# Pleiotropy: patterns, mechanisms, and evolutionary consequences

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $306,032

## Abstract

PROJECT SUMMARY
The long-term objective of the PI's research program is to understand the molecular genetic mechanisms and
driving forces of phenotypic variation and evolution. Pleiotropy is one of the most common yet least understood
phenomena in genetics. It refers to the observation that one mutation impacts multiple phenotypic traits.
Pleiotropy may be concordant or antagonistic, depending on whether the mutational effects on multiple traits
are in the same or opposite directions (when the directions are alignable). Pleiotropy, especially antagonistic
pleiotropy, is widely invoked in explanations and models of senescence, cancer, genetic disease, sexual
conflict, cooperation, evolutionary constraint, adaptation, neofunctionalization, and speciation, among other
things. This project addresses three key gaps in our understanding of pleiotropy: patterns, mechanisms, and
evolutionary consequences. First, while the environmental pleiotropy of null mutations has been extensively
studied, the same is not true for non-null mutations. This project will use a high-throughput method to
determine the in vivo fitness landscapes of one yeast RNA gene and four protein genes in 12 environments.
Each landscape will include >20,000 genotypes, providing unprecedentedly large data for inducing general
principles of environmental pleiotropy. More importantly, these data will allow inferring fitness effects of
mutations in one environment from those in another, which will be instrumental in explaining and predicting
evolution in nature. Second, while pleiotropy is typically studied from the perspective of mutations, the other
side of the coin is the relationship between phenotypic traits that are often impacted by the same mutations.
Maximum growth rate r and carrying capacity K of density-dependent population growth are key life-history
traits fundamental to many ecological and evolutionary theories and are directly relevant to combating
pathogens and tumors. Although r and K are generally thought to be negatively correlated, both r-K tradeoffs
and "tradeups" have been observed. However, neither the conditions under which each of these relationships
occur nor the causes of these relationships are well understood. These questions will be addressed in yeast by
mapping quantitative trait loci influencing r and K and estimating the r and K of 500 single-gene deletion strains
in multiple environments, followed by modeling of biological processes impacting r and K. Third, if mutations
with large benefits in one environment are generally deleterious in other environments, a population adapting
to a changing environment may have few adaptive substitutions, despite continuous and strong selections.
This project will test the above hypothesis using experimental evolution of yeast in constant vs. changing
environments. If supported, this hypothesis will profoundly alter our interpretation of the
nonsynonymous/synonymous substitution rate ratio estimated from intra and inter...

## Key facts

- **NIH application ID:** 9993534
- **Project number:** 5R01GM103232-06
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** JIANZHI ZHANG
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $306,032
- **Award type:** 5
- **Project period:** 2013-09-01 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993534

## Citation

> US National Institutes of Health, RePORTER application 9993534, Pleiotropy: patterns, mechanisms, and evolutionary consequences (5R01GM103232-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9993534. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*