High-throughput profiling and analysis of plant responses over time to abiotic stress

Authors: VELEY, KIRA - Danforth Plant Science Center; BERRY, JEFFREY - Danforth Plant Science Center; FENTRESS, SARAH - Danforth Plant Science Center; SCHACHTMAN, DANIEL - University Of Nebraska; Baxter, Ivan; BART, REBECCA - Danforth Plant Science Center

Submitted to: Plant Direct
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/28/2017
Publication Date: 10/25/2017
Citation: Veley, K.M., Berry, J.C., Fentress, S., Schachtman, D., Baxter, I.R., Bart, R. 2017. High-throughput profiling and analysis of plant responses over time to abiotic stress. Plant Direct. 1(4):1-13. https://doi.org/10.1002/pld3.23.
DOI: https://doi.org/10.1002/pld3.23

Interpretive Summary: Energy sorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass, annual crop prized for abiotic stress (drought, heat, etc.,) tolerance. Measuring genotype-by-environment (G x E) interactions on crop productivity for breeding applications remains a progress bottleneck. High throughput phenotyping (crop performance) within controlled environments has been proposed as a potential solution. Early, measurable indicators of desirable agronomic traits that translate to the farmer's field would greatly aid in increasing the speed of crop improvement efforts. Here we identify shape, color and ionomic (elemental composition) indicators for genetically diverse sorghum varieties to abiotic stress. We subjected a panel of 30 sorghum genotypes (cultivars) to nitrogen deprivation or drought stress and measured plant performance responses within an automated phenotyping facility followed by ionomic profiling. Images of growing plants (24 plants per genotype per experiment, 1440 plants total) were collected every day for three weeks, and key metrics were quantified using PlantCV image analysis software. Responses to stress were quantified using differences in shape (16 measureable outputs), color (hue and intensity), and ionome (18 elements total). We found plant shape characteristics to be reliable indicators of performance under both stress conditions tested. In contrast, color was a defining indicator of nitrogen starvation but not drought stress. Through this analysis we were able to measure the speed at which specific genotypes respond to stress and identify individual cultivars that perform most favorably under these stress conditions. This study reveals the importance of quantitative outputs displayed by sorghum varieties under different abiotic stress conditions that can now be investigated further using classical and molecular genetics. However, translatability of the results from this study need to be validated to determine how each of the many measurable outputs discovered here, correlate with similar stress responses under field conditions. We predict that some indicators will prove more translatable than others. In the end we must overlay high throughput phenotyping with field studies to accelerate crop improvement. These results will improve our understanding of this important process in grasses, and understanding the results on the genetic level will help make a wide variety of crops, including those that are not related to the grasses such as soybean and cotton, more tolerant to environmental challenges.

Technical Abstract: Energy sorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass, annual crop prized for abiotic stress tolerance. Measuring genotype-by-environment (G x E) interactions remains a progress bottleneck. High throughput phenotyping within controlled environments has been proposed as a potential solution. Early, measureable indicators of desirable traits that translate to the field would increase the speed of crop improvement efforts. Here we identify shape, color and ionomic indicators of abiotic stress for genetically diverse sorghum varieties. We subjected a panel of 30 sorghum genotypes to either nitrogen deprivation or drought stress and measured responses within an automated phenotyping facility, followed by ionomic profiling. Images of growing plants were collected every day for three weeks, and key metrics are reported. Responses to stress were quantified using differences in shape (16 measureable outputs), color (hue and intensity) and ionome (18 elements). We found shape characteristics to be reliable indicators of performance under both stress conditions tested. In contrast, color was a defining indicator of nitrogen starvation but not drought stress. Through this analysis we were able to measure the speed at which specific genotypes respond to stress and identify individual genotypes that perform most favorably under these stress conditions. These data are made available through an open access, user-friendly, web-based interface. Ionomic profiling was conducted as an independent, low cost and high throughput option for characterizing G x E. The effect of genotype on the ionome was consistent between the two experiments confirming the robustness of the high throughput platform. In addition, multiple individual elements were identified as quantitative outputs of abiotic stress. While the important challenge of translation between controlled environment- and field-based experiments remains, the multiple revealed quantitative outputs from different abiotic stress conditions are genetically encoded. Consequently, the genetic explanations for these responses can now be elucidated using classical and molecular genetics. We propose this work as a time efficient method of dissecting the genetic mechanisms used by sorghum to respond to abiotic stress. In summary, this work provides a mechanism to overlay high throughput phenotyping with field studies to accelerate crop improvement.