# A quantitative examination of cellular mechanisms that modulate the impacts of genetic variation

> **NIH NIH R35** · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · 2022 · $371,447

## Abstract

Project summary
One of the biggest challenges in quantitative genetics and evolutionary biology is that the
phenotypic effects of genetic change differ across environments and genetic backgrounds. This
makes it more difficult to identify the genetic basis of complex traits and to predict whether
evolution will proceed via the same genetic changes when faced with similar selection
pressures. When mutations have context-dependent effects, it can also lead to fundamental
problems with reproducibility in biological research. My lab’s goal is to shed light on context-
dependency by drawing insights from cell biology. We hypothesize that basic properties of cells
can change the phenotypic impacts of mutation in predictable ways, and that trends exist that
explain how specific types of mutations interact with specific types of environmental or genetic
perturbations. In the next five years, we will quantify how the impact of genetic change on
budding yeast’s growth rate is modulated by (1) other genes participating in the same regulatory
network, and (2) accumulation of toxic misfolded proteins in cells. We will engineer large
numbers of yeast strains that differ by single point mutations and quantify the impact of these
mutations on cell growth as we systematically change the genetic background (i.e. impair each
gene in the network, one at a time) or the environment (incrementally increase levels of a stress
that destabilizes protein folding). This strategy – re-measuring the impacts of many mutations as
we slowly and systematically perturb systems – gives us power to distinguish consistent trends
that describe how the impact of mutations depends on context. It feasible and cost-effective to
measure the impact of thousands of mutations across hundreds of systematic perturbations due
to recent advances in yeast genetics (e.g. modifications to the CRISPR system and DNA
barcoding approaches). The trends describing how particular types of mutations respond to
particular types of perturbations will allow us to make, and to test, predictions about (1) how the
impacts of untested mutations will change depending on context, and (2) ranges of conditions in
which laboratory evolution experiments will proceed via similar genetic changes. Overall, this
research direction will result in a mechanistic and quantitative understanding of one of biology’s
most challenging questions: how the impacts of mutation depend on context.

## Key facts

- **NIH application ID:** 10431832
- **Project number:** 5R35GM133674-04
- **Recipient organization:** ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- **Principal Investigator:** Kerry A Geiler-Samerotte
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $371,447
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10431832

## Citation

> US National Institutes of Health, RePORTER application 10431832, A quantitative examination of cellular mechanisms that modulate the impacts of genetic variation (5R35GM133674-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10431832. Licensed CC0.

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