Components of Water Use Efficiency Have Unique Genetic Signatures in the Model C₄ Grass Setaria

• Published in: Plant physiology (Bethesda) Vol. 178; no. 2; pp. 699 - 715
• Main Authors: Feldman, Max J., Ellsworth, Patrick Z., Fahlgren, Noah, Gehan, Malia A., Cousins, Asaph B., Baxtera, Ivan
• Format: Journal Article
• Language: English
• Published: United States American Society of Plant Biologists 01.10.2018
• Subjects: BASIC BIOLOGICAL SCIENCES; ECOPHYSIOLOGY AND SUSTAINABILITY
• ISSN: 0032-0889; 1532-2548; 1532-2548
• DOI: 10.1104/pp.18.00146

Plant growth and water use are interrelated processes influenced by genetically controlled morphological and biochemical characteristics. Improving plant water use efficiency (WUE) to sustain growth in different environments is an important breeding objective that can improve crop yields and enhance agricultural sustainability. However, genetic improvement of WUE using traditional methods has proven difficult due to the low throughput and environmental heterogeneity of field settings. To overcome these limitations, this study utilizes a high-throughput phenotyping platform to quantify plant size and water use of an interspecific Setaria italica × Setaria viridis recombinant inbred line population at daily intervals in both well-watered and water-limited conditions. Our findings indicate that measurements of plant size and water use are correlated strongly in this system; therefore, a linear modeling approach was used to partition this relationship into predicted values of plant size given water use and deviations from this relationship at the genotype level. The resulting traits describing plant size, water use, and WUE all were heritable and responsive to soil water availability, allowing for a genetic dissection of the components of plant WUE under different watering treatments. Linkage mapping identified major loci underlying two different pleiotropic components of WUE. This study indicates that alleles controlling WUE derived from both wild and domesticated accessions can be utilized to predictably modulate trait values given a specified precipitation regime in the model C₄ genus Setaria.