(612e) Defining the Architecture of Complex Traits to Enable Genome Design

Despite remarkable advances in DNA reading and writing, genome design remains a formidable challenge: even a small ensemble of hundreds of polymorphisms can afford more possible genotypes than there are atoms in the universe. Safely and effectively applying gene editing technology will therefore require comprehensive models of the genotype-to-phenotype relationship. In pursuit of this goal, we have developed super-resolution quantitative genetics approaches that allow us to make this connection at single-nucleotide resolution (She and Jarosz, Cell 2018; Jakobson, She, and Jarosz, Nat. Comm. 2019; Jakobson and Jarosz, Cell Systems, in press).

Despite the complexity of the genotype-to-phenotype relationship, we can nonetheless build a quantitative molecular understanding of the underlying design rules. All types of genetic variation made important contributions to phenotype, but there were distinct molecular signatures associated with causal variants. Notably, nominally ‘silent’ synonymous variants played a central role and cannot be neglected. Nonlinearity (dominance) was widespread and driven by regulatory variation. Natural genotype-to-phenotype maps were embedded with pervasive cross-talk between phenotypes (pleiotropy) and conditional variant effects (gene-environment interactions). Polymorphisms in disordered regions of proteins, once thought to constitute inert linkers, made widespread contributions to phenotype.

We have now combined this platform with chemical genetic and functional genomic approaches to understand the robustness of the genotype-to-phenotype map. Interactions with protein chaperones and other epigenetic modifiers percolated throughout the cellular network and impacted regulatory as well as protein-coding variation, revealing a mechanism for pervasive modification of the effects of polymorphisms. Understanding these effects will be crucial in designing genomes that result in robust phenotypes across cell types and through cell-fate decisions.