# Genetic interactions and the evolution of complex traits in yeast

> **NIH NIH R35** · LEHIGH UNIVERSITY · 2024 · $249,188

## Abstract

Below is the original Summary to fill this Mandatory Field
PROJECT SUMMARY/ABSTRACT
 Adaptive evolution is a fundamental process in biology. At its simplest random mutation produces
phenotypic variation on which selection acts, enriching for favorable phenotypes and purging the less-
favorable ones. This process has produced the diversity of life on Earth. Yet at the same time, adaptive
evolution is responsible for some of the most vexing problems in human health, from the growing problem
of antibiotic resistance to real-time evolution of viral pathogens to cancers that resist drug treatments and
evade the immune system. Despite this, we lack a basic mechanistic understanding of how genomes
respond to selection. One major unknown is how adaptive evolution “chooses” one particular path from
among a vast number of possible ones. Another major unknown is how genetic variation produces new
phenotypes on which selection acts. Experimental Evolution provides a way forward to address both of
these significant gaps in our knowledge. With advances in high-throughput biology we can evolve hundreds
of initially identical populations in parallel for thousands of generations, with exquisite control over
experimental parameters. This versatile technique makes it possible to test evolutionary theory through
experiments that are impossible to perform in natural populations. At the same time, experimental evolution
is powerful tool for functional genomics. By identifying the genes and pathways that respond to selective
pressures, and how these mutations interact to alter phenotype, laboratory evolution experiments identify
previously unknown cellular connections. In the past five years my laboratory has advanced a mechanistic
understanding of adaptive evolution. Future work will determine how genetic changes give rise to complex
phenotypes. We will perform evolution experiments following perturbation of the genetic background and
in shifting environments. In addition to advancing our understanding of adaptive evolution, we expect,
based on our prior work, to identify previously unknown nuclear-nuclear, nuclear-cytoplasmic, and gene-
environment interactions. Finally, we will develop a fast and reliable method for performing multiple rounds
of pooled gene editing in yeast, and we will use this method to systematically assay genetic interactions
that have been missed by other methods. By connecting genotype to phenotype in an evolutionary context,
our work will provide a mechanistic understanding of how complex traits evolve. This work will advance
our understanding of adaptive evolution and the genetic basis of complex traits in less tractable systems,
including humans and human pathogens.

## Key facts

- **NIH application ID:** 11032925
- **Project number:** 3R35GM149540-02S1
- **Recipient organization:** LEHIGH UNIVERSITY
- **Principal Investigator:** Gregory I Lang
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $249,188
- **Award type:** 3
- **Project period:** 2023-05-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11032925

## Citation

> US National Institutes of Health, RePORTER application 11032925, Genetic interactions and the evolution of complex traits in yeast (3R35GM149540-02S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/11032925. Licensed CC0.

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