Mechanisms driving complex reproducible outcomes - Overall vision of research program – Development is characterized by elaborate multicellular morphologies generated from simple, single cell precursors. Dysregulation of developmental pathways has devastating consequences. For instance, in humans, it leads to various cancers, neurodevelopmental disorders, cardiovascular diseases, autoimmune and inflammatory disorders, and many more (editorialized in 3,4). The core question of my first research direction is: how do members of transcription factor (TF) families coordinate the complex developmental pathways that generate the morphologies and cell types we see in nature? Further, developmental programs usually unfold with relatively few errors, even in the face of extensive genetic and environmental noise. The core question of my second research direction is: what determinants and relationships lend reproducibility to the remarkably difficult task of developmental patterning? Overview of research in the laboratory – Our first research direction focuses on TF functional divergence, a central driver of the remarkable cellular and organismal complexity seen in Eukaryota5-10,12,13. Using homeodomain proteins as a model, we found what appears to be a new mechanism of TF functional divergence. Specifically, we found that two functionally divergent paralogs bind a nearly identical set of genes. Despite this, each paralog has hundreds of uniquely regulated genes. These TFs thus appear to generate paralog-specific transcriptional outcomes through differential usage of shared binding sites. Regulatory mechanisms and evolutionary properties of this new mechanism are unknown. Our second research direction investigates the molecular factors and functional partnerships generating robust outcomes, particularly for complex organs of multicellular eukaryotes44,47-49. Using mathematical modeling, screening of natural variants, and flat leaf production as a readout, we identified variants of Arabidopsis thaliana with clear differences in robustness. These preliminary analyses reveal a genetic basis to robust flat leaf production and suggest robustness is a complex polygenic phenomenon. The genetic determinants and relationships underlying this robustness are unknown. Five-year goals – We propose to study differential usage of shared binding sites using evolutionary, bioinformatic, and mechanistic approaches. We will include new TFs and new species to test the breadth of this mechanism, bioinformatic and statistical analyses to predict causal features, and genomic and proteomic approaches to directly test for their functional contributions. We propose to identify the genetic determinants and relationships responsible for robust flat leaf production using quantitative genetic, mechanistic, and mathematical approaches. Genetic polymorphisms associated with robustness will be identified, then tested using CRISPR- Cas9 base editing and transcriptomics. We will also target known players using genomic and proteomic assays. Finally, the mathematical framework of topological data analysis – which captures the structure of large datasets – will be used to identify factors and relationships controlling the complex phenomenon of robustness.
