BME PhD Prospectus Defense: Anjali Gajendiran

Title: "Developing a Transposon-Based Synthetic Genomics Platform to Induce Large-Scale Genetic Diversity in Plants"

Advisory Committee: Mary Dunlop – BU BME (Chair) Ahmad (Mo) Khalil – BU BME (Advisor) Mary Gehring – MIT Biology, BE Sudarshan (Sud) Pinglay – Univ. of Washington, Genome Sciences Brian Cleary – BU CDS, BME, Biology

Abstract: Our agricultural systems are under ever-mounting pressure due to the demands of a growing global population, the effects of a warming planet, and other stresses. Innovations in plant engineering are critical to better understanding genome architecture and the effects of variation on fitness to rapidly generate crops with superior agronomic traits. Pan-genome studies have highlighted how large-scale genomic perturbations, like structural variation, are more likely to generate novel phenotypic effects than small mutational changes and underlie important crop domestication traits. While these studies can guide our attention to the variation necessary to engineer more robust crops, they are limited to naturally occurring variation within plants, which is insufficient to capture a comprehensive genetic landscape of all possible beneficial traits. As a result, there is a requirement for unbiased methods that generate large-scale variation in the plant genome to discover the genetic basis of useful traits – knowledge crucial for advancing crop development. Unfortunately, our ability to introduce and probe drastic genetic variation in plants is hampered by limitations in current plant mutagenesis methods and genome engineering tools. To address these limitations, we aim to develop a transposon-based synthetic genomics platform that reliably and efficiently induces large-scale, random genetic diversity in the plant genome. To achieve this, we aim to establish the foundational plant genome engineering components necessary to facilitate the amplification, random integration, and mapping of DNA payload-containing transposons using Arabidopsis thaliana as a model. By encoding DNA payloads, like enhancers or recombination sites, this platform can induce large-scale transcriptional rewiring and structural variation within the plant genome. To showcase the versatility of a programmable approach for inducing variation, we will leverage this platform to power a semi-continuous evolution pipeline, demonstrating how iterative cycles of enhancer arrangement can improve fitness under selection pressure. Ultimately, this platform will enable us to inform precision crop engineering, drive functional genomics studies in plants, and generate novel germplasm for plant breeders.