeding Values and recombination probabilities for all possible parent combinations before final selection. This advance computation allows the system to pre-evaluate the genetic potential of combinations, storing intermediate results that can be efficiently queried during the selection process, thereby reducing real-time computational burden while maintaining high prediction accuracy.
Solution Approach 2:
The patent introduces Combined Genome-Wide Estimated Breeding Value as an intermediary metric that aggregates complex genetic information from multiple parents into a single evaluative measure. This intermediary metric serves as a bridge between detailed genomic data and final selection decisions, simplifying the comparison of different parent combinations while preserving the underlying genetic complexity needed for accurate prediction.
Data Source
AI summary
The present invention provides a method for improving at least one phenotypic trait of interest in subsequent generation(s) of a population of individuals, preferably crop plants or cattle. Particularly, the method identifies the combination of at least three individuals that gives, upon subsequent intercrossing, the highest estimated probability of improving the at least one phenotypic trait of interest in the subsequent generation(s). Also provided is a computer-readable medium comprising instructions for performing the method.