Multiomic Data Integration in the Analysis of Drought-Responsive Mechanisms in Quercus ilex Seedlings

The integrated analysis of different omic layers can provide new knowledge not provided by their individual analysis. This approach is also necessary to validate data and reveal post-transcriptional and post-translational mechanisms of gene expression regulation. In this work, we validated the possibility of applying this approach to non-model species such as Quercus ilex. Transcriptomics, proteomics, and metabolomics from Q. ilex seedlings subjected to drought-like conditions under the typical summer conditions in southern Spain were integrated using a non-targeted approach. Two integrative approaches, PCA and DIABLO, were used and compared. Both approaches seek to reduce dimensionality, preserving the maximum information. DIABLO also allows one to infer interconnections between the different omic layers. For easy visualization and analysis, these interconnections were analyzed using functional and statistical networks. We were able to validate results obtained by analyzing the omic layers separately. We identified the importance of protein homeostasis with numerous protease and chaperones in the networks. We also discovered new key processes, such as transcriptional control, and identified the key function of transcription factors, such as DREB2A, WRKY65, and CONSTANS, in the early response to drought.