Dissecting epistasis for enhanced crop productivity
A major goal in plant biology is to understand how naturally occurring genetic variation leads to quantitative differences in economically important traits. Efforts to navigate the genotype-to-phenotype map are often focused on linear genetic interactions. As a result, crop breeding is mainly driven by loci with predictable additive effects. However, it has become clear that quantitative trait variation often results from perturbations of complex genetic networks. Thus, understanding epistasis, or interactions between genes, is key for our ability to predictably improve crops. To meet this challenge, this project will reveal and dissect epistatic interactions in gene regulatory networks that guide stem cell differentiation in the model crop tomato. In the first aim, I will utilize exhaustive allelic series for epistatic MADS-box genes that quantitatively regulate flower and fruit production as an experimental model system to study fundamental principles of epistasis that can be applied to other genetic networks. Genome-wide transcript profiling will be used to reveal molecular signatures of epistasis and potential targets for predictable crop improvement by advanced CRISPR/Cas9 gene editing technology. Further, my preliminary data suggests that epistasis is widespread and important across major productivity traits in tomato. Thus, in a second aim, I will access this untapped resource of cryptic genetic variation by sensitizing a tomato diversity panel for weak epistatic effects from unknown natural modifier loci of stem cell differentiation using trans-acting CRISPR/Cas9 editing cassettes. This screen represents a new approach to mutagenesis in plants with potential to reveal cryptic variation in other system. The outcomes of this project will advance our knowledge in a fundamental area of plant genome biology, help uncover and understand the functional architecture of epistasis, and have potential to bring significant improvements to agriculture.