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CROP BREEDING & GENETICS

Analysis of Genotype-by-Environment Interaction in Wheat Using a Structural Equation Model and Chromosome Substitution Lines

^a Monsanto Co., 800 N. Lindbergh Blvd., St. Louis, MO 63167
^b Univ. of Nebraska, Lincoln, NE 68583-0940
^c USDA-ARS, Florence, SC
^d Washington State Univ., Pullman, WA. Published as Univ. of Nebraska ARD Journal Series no. 14689

^* Corresponding author (keskridge1{at}unl.edu).

The presence of genotype-by-environment interaction (GEI) complicates selection of superior genotypes and an understanding of environmental and genotypic causes of significant GEI is important in all stages of plant breeding. We present a systematic approach for understanding GEI of complex interrelated traits by combining chromosome substitution lines that allowed us to study the effects of genes on a single chromosome with a structural equation model that approximated the complex processes involving genes, environmental conditions, and traits. We applied the approach to recombinant inbred chromosome wheat lines grown in multiple environments. The final model explained 74% of the yield GEI variation and we found that spikes per square meter (SPSM) GEI had the highest direct effect on yield GEI and that the genetic markers were mostly sensitive to temperature and precipitation during the vegetative and reproductive periods. In addition, we identified a number of direct and indirect causal relationships that described how genes interacted with environmental factors to affect GEI of several important agronomic traits which would not have been possible with previously used methods.

Abbreviations: CNN, cv. Cheyenne • GEI, genotype-by-environment interaction • KPS, kernels per spike • ML, maximum likelihood • P, precipitation • QTL, quantitative trait locus • RICLs, recombinant inbred chromosome lines • RILs, recombinant inbred lines • SEM, structural equation modeling • SPSM, spikes per square meter • SR, solar irradiance • T, temperature • TKW, thousand kernel weight • YLD, yield.