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

Molecular Plant 2021年第6期14卷 874-887页

作者： Xianran Li Tingting Guo Jinyu Wang Wubishet ABekele Sivakumar Sukumaran Adam EVanous james pmcnellie Laura Tibbs Cortes Marta SLopes Kendall RLamkey Mark EWestgate John KMcKay Sotirios VArchontoulis Matthew PReynolds Nicholas ATinker Patrick SSchnable Jianming Yu Department of Agronomy Iowa State UniversityAmesIA 50011USA Ottawa Research and Development Centre Agriculture and Agri-Food CanadaOttawaONCanada International Maize and Wheat Improvement Center(CIMMYT) Mexico CityMexico Department of Bioagricultural Sciences and Pest Management Colorado State UniversityFort CollinsCO 80523USA

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.

关键词： phenotypic plasticity genotype by environment interaction gene-environment interplay genomewide association studies genomic selection flowering time reaction norm

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