CRISPR Allele Combinations for High Throughput Phenotypic Testing
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Solution Overview
Problem
Current methods for improving agronomic traits in elite plant varieties face challenges in generating new genetic diversity and identifying effective combinations of mutations, as they often result in massive genetic changes and require laborious isolation and evaluation processes, with limited success in incorporating favorable alleles and synergistic effects.
Innovation Solution
The method involves selecting genomic targets, designing gRNAs to mutate these targets, and using the CRISPR/Cas system to introduce germline mutations in plants, followed by sexual crossing to identify combinations of mutations that enhance phenotypic traits such as yield, stress tolerance, and efficiency, within a uniform elite genetic background.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If random mutagenesis or wide crosses are used to generate new genetic diversity, then genetic variation is increased, but the process becomes laborious and requires massive changes of genetic material with limited success in identifying favorable allele combinations
Solution Approach 1:
The patent applies preliminary action by pre-selecting candidate loci based on prior knowledge (QTL mapping, association studies, homology to other species) before conducting mutagenesis. This focuses the mutagenesis effort on specific genomic regions most likely to contain favorable alleles, rather than random mutagenesis across the entire genome, thereby increasing the efficiency of identifying beneficial mutations while maintaining elite genetic background
Solution Approach 2:
The patent implements local quality by applying mutagenesis selectively to specific candidate loci rather than uniformly across the genome. Each candidate locus is targeted with mutagenesis based on its potential to improve specific agronomic traits, allowing concentrated effort on high-priority regions while preserving the rest of the elite genetic background
2Reliability
If saturation mutagenesis of multiple candidate loci is performed, then the likelihood of identifying synergistic allele combinations increases, but the complexity of managing and testing large populations increases
Solution Approach 1:
The patent applies segmentation by dividing the candidate loci into discrete targets and using independent mutagenesis of each locus. This allows systematic combination of mutations across multiple loci in a structured manner, making it feasible to manage and track specific allele combinations through sexual crossing and population testing, thereby identifying synergistic effects without overwhelming complexity
Solution Approach 2:
The patent implements universality by using a standardized mutagenesis platform (e.g., CRISPR/Cas9 or other targeted mutagenesis systems) that can be applied uniformly across multiple candidate loci. This universal approach enables consistent generation of mutations at different loci using the same methodology, simplifying the management and comparison of resulting populations
3Quantity of substance
If traditional breeding methods are used to incorporate new alleles, then genetic material changes are massive and require many backcrosses, but this results in loss of elite genetic background and requires laborious isolation and evaluation processes
Solution Approach 1:
The patent applies the taking out principle by extracting and mutating only the specific candidate loci of interest within the elite genetic background, rather than introducing entire foreign genomes through wide crosses. This selective approach allows incorporation of new alleles at specific locations while preserving the rest of the elite background, eliminating the need for multiple backcrosses and reducing breeding cycle time
Solution Approach 2:
The patent implements parameter changes by using targeted mutagenesis to induce specific genetic changes at candidate loci rather than relying on random mutations or large-scale genomic changes. This precise control over genetic modification parameters enables efficient allele incorporation while maintaining the elite genetic background, significantly reducing the time and labor required compared to traditional breeding
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for high-throughput identification of combinations of mutations that improve agronomic traits, increasing the likelihood of additive or synergistic effects, reducing the need for backcrosses, and enabling the testing of large numbers of mutations in elite genetic backgrounds, leading to more efficient and reliable results.
Implementation Method 1
making a plant cell that has both gRNAs designed to mutate the selected genomic targets and a Cas polypeptide, so that a plant descended from the plant cell will have germline mutations
Data Source
AI summary
High throughput methods are described for identifying combinations of mutations that can be used to improve a phenotypic feature in an organism. Large populations of organisms (e.g., plants) containing different combinations of mutations can be assessed using the methods.