# Toward a mechanistic understanding of genetic interactions > **NIH NIH R35** · UNIVERSITY OF WASHINGTON · 2024 · $532,915 ## Abstract A key challenge of the post-genomic era is the functional interpretation of the vast numbers of single nucleotide variants found in human genomes. This challenge is compounded by the fact that these variants contribute to complex traits and diseases by interacting with one another and with genetic variation in repetitive DNA elements. Assessing the phenotypic consequences of all genetic interactions amounts to an impossible numbers game. In order to prioritize certain variant combinations, I will use model organisms with powerful genetics, namely the yeast S. cerevisiae and the worm C. elegans, to identify and characterize genetic interactions with large impact on complex phenotypes. I propose three projects that capitalize on our previous studies. These projects are united by their focus on genetic interactions (i.e. epistasis), albeit they address different types of variant combinations and different mechanisms. The first project focuses on rDNA, a highly variable repetitive DNA element. Variation in rDNA copy number impacts gene expression, replication, genome stability, and mitochondrial abundance. Like other repetitive loci, rDNA is predisposed to interact epistatically with other variants because of its high mutation rate. Using newly developed C. elegans mapping populations and robotics-enabled phenotyping, our preliminary data show that rDNA copy number variation affects lifespan and fitness through epistasis. High-throughput analyses of healthspan traits such as stress resistance and fertility are ongoing. We will pursue fine-mapping of the most significant genomic loci implicated in epistasis with rDNA because their identity, possibly DNA replication or repair genes, may point to the molecular mechanism by which rDNA variation affects phenotype. In both yeast and worms, we will use the entire tool box of genetics and genomics to directly interrogate the pathways by which rDNA copy number variation affects replication, genome stability, and mitochondrial abundance. To enable accurate high-throughput measurements of rDNA copy number in model organisms and humans, we will optimize a promising FISH technology. The second project relies on the detailed genotype–phenotype maps we established for genes in the yeast mating pathway. Selecting single nucleotide variants of small and intermediate effects, we will combine variants in two genes and test the combinations for mating efficiency while also perturbing strong genetic modifiers and applying common stresses. To do so, we developed a sequencing strategy that allows us to simultaneously phenotype tens of thousands of single nucleotide variant combinations between pairs of genes. The third project will apply a technology of dominant negative polypeptides that we recently developed to identify at genome scale protein interaction surfaces and their dynamics. In yeast, we will explore to what extent genetic interactions reflect direct protein interactions. We will ask how easily (or not) protein ... ## Key facts - **NIH application ID:** 10869931 - **Project number:** 5R35GM139532-04 - **Recipient organization:** UNIVERSITY OF WASHINGTON - **Principal Investigator:** Christine Queitsch - **Activity code:** R35 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $532,915 - **Award type:** 5 - **Project period:** 2021-06-01 → 2026-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10869931 ## Citation > US National Institutes of Health, RePORTER application 10869931, Toward a mechanistic understanding of genetic interactions (5R35GM139532-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10869931. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*