2022 Fiscal Year Final Research Report
Genome prediction method for identifying agronomic trait genes and gene networks using rice NAM population
| Project/Area Number |
20H02962
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 39010:Science in plant genetics and breeding-related
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| Research Institution | Iwate Biotechnology Research Center |
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Principal Investigator |
Abe Akira 公益財団法人岩手生物工学研究センター, ゲノム育種研究部, 主席研究員 (80503606)
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| Co-Investigator(Kenkyū-buntansha) |
石川 和也 公益財団法人岩手生物工学研究センター, ゲノム育種研究部, 研究員 (40804703)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | Genomic prediction / rice / NAM population / Gene-Gene interaction / G x E interaction / Epistasis |
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| Outline of Final Research Achievements |
We developed a novel model to detect epistatic interaction using recombinant inbred lines (RILs) and released an R package RIL-StEp. We identified a region on Chr.11 that is associated with grain number per panicle and has an epistatic relationship with the FZP region. A candidate gene was identified by RNA-seq analysis. We found that FZP represses the expression of the candidate gene and identified the possibility that polymorphisms in the promoter sequences of the candidate gene are involved in the epistatic effect.
A genomic prediction model was constructed using the NAM population to accurately predict agronomic traits from genotypes. The model achieved high prediction accuracy (correlation coefficient of 0.9 or higher) for leaf width, number of grains per panicle, number of panicles, and grain size. Furthermore, the model was able to predict traits with high accuracy even in lines in which the genomes of multiple varieties had been introduced through crosses.
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| Free Research Field |
Plant genetics, Plant breeding
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| Academic Significance and Societal Importance of the Research Achievements |
イネにおける量的形質の変動の原因となる遺伝子とそれらネットワークを理解することは重要な課題である。本研究の成果は、イネの収量性に直結する穂の着粒構造の遺伝的改良に寄与するものである。構築したゲノミック予測モデルは、極めて精度が高く、イネのみならず多様な作物におけるゲノミック選抜に波及することが期待できる。また、目的とする形質が予測されるゲノムをデザインし、そのゲノムを交配等で再現する「ゲノムデザイン育種」への端緒となるものである。
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