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Genomic insight into balancing high yield, good quality, and blast resistance of japonica rice
Genome Biology ( IF 12.3 ) Pub Date : 2021-10-06 , DOI: 10.1186/s13059-021-02488-8
Ning Xiao 1, 2 , Cunhong Pan 1 , Yuhong Li 1 , Yunyu Wu 1 , Yue Cai 1 , Yue Lu 3 , Ruyi Wang 2 , Ling Yu 1 , Wei Shi 1 , Houxiang Kang 2 , Zhaobing Zhu 1 , Niansheng Huang 1 , Xiaoxiang Zhang 1 , Zichun Chen 1 , Jianju Liu 1 , Zefeng Yang 3 , Yuese Ning 2 , Aihong Li 1, 4
Affiliation  

Balancing the yield, quality and resistance to disease is a daunting challenge in crop breeding due to the negative relationship among these traits. Large-scale genomic landscape analysis of germplasm resources is considered to be an efficient approach to dissect the genetic basis of the complex traits. Central China is one of the main regions where the japonica rice is produced. However, dozens of high-yield rice varieties in this region still exist with low quality or susceptibility to blast disease, severely limiting their application in rice production. Here, we re-sequence 200 japonica rice varieties grown in central China over the past 30 years and analyze the genetic structure of these cultivars using 2.4 million polymorphic SNP markers. Genome-wide association mapping and selection scans indicate that strong selection for high-yield and taste quality associated with low-amylose content may have led to the loss of resistance to the rice blast fungus Magnaporthe oryzae. By extensive bioinformatic analyses of yield components, resistance to rice blast, and taste quality, we identify several superior alleles for these traits in the population. Based on this information, we successfully introduce excellent taste quality and blast-resistant alleles into the background of two high-yield cultivars and develop two elite lines, XY99 and JXY1, with excellent taste, high yield, and broad-spectrum of blast resistance. This is the first large-scale genomic landscape analysis of japonica rice varieties grown in central China and we demonstrate a balancing of multiple agronomic traits by genomic-based strategy.
更新日期:2021-10-06
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