Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects

By Scott C. Chapman, Mark Cooper, Dean W. Podlich, Graeme L. Hammer. Agronomy Journal, 2003

221 citations recorded by the source corpus.

Functional genomics is the systematic study of genome-wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM-- Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this space using a quantitative genetics model of a plant breeding program (QU-- GENE) to simulate recurrent selection. Complex epistatic and gene x environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe-Terminal drought environment type, late genotypes were favored in the Mild-Terminal and Midseason drought environment types. In the Severe-Terminal environment, there was an interaction of the stay-green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene x gene x environment interactions will challenge the application of genomics and marker-assisted selection in crop improvement for dryland adaptation.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/e32f750deb61d6dc1d2fc9b32fe6194faae5fbad

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Citations in the corpus

Improving drought tolerance in maize: a view from industry (2004, methodology): “Chapman et al. (2003) working in grain sorghum (Sorghum bicolor L. Moench) provided some motivation for the application of a modeling approach to the study of multiple complex traits with putative roles in determining drought tolerance and grain yield in a target population of environments (TPE).”
Model-assisted phenotyping and ideotype design (2015, background): “…et al., 2011). in addition, robust gene-to-phenotype models linked to quantitative genetics models like QUGene (Podlich and Cooper, 1998), give new opportunities to explore alternative selection methods and assist breeding for complex traits in broad or specific environments (Chapman et al., 2003).”
Statistical models for genotype by environment data: from conventional ANOVA models to eco-physiological QTL models (2005, background): “Some key papers in this new tradition are Cooper et al. (2002a, 2002b) and Chapman et al. (2002, 2003) .”
Crop design for specific adaptation in variable dryland production environments (2014, background): “They do not search the full spectrum of potential G M E combinations forming the ‘adaptation landscape’ (Cooper and Hammer 1996; Chapman et al. 2003; Messina et al. 2011).”
Genomics and the physiologist: bridging the gap between genes and crop response (2004, background): “A new generation of gene-to-phenotype models that link genetic controls of key traits, crop process models and simulation of the plant breeding process itself is currently under development, and offers unique opportunities to strengthen the linkages between geneticists, plant breeders and physiologi”
APSIM - Evolution towards a new generation of agricultural systems simulation (2014, background): “A rugged yield-trait adaptation landscape indicates complex G E M interactions, but combining biologically functional crop models in APSIM with the quantitative genetics simulation model QU-GENE (Podlich and Cooper, 1998) has allowed identification of promising breeding strategies that enable naviga”
Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials (2008, methodology): “These assumptions resulted in there being only 4235 ‘expression states’, i.e. genotypes that had the same net value for a trait parameter (once gene eVects are added) have the same expression state, and would have the same phenotype in a given environment (Chapman et al. 2003).”