# Understanding predictability of evolutionary trajectories

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $382,696

## Abstract

Work over the last decade has provided tantalizing clues that the genetic mechanisms that underlie
evolutionary trajectories may be more constrained and deterministic than previously appreciated.
Whether the genetic basis of evolution is predictable or stochastic is a fundamental question in
evolutionary biology, and the ability to predict evolutionary responses has critical implications for the
fields of agriculture, medicine and conservation. Unfortunately, we are far from understanding the
factors that underlie the predictability of evolutionary responses or the fitness consequences
associated with alternative evolutionary trajectories in nature. Surveys of replicate populations
adapting to the same environmental conditions provide an opportunity to quantify the repeatability of
evolutionary trajectories and determine the factors affecting observed patterns of variation. Several
genetic factors are hypothesized to affect the probability of a gene or mutation’s use during the
process of adaptation. However, to date there have been few empirical tests determining the
contribution of individual factors to patterns of gene re-use (parallelism) in natural populations.
 In the proposed work, we built upon our prior findings and combine innovative population
genomics, genetic engineering, and experiments to answer three core biological questions: 1)
How does parallelism translate across biological levels? 2) Which genetic factors affect
parallelism? 3) What are the fitness consequences associated with genetically distinct, yet
phenotypically similar, evolutionary trajectories? Our laboratory is well positioned to answer
these profoundly important questions about the repeatability and predictability of evolutionary
trajectories. Our model system for addressing these questions is the threespine stickleback
(Gasterosteus aculeatus), a species with bountiful genetic and genomic resources. Stickleback are
considered a textbook example of parallel phenotypic evolution; thousands of independently derived
stickleback populations have repeatedly adapted to a variety of freshwater environments. We will
survey several focal freshwater populations to examine the scaling of papalism across biological
levels and to test whether the source and type of genetic variation or epistatic interactions predict the
frequency of gene use during adaptation. The creation of genetically modified lines that differ only in
their allele frequencies at candidate loci will allow us to test whether fitness coefficients can predict
the probability of gene use (magnitude of genetic parallelism) in nature. Together this work will test
several fundamental evolutionary questions and take a first step toward determining whether the
development of a predictive evolutionary framework is possible.

## Key facts

- **NIH application ID:** 10897323
- **Project number:** 5R35GM151058-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Diana Jessie Rennison
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $382,696
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10897323

## Citation

> US National Institutes of Health, RePORTER application 10897323, Understanding predictability of evolutionary trajectories (5R35GM151058-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10897323. Licensed CC0.

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