URoL: Epigenetics 2- Collaborative Research: Revealing how epigenetic inheritance governs the environmental challenge response with transformative 3D genomics and machine learning

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This project seeks to define how plants respond to environmental challenge. Understanding plant responses to environmental stress is important to secure our future national interest in maintaining agricultural productivity and preserving the environment. This project will advance the understanding of how elevated carbon dioxide alters plant form on both the molecular scale of DNA organization, as well on the scale of plant growth. This proposal asks whether these plant responses will last generations, and if so, tests the mechanism of inheritance. Additionally, this project promotes the training and development of a diverse future science-enabled workforce. The product of this research will be a predictive model for the lasting consequences of environmental challenge on growth patterns across the plant kingdom.It is unclear how environmental challenge broadly alters plant form, and whether the resulting changes are inherited epigenetically to the subsequent generations. This proposal establishes a team with expertise in genomics, phenomics, data visualization, image analysis, machine learning, modeling, and analysis of three dimensional (3D) shapes for the common goal to bridge the environment / genotype / phenotype gap. The transformative aspect of this proposal is the novelty of the data analysis. The team has cutting-edge expertise in the mathematical and computational analysis of plant form in 3D space. However, the analysis of genome regulation hasn't changed for a decade and is stuck in 2D. The researchers propose to use their expertise on 3D shapes to elevate the standard genomic analysis to 3D, therefore opening doors to new discoveries based on the relation between genome regulation and plant form. By utilizing diverse plant species, well-characterized mutants, and machine learning, the researchers will deliver a computational algorithm to predict and model across the plant kingdom how environmental challenge regulates plant form, and which of these aspects are epigenetically inherited to the next generation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.