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Pleiotropy and epistasis in auxin signaling networks

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Date

2024-09-13

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Publisher

Virginia Tech

Abstract

Plant hormones and their gene regulatory networks orchestrate a diverse array of metabolic and physiological changes crucial for growth, development, and environmental responses. Targeting the engineering of hormone signaling networks holds promise for enhancing plant health, crop productivity, and vigor. However, these networks are intricate, featuring negative feedback loops, extensive interconnections between pathways, pleiotropy, and overlapping gene expression. These complexities pose challenges in identifying candidate genes and parsing apart their isolated functions that could be strategically engineered to achieve desired plant phenotypes. Integration of comparative evolution, synthetic biology, and expression analysis facilitates the deconstruction of these networks. Through systems biology approaches data dimensionality can be reduced, enabling the attribution of specific phenotypes to associated genes. Here, I reviewed how the employment of these above-mentioned approaches can aid in the identification of candidate genes involved the regulation of growth and development within specific tissues, and how through synthetic biology we can explore the sequence-function space of candidate genes and their pathway modules. Candidate genes identified through this process can be evaluated through comparative evolutionary approaches, and efficiently tested in synthetic systems for engineering of their molecular functionalities in a high-throughput manner. Here, as a case study, I employ a systems biology approach to identify tissue-specific candidate genes within the auxin regulatory network in soybean shoot development. This method aims to minimize pleiotropy and off-target effects by utilizing expression analysis tissue-specificity score and principal component analysis. I primarily, focused on three pivotal components of the nuclear auxin signaling pathway: Aux/IAA transcriptional repressors, ARF transcription factors, and TIR1/AFB auxin receptors. These components collectively modulate auxin signaling, influencing various growth and environmental responses. I identified genes within the three pivotal components of auxin signaling involved in early shoot architecture development, which has advantages from weed suppression to yield in soybean cultivation. I used a yeast chassis to investigate the function of pleiotropic auxin receptors, which primarily regulate Aux/IAA levels and orchestrate transcriptional changes in response to auxin. I explored whether these receptors modulate auxin response in a concerted fashion, as they are generally not tissue specific. Here, I reported that auxin receptors interact in an epistatic manner to modulate auxin response. This case of study serves as a foundation in engineering plant genotype-phenotype via auxin signaling.

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Keywords

Gene networks, auxin, crop improvement, synthetic biology, transcriptomics, epistasis, pleiotropy

Citation