# Genomics of rapid adaptation in the lab and in the wild

> **NIH NIH R35** · STANFORD UNIVERSITY · 2023 · $249,828

## Abstract

Project Summary
Adaptation is the foundational concept in biology. My lab aims to build an empirically and theoretically rich theory
of adaptation. We focus specifically on the inference of adaptation from genomic data and on the study of rapid
evolution in real time. The latter include (i) experimental evolution in yeast (adaptation by de novo mutation in
well-mixed clonal system), (ii) adaptation on seasonal and ecological time-scales in Drosophila (adaptation from
standing variation in a obligately sexual organism), and (iii) inference of adaptation from well resolved population
genomic and phylogenetic data. These projects utilize a diversity of systems, high throughput and well-powered
experimental modalities, and sophisticated and varied analytic frameworks, but they all focus on the overarching
need to understand the dynamics of rapid adaptation. The reduction in the cost of sequencing is making it
possible and imperative to increase the resolution through the increase in the number of replicates and this in
turn requires the application of liquid handling robotic systems as the one I am requesting here.

## Key facts

- **NIH application ID:** 10794860
- **Project number:** 3R35GM118165-08S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Dmitri Petrov
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $249,828
- **Award type:** 3
- **Project period:** 2016-06-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10794860

## Citation

> US National Institutes of Health, RePORTER application 10794860, Genomics of rapid adaptation in the lab and in the wild (3R35GM118165-08S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10794860. Licensed CC0.

---

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