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Updated: Jun 13, 2026

Breeding by Design for Functional Rice with Genome Editing Technologies
Published on: January 3, 2025
A fast method for breeding by design via G × E interactions detected in large-scale climatic, phenomic and genomic
Jing-Tian Wang1, Xue-Lian Han1, Miao-Miao Zhao1
1College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
None:
Although large-scale populations are used to detect genes for polygenic traits, few studies integrate genes and gene-by-environment interactions (GEIs) into breeding by design. Here, we present Fast3VmrMLM, which uses eight big-data techniques to analyze climatic, phenomic and genomic data together to detect GEIs, decipher plasticity and guide breeding. In multi-environment joint analysis (MEJA) of maize, rice and soybean datasets, a total of 396 known genes and 84 known GEIs validated Fast3VmrMLM. In a 12-environment maize dataset, six GEIs interacting with five meteorological factors and two MEJA-detected GEIs helped to explain flowering time plasticity. Thirteen known genes, eight known GEIs and seven plasticity genes advanced flowering by 1.10-6.61 days, whereas nine known genes, one known GEI and three plasticity genes increased yield by 0.51-3.56 Mg·ha-1, identifying 15 high breeding potential hybrids and 29 genes. By incorporating single nucleotide polymorphisms, haplotypes and structural variations, Fast3VmrMLM offers a big-data platform for identifying GEIs and developing climate-adaptive cultivars.
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