文献类型： 外文期刊
作者： Liu, Hai-Jun 1 ; Wang, Xiaqing 1 ; Xiao, Yingjie 1 ; Luo, Jingyun 1 ; Qiao, Feng 1 ; Yang, Wenyu 1 ; Zhang, Ruyang 2 ; Me 1 ;
作者机构： 1.Huazhong Agr Univ, Natl Key Lab Crop Genet Improvement, Wuhan 430070, Peoples R China
2.Beijing Acad Agr & Forestry Sci, Beijing Key Lab Maize DNA Fingerprinting & Mol Br, Beijing 100097, Peoples R China
3.Sanming Acad Agr Sci, Sanming 365509, Fujian, Peoples R China
4.Huazhong Agr Univ, Coll Sci, Wuhan 430070, Peoples R China
5.Hebei Agr Univ, Coll Life Sci, Baoding 071001, Peoples R China
6.Guangdong Acad Agr Sci, Agrobiol Gene Res Ctr, Guangzhou 510640, Peoples R China
7.USDA ARS, Corn Host Plant Resistance Res Unit, Box 9555, Mississippi State, MS 39762 USA
关键词： Population development; Genome-wide association mapping; Cross-omics; Functional genomics; Zea mays
期刊名称：GENOME BIOLOGY （ 影响因子：13.583； 五年影响因子：17.433 ）
ISSN： 1474-760X
年卷期： 2020 年 21 卷 1 期
页码：
收录情况： SCI
摘要： Background Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders. Results Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width. Conclusions Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits.
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