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

Abstract

Improving crop productivity while simultaneously reducing agricultural water input is essential to ensure the security of our global food supply and protect our diminishing freshwater resources. The irrigation requirements needed to mitigate the productivity loss associated with drought stress makes agriculture the largest industrial consumer of fresh water (Boyer, 1982; Hamdy et al., 2003). Addressing these challenges will require an integrated approach that combines irrigation practices that minimize water loss and the deployment of crop plants with superior water use efficiency

Latent Space Phenotyping: Automatic Image-Based Phenotyping for Treatment Studies

“…We evaluated the proposed method using three natural datasets across different plant species and different treatment types, including a population of recombinant inbred lines of Foxtail grass (Setaria) treated with drought stress [8], a panel of sorghum treated with nitrogen deficiency [34], and the founders of a nested association mapping population of Canola Brassica napus treated with drought stress. We performed two additional experiments using synthetic datasets, including a model of Arabidopsis thaliana, where ground-truth candidate loci were verified.…”

“…We used a published dataset of a recombinant inbred line (RIL) population of the C 4 model grass Setaria [9,8]. The dataset includes drought and well-watered conditions and has been used to detect QTL relevant to water use efficiency and drought tolerance [26,8].…”

“…The dataset was used as provided by the authors of the original study [8] with a few modifications. The image data was downsampled to 411 by 490 pixels, to allow for a more practical input size for the CNN.…”

“…A total of four QTL were detected with respect to the ratio of the trait under the two conditions. However, we discard these QTL as potentially spurious under the guidance of the original paper [8]. For the difference in trait values between conditions, we identified two QTL associated with drought resistance in the Setaria RIL population (Figure 3.1, right).…”

“…The use of association mapping techniques, such as genome-wide association studies (GWAS) have yielded many candidate loci for agronomically important quantitative traits in plants [4]. For food crops, genome-wide analysis of susceptibility or resistance to abiotic stress factors such as drought [8], nitrogen deficiency [24], salinity [5], or other factors leads to the discovery of genetic differences underlying these agronomically important characteristics. These treatment-based GWAS studies are capable of identifying resistance alleles which could result in a tolerance to a wider variety of environmental conditions if, for example, introgressed into agricultural lines.…”