An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops

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creativework.keywords - en
Phenotypic plasticity
Plasticité phénotypique
Interaction génotype-environnement
Genotype-environment interaction
creativework.keywords - fr
Sélection génomique
Geonomic selection
Grain--Flowering time
Céréales--Floraison
dc.contributor.author
Li, Xianran
Guo, Tingting
Wang, Jinyu
Bekele, Wubishet A.
Sukumaran, Sivakumar
Vanous, Adam E.
McNellie, James P.
Tibbs-Cortes, Laura E.
Lopes, Marta S.
Lamkey, Kendall R.
Westgate, Mark E.
McKay, John K.
Archontoulis, Sotirios V.
Reynolds, Matthew P.
Tinker, Nicholas A.
Schnable, Patrick S.
Yu, Jianming
dc.date.accepted
2021-03-09
dc.date.accessioned
2024-05-27T14:38:57Z
dc.date.available
2024-05-27T14:38:57Z
dc.date.issued
2021-03-09
dc.date.submitted
2020-09-30
dc.description.abstract - en
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.
dc.identifier.citation
Li, X., Guo, T., Wang, J., Bekele, W. A., Sukumaran, S., Vanous, A. E., McNellie, J. P., Tibbs-Cortes, L. E., Lopes, M. S., Lamkey, K. R., Westgate, M. E., McKay, J. K., Archontoulis, S. V., Reynolds, M. P., Tinker, N. A., Schnable, P. S., & Yu, J. (2021). An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops. Molecular Plant, 14(8), 874–887. https://doi.org/10.1016/j.molp.2021.03.010
dc.identifier.doi
https://doi.org/10.1016/j.molp.2021.03.010
dc.identifier.issn
1752-9867
1674-2052
dc.identifier.uri
https://open-science.canada.ca/handle/123456789/2516
dc.language.iso
en
dc.publisher
Cell Press
dc.rights - en
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.rights - fr
Creative Commons Attribution - Pas d'utilisation commerciale - Pas de modification 4.0 International (CC BY-NC-ND 4.0)
dc.rights.openaccesslevel - en
Gold
dc.rights.openaccesslevel - fr
Or
dc.rights.uri - en
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.uri - fr
https://creativecommons.org/licenses/by-nc-nd/4.0/deed.fr
dc.subject - en
Agriculture
dc.subject - fr
Agriculture
dc.subject.en - en
Agriculture
dc.subject.fr - fr
Agriculture
dc.title - en
An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops
dc.type - en
Article
dc.type - fr
Article
local.article.journalissue
6
local.article.journaltitle
Molecular Plant
local.article.journalvolume
14
local.pagination
874-887
local.peerreview - en
Yes
local.peerreview - fr
Oui
local.requestdoi
No
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