MOLECULAR CROSSTALK BETWEEN PHYTOHORMONES AND EPIGENETIC REGULATION IN PLANT STRESS RESPONSE A MULTI-OMICS APPROACH

Abstract

Purpose: This investigation utilizes a multi-omics approach to further understand the interplay between phytohormones and epigenetics in the stress responses of plants. Even though the stress is not being gone through systematically, it is clear that both phytohormonal signalling and epigenetic mechanisms in isolation are key players in the sustenance of plants to stress. The investigation proposes to determine how these systems work together to regulate plant invasive plant stress such as drought, salinity or even pathogens.

Objective: The main aim of the research is to investigate interactions between different signal steroid hormonal pathways, abscisic acid (ABA) and its antagonist’s salicylic acid (SA) and jasmonic acid (JA) and histone modifications namely DNA methylation and histone acetylation during the plant stress responses. The purpose is to delineate key control elements that would be able to give insights on meetings of these various systems and stress memory and the effect on stress tolerance.

Methodology: The investigation of plants’ responses to different environmental stressors involved the application of a multi-omics approach integrating genomic, transcriptomic, epigenomic and proteomic information. Statistical methods included the Chi-Square Test for Independence; the Kruskal-Wallis Test; Ordinal Logistic Regression; and the Mann-Whitney U Test. To verify the statistical results, graphical means such as bar plots and box plots were employed. The Chi-Square Test was used to evaluate the relationship between the Area of Expertise and Observed Epigenetic Modification, while the Kruskal-Wallis Test evaluated the median Usefulness of Multi-Omics among Different Expert Groups. Ordinal Logistic Regression analyzed the effect that expertise and experience as an observer of epigenomic modifications have on the perception of multi-omics approaches, while the Mann- Whitney U Test assessed the differences in perceptions based on the type of the underlying mechanism of the epigenetic modification as memory mechanisms.

Results: No statistically significant differences were seen in chi-square testing for association with the Area of Expertise and Observed Epigenetic Modification (Chi-Square statistics = 6.67, p-value = 0.573, df = 8). In the presence of various levels of expertise, the median Usefulness of Multi-Omics remained unchanged as evidenced by the Kruskal-Wallis statistic = 0.85, p-value = 0.931. Ordinal Logistic Regression Statistics analyzed the Area of Expertise, Observed Epigenetic Modification, and Years of Experience variables and determined them not useful in multi-omics perception estimates (Pseudo-R-squared = 0.01255, LLR p-value = 0.6795). The estimation was done using the Mann-Whitney U Test which indicated no difference existed in the Usefulness of Multi-Omics regarding the epigenetic memory mechanisms where some people used it and others did not, and the U statistic recorded was U statistic = 6611.0, p-value = 0.554. The use of graphical data such as the bar plots and Box plots further confirms these statistical results. Their Relationships and distributions of the important variables are given pictorially to enhance understanding.

Practical Implications: A potential use of the identification of some specific epigenetic markers associated with the phytohormonal signals will be to use genetic or epigenetic means to enhance crop stress resilience. Such targeting of these key regulatory nodes where phytohormonal signalling and epigenetic regulation feedback into each other will lay the groundwork for the creation of crops bred for resistance to environmental stresses. Such results have important implications for the development of crop varieties which address the consequences of climate change and food insecurity issues.

Novelty: This research is among the first to use fully integrated multi-omics to study the interactions between phytohormones and epigenetics in the stress responses of plants. It is necessary to understand how all the omic data fit together into an integrated picture to understand how plants can adapt to a stress situation. The epigenetic aspect has been introduced in the study as well as the concept of how it is elicited by phytohormones, which adds to the literature on plant stress memory.

Conclusion: The data shows that there is a close correlation between phytohormones and epigenetic mechanisms directing genes that ultimately respond to stress through environmental changes. Yet, there were no strong relationships observed between knowledge, exposure or change and attitudes about the usefulness of the other methods that emerged from the case study; such a situation did not impede the further investigation of plant stress response in this multi-omics study. The data suggest the possibility of modifying the genetic program of plants for them to withstand certain types of stress through targeted interference with the phytohormonal-epigenetic regulatory system. Further studies should aim at testing these conclusions in a more diverse set of crops and environments to explain the molecular crosstalk in a more practical sense