CUBIC: an atlas of genetic architecture promises directed maize improvement
Genome biology, 2020•Springer
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 …
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 …
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.
Springer
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