An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops
| Autor: | Adam Vanous, Tingting Guo, Kendall R. Lamkey, Matthew P. Reynolds, Jinyu Wang, John K. McKay, Marta S. Lopes, Xianran Li, Mark E. Westgate, Patrick S. Schnable, Wubishet A. Bekele, Nicholas A. Tinker, Sotirios V. Archontoulis, James P. McNellie, Sivakumar Sukumaran, Jianming Yu, Laura E. Tibbs-Cortes |
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| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
0301 basic medicine Germplasm Avena Genome-wide association study Plant Science Computational biology Biology 01 natural sciences Polymorphism Single Nucleotide Zea mays 03 medical and health sciences Gene Expression Regulation Plant Dimension (data warehouse) Gene–environment interaction Molecular Biology Triticum Genetic association Phenotypic plasticity Marker-assisted selection Plant Breeding 030104 developmental biology Phenotype Trait Gene-Environment Interaction 010606 plant biology & botany Genome-Wide Association Study |
| Zdroj: | Molecular plant. 14(6) |
| ISSN: | 1752-9867 |
| Popis: | Identifying mechanisms and pathways involved in gene-environment interplay and phenotypic plasticity is a long-standing challenge. It is highly desirable to establish an integrated framework with an environmental dimension for complex trait dissection and prediction. A critical step is to identify an environmental index that is both biologically relevant and estimable for new environments. With extensive field-observed complex traits, environmental profiles, and genome-wide single nucleotide polymorphisms for three major crops (maize, wheat, and oat), we demonstrated that identifying such an environmental index (i.e., a combination of environmental parameter and growth window) enables genome-wide association studies and genomic selection of complex traits to be conducted with an explicit environmental dimension. Interestingly, genes identified for two reaction-norm parameters (i.e., intercept and slope) derived from flowering time values along the environmental index were less colocalized for a diverse maize panel than for wheat and oat breeding panels, agreeing with the different diversity levels and genetic constitutions of the panels. In addition, we showcased the usefulness of this framework for systematically forecasting the performance of diverse germplasm panels in new environments. This general framework and the companion CERIS-JGRA analytical package should facilitate biologically informed dissection of complex traits, enhanced performance prediction in breeding for future climates, and coordinated efforts to enrich our understanding of mechanisms underlying phenotypic variation. |
| Databáze: | OpenAIRE |
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