Adaptation is the central concept in evolution and biology in general.
I aim to build and quantitative and predictive theory of the adaptive process by focusing on interrelated empirical, computational, and theoretical studies of rapid adaptation in a range of systems. The MIRA grant will be supporting three specific umbrella projects that focus on: (i) inference of the dynamics of adaptation from genomic data, (ii) studies of rapid seasonal adaptation in Drosophila, and (iii) high throughput studies of adaptive mutation in experimental evolution studies in yeast.

Public Health Relevance

Evolutionary adaptation is the central concept in biology and is at the heart of many problems facing humanities such as cancer and infectious disease. Using a series of interrelated projects Petrov lab will pursue research aimed at building a predictive and quantitative theory of adaptation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM118165-01
Application #
9071712
Study Section
Special Emphasis Panel (ZGM1-TRN-7 (MR))
Program Officer
Janes, Daniel E
Project Start
2016-06-01
Project End
2021-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
1
Fiscal Year
2016
Total Cost
$712,354
Indirect Cost
$261,497
Name
Stanford University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Li, Yuping; Venkataram, Sandeep; Agarwala, Atish et al. (2018) Hidden Complexity of Yeast Adaptation under Simple Evolutionary Conditions. Curr Biol 28:515-525.e6
Rogers, Zoë N; McFarland, Christopher D; Winters, Ian P et al. (2018) Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice. Nat Genet 50:483-486
Enard, David; Petrov, Dmitri A (2018) Evidence that RNA Viruses Drove Adaptive Introgression between Neanderthals and Modern Humans. Cell 175:360-371.e13
Behrman, Emily L; Howick, Virginia M; Kapun, Martin et al. (2018) Rapid seasonal evolution in innate immunity of wild Drosophila melanogaster. Proc Biol Sci 285:
Assaf, Zoe June; Tilk, Susanne; Park, Jane et al. (2017) Deep sequencing of natural and experimental populations of Drosophila melanogaster reveals biases in the spectrum of new mutations. Genome Res 27:1988-2000
Winters, Ian P; Chiou, Shin-Heng; Paulk, Nicole K et al. (2017) Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity. Nat Commun 8:2053
Zhu, Yuan O; Sherlock, Gavin; Petrov, Dmitri A (2017) Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum. PLoS Genet 13:e1006455
Rogers, Zoë N; McFarland, Christopher D; Winters, Ian P et al. (2017) A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo. Nat Methods 14:737-742
Wittmann, Meike J; Bergland, Alan O; Feldman, Marcus W et al. (2017) Seasonally fluctuating selection can maintain polymorphism at many loci via segregation lift. Proc Natl Acad Sci U S A 114:E9932-E9941
Feder, Alison F; Kline, Christopher; Polacino, Patricia et al. (2017) A spatio-temporal assessment of simian/human immunodeficiency virus (SHIV) evolution reveals a highly dynamic process within the host. PLoS Pathog 13:e1006358

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