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01 24, 2020;21 (1): 20.

CUBIC: an atlas of genetic architecture promises directed maize improvement.

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
Author Information
  1. Hai-Jun Liu: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  2. Xiaqing Wang: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  3. Yingjie Xiao: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  4. Jingyun Luo: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  5. Feng Qiao: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  6. Wenyu Yang: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  7. Ruyang Zhang: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China.
  8. Yijiang Meng: College of Life Science, Hebei Agricultural University, Baoding, 071001, China.
  9. Jiamin Sun: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  10. Shijuan Yan: Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Tianhe District, Guangzhou, 510640, China.
  11. Yong Peng: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  12. Luyao Niu: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  13. Liumei Jian: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  14. Wei Song: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China.
  15. Jiali Yan: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
  16. Chunhui Li: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China.
  17. Yanxin Zhao: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China.
  18. Ya Liu: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China.
  19. Marilyn L Warburton: Corn Host Plant Resistance Research Unit, United States Department of Agriculture-Agricultural Research Service, Box 9555, Mississippi State, MS, 39762, USA.
  20. Jiuran Zhao: Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Beijing Academy of Agriculture & Forestry Sciences, Beijing, 100097, China. maizezhao@126.com.
  21. Jianbing Yan: National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China. yjianbing@mail.hzau.edu.cn. ORCID
PMID: 31980033 DOI: 10.1186/s13059-020-1930-x

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.

Keywords

Cross-omics Functional genomics Genome-wide association mapping Population development Zea mays

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MeSH Term

Alleles
Epistasis, Genetic
Gene Expression Profiling
Genes, Plant
Genome-Wide Association Study
Genomics
Phenotype
Polymorphism, Single Nucleotide
Quantitative Trait Loci
Zea mays
Journal Article Research Support, Non-U.S. Gov't

Links to CNCB-NGDC Resources

BioProject: PRJCA000346 (Resequencing on a modified MAGIC population of maize)
GSA: CRA000171 (CRA_171)
GEN: GEND000324 (Unbalanced Breeding-like Inter-Cross (CUBIC) offspring)

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