CUBIC: an atlas of genetic architecture promises directed maize improvement

Abstract 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...

Full description

Bibliographic Details
Main Authors: Hai-Jun Liu, Xiaqing Wang, Yingjie Xiao, Jingyun Luo, Feng Qiao, Wenyu Yang, Ruyang Zhang, Yijiang Meng, Jiamin Sun, Shijuan Yan, Yong Peng, Luyao Niu, Liumei Jian, Wei Song, Jiali Yan, Chunhui Li, Yanxin Zhao, Ya Liu, Marilyn L. Warburton, Jiuran Zhao, Jianbing Yan
Format: Article
Language:English
Published: BMC 2020-01-01
Series:Genome Biology
Subjects:
Online Access:https://doi.org/10.1186/s13059-020-1930-x
Description
Summary:Abstract 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.
ISSN:1474-760X