Structure and function of rice hybrid genomes reveal genetic basis and optimal performance of heterosis

Exploitation of crop heterosis is crucial for increasing global agriculture production. However, the quantitative genomic analysis of heterosis was lacking, and there is currently no effective prediction tool to optimize cross-combinations. Here 2,839 rice hybrid cultivars and 9,839 segregation indi...

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Veröffentlicht in:Nature genetics 2023-10, Vol.55 (10), p.1745-1756
Hauptverfasser: Gu, Zhoulin, Gong, Junyi, Zhu, Zhou, Li, Zhen, Feng, Qi, Wang, Changsheng, Zhao, Yan, Zhan, Qilin, Zhou, Congcong, Wang, Ahong, Huang, Tao, Zhang, Lei, Tian, Qilin, Fan, Danlin, Lu, Yiqi, Zhao, Qiang, Huang, Xuehui, Yang, Shihua, Han, Bin
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Sprache:eng
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Zusammenfassung:Exploitation of crop heterosis is crucial for increasing global agriculture production. However, the quantitative genomic analysis of heterosis was lacking, and there is currently no effective prediction tool to optimize cross-combinations. Here 2,839 rice hybrid cultivars and 9,839 segregation individuals were resequenced and phenotyped. Our findings demonstrated that indica – indica hybrid-improving breeding was a process that broadened genetic resources, pyramided breeding-favorable alleles through combinatorial selection and collaboratively improved both parents by eliminating the inferior alleles at negative dominant loci. Furthermore, we revealed that widespread genetic complementarity contributed to indica – japonica intersubspecific heterosis in yield traits, with dominance effect loci making a greater contribution to phenotypic variance than overdominance effect loci. On the basis of the comprehensive dataset, a genomic model applicable to diverse rice varieties was developed and optimized to predict the performance of hybrid combinations. Our data offer a valuable resource for advancing the understanding and facilitating the utilization of heterosis in rice. Resequencing of 2,839 hybrid rice cultivars and 9,839 F 2 individuals from 18 elite crosses is used to characterize the genetics underlying a range of grain yield-related traits, providing insights into heterosis during breeding and a predictive model.
ISSN:1061-4036
1546-1718
DOI:10.1038/s41588-023-01495-8