The physiology, mapping, and prediction of stable carbon isotopes: a proxy trait for water-use efficiency in maize
Drought is the leading cause of yield loss in maize in the United States, and climate models predict that drought events will become more frequent and severe. In recent years, focus has been placed on developing crops to be better adapted to weather extremes by selecting for heat tolerance and drought resistant traits. Due to difficulty in quantifying water-use efficiency (WUE), it is a trait that is often not the target of direct selection in breeding programs. However, as global fresh water reserves become depleted and rainfall becomes more sporadic, there is a need to shift focus to develop plants that can yield competitively while simultaneously requiring less water. Thus, developing methodologies to measure WUE at scale, and elucidating the mechanism underlying WUE will become vital to food security in the future. The relationship between stable carbon isotope ratios (δ13C) and WUE has been well characterized in C3 crops, but only recently gained attention in C4 plants. We observed high correlations between WUE and δ13C in greenhouse grown maize, which is important towards developing an effective method to quickly assay WUE in C4 species. To achieve our objective of developing δ13C into a useful trait for maize breeders, we studied the optimal environment and timepoints for sampling. Our results demonstrate that a lack of water has the ability to downshift δ13C values while maintaining comparable variance. To assess how quickly δ13C values respond to drought conditions, we collected data that illustrates a slow, but immediate, additive decrease in δ13C that was detectable as early as the next leaf after water stress was applied. Once optimal water is restored, δ13C values increase and eventually return to pre-drought levels. These results highlight the need to acquire samples when plants are not experiencing drought stress. To further develop δ13C measurements for real-world applications, large multiyear trials were planned with elite germplasm. These experiments showed moderate levels of heritability which facilitate characterizing the genetic architecture of this trait. Prior mapping attempts found regions correlated to δ13C, while multiple methods presented here did not. Our results show the complexity and multigenic nature of δ13C, thus highlighting the need for approaches that combine effects from every marker. Genomic prediction is one such method to account for the additive nature of this phenotype. The integration of physiological and genetic control of δ13C facilitates the breeding and engineering of more efficient crops.
Water-use Efficiency, Maize, Genetic Mapping, Genomic Prediction
University of Illinois - Urbana-Champaign
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University of Illinois at Urbana-Champaign