Optimal Haploid Value Selection for Elite Line Creation
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Solution Overview
Problem
Current plant breeding methods, such as genomic selection, face limitations in selecting optimal haplotypes for doubled haploids due to sparse marker maps and linkage phase uncertainty, leading to reduced genetic gain and diversity over multiple generations.
Innovation Solution
The implementation of optimal haploid value (OHV) selection, which determines the best combination of genome segments for breeding pairs, allowing for the selection of elite doubled haploids that combine the highest predicted haploid genome segment values, thereby increasing genetic gain and diversity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional genomic selection is used with sparse marker maps, then the method is simpler and less costly, but the selection precision and genetic gain are reduced due to linkage phase uncertainty
Solution Approach 1:
The patent segments the genome into haplotype blocks defined by dense marker maps, allowing precise tracking of chromosomal segments through generations. This segmentation enables accurate determination of linkage phase and haplotype inheritance patterns, directly improving selection precision without requiring entire genomes to be analyzed as single units
Solution Approach 2:
The patent performs preliminary action by establishing dense marker maps and determining linkage phase in advance before selection events occur. Reference populations are genotyped and analyzed beforehand to create prediction equations that can be applied to subsequent breeding populations, eliminating the need for real-time complex analysis during selection decisions
2Productivity
If selection based on overall GEBV is applied to maximize genetic gain in the next generation, then short-term genetic gain is improved, but genetic diversity is lost and long-term gains are limited
Solution Approach 1:
The patent segments the genome into independently selectable haplotype blocks rather than selecting entire genomes based on overall GEBV. This allows breeders to select for specific beneficial chromosomal segments while maintaining other segments that contribute to genetic diversity, enabling simultaneous improvement of genetic gain and preservation of adaptability
Solution Approach 2:
The patent applies local quality by evaluating and selecting individual haplotype blocks based on their specific contribution to trait variation rather than relying on overall genomic estimated breeding values. This localized selection approach allows optimization of specific genomic regions while preserving diversity in other regions, balancing short-term gain with long-term adaptability
3Measurement precision
If phenotypic selection with progeny testing is used to choose the best doubled haploid, then selection accuracy is improved, but the breeding cycle time and cost increase significantly
Solution Approach 1:
The patent performs preliminary action by determining haplotype values and predicting doubled haploid performance using genomic data before actual phenotypic expression occurs. Prediction equations are developed in advance using reference populations, allowing selection decisions to be made at the seedling stage rather than waiting for mature plant phenotyping and progeny testing
Solution Approach 2:
The patent replaces the mechanical system of physical phenotypic measurement and progeny testing with a genomic-based prediction system. DNA markers and haplotype analysis substitute for time-consuming field phenotyping, enabling accurate selection predictions to be made in the laboratory rather than through lengthy field trials
Data Source
AI summary
This disclosure concerns methods for estimating the breeding value of plants for the purpose of producing doubled haploid, for example, to identify selection candidates having high breeding values.