Cross-species predictive modeling reveals conserved drought responses between maize and sorghum

Authors: PARDO, JEREMY - Michigan State University; WAI, CHING MAN - Michigan State University; HARMAN, MAXWELL - Michigan State University; NGUYEN, ANNIE - Michigan State University; KREMLING, KARL - Cornell University; ROMAY, MARIA CINTA - Cornell University; Lepak, Nicholas; BAUERLE, TARYN - Cornell University; Buckler, Edward - Ed; THOMPSON, ADDIE - Michigan State University; VANBUREN, ROBERT - Michigan State University

Submitted to: Proceedings of the National Academy of Sciences (PNAS)
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/30/2023
Publication Date: 2/27/2023
Citation: Pardo, J., Wai, C., Harman, M., Nguyen, A., Kremling, K.A., Romay, M., Lepak, N.K., Bauerle, T.L., Buckler IV, E.S., Thompson, A.M., Vanburen, R.M. 2023. Cross-species predictive modeling reveals conserved drought responses between maize and sorghum. Proceedings of the National Academy of Sciences (PNAS). 120(10). Article e2216894120. https://doi.org/10.1073/pnas.2216894120.
DOI: https://doi.org/10.1073/pnas.2216894120

Interpretive Summary: Drought is a complex and variable stress that is difficult to quantify and link to underlying mechanisms both within and across species. Here, we developed a predictive model to classify drought stress responses in sorghum and identify important features that are responsive to water deficit. Our model has high predictive accuracy across development, genotype, and stress severity, and the top features are enriched in genes related to classical stress responses and have functional and evolutionary conservation. We applied this sorghum-trained model to maize, and observed similar predictive accuracy of drought responses, supporting transfer learning across plant species. Our findings suggest there are deeply conserved drought responses across C4 grasses that are unrelated to tolerance.

Technical Abstract: Drought tolerance is a highly complex trait controlled by numerous interconnected pathways with substantial variation within and across plant species. This complexity makes it difficult to distill individual genetic loci underlying tolerance, and to identify core or conserved drought-responsive pathways. Here, we collected drought physiology and gene expression datasets across diverse genotypes of the C4 cereals sorghum and maize and searched for signatures defining water-deficit responses. Differential gene expression identified few overlapping drought-associated genes across sorghum genotypes, but using a predictive modeling approach, we found a shared core drought response across development, genotype, and stress severity. Our model had similar robustness when applied to datasets in maize, reflecting a conserved drought response between sorghum and maize. The top predictors are enriched in functions associated with various abiotic stress-responsive pathways as well as core cellular functions. These conserved drought response genes were less likely to contain deleterious mutations than other gene sets, suggesting that core drought-responsive genes are under evolutionary and functional constraints. Our findings support a broad evolutionary conservation of drought responses in C4 grasses regardless of innate stress tolerance, which could have important implications for developing climate resilient cereals.