Assessing drought stress in sugarcane with gene expression and phenomic data using CSI-OC

Sugarcane, a prominent global crop utilized for sugar, bioethanol, and renewable bioenergy production, holds significant importance in Colombia. In 2022, it contributed to the production of 2.1 million tons of sugar, 347 million liters of bioethanol, and 1745 GWh of electrical energy. The cultivation of sugarcane worldwide faces vulnerability to drought stress induced by climate change, which significantly affects yields. Understanding how plants respond to drought involves complex interactions among genes, morphology, physiology, and biochemistry. However, these factors are often analyzed separately using methods such as Differentially Expressed Genes, comparative physiology, or metabolomics, thereby restricting the potential for broader insights that could arise from their further integration. This paper uses an improved version of Control-Stress data Integration with Overlapping Clustering (CSI-OC), a methodology that provides a comprehensive perspective by integrating diverse data types, in which a Lasso-based network helps in pinpointing stress-responsive genes. The objective of this study is to utilize CSI-OC to identify genes relevant to drought stress in Colombian sugarcane cultivars. To accomplish this goal, the study analyzes both leaf and root expression data, alongside four physiological parameters associated with leaf responses across different levels of drought stress. Computational evaluation indicates that the datasets are effectively processed using the CSI-OC workflow. This methodology demonstrates good performance in identifying genes strongly correlated with both the stress condition and the considered phenotypic traits. As stress levels increase, the number of genes selected by CSI-OC displays a contrasting pattern between leaves and roots. This observation implies a coordinated cascade of gene responses from leaves to roots with escalating stress levels, indicating a holistic adaptation strategy within the plant. Overall, the findings of this study underscore the effectiveness of CSI-OC as a comprehensive approach for identifying pertinent genes linked to drought stress in sugarcane.