We will adapt 96 replicate populations of yeast (plus controls) to four environmental stressors for 1500 generations. Unlike a typical yeast/microbial experimental evolution experiment recombination will take place once every 30 generations during evolution. When evolution is complete, each population will be resequenced and the allele frequency of every SNP in the genome estimated at several time-points. Theory, preliminary data, and simulations suggest that the combination of an outbred population, recombination, 1500 generations of evolution, and 96-fold experimental replication will allow us to reliably identify a small number of Candidate Causative Polymorphisms (CCPs) as likely being causative. We will then use site-specific in vivo mutagenesis for 48 CCPs to prove a subset are causative. Experimental work will provide unprecedented insight into how adaptation takes place at the molecular level in outbred sexual species. The results of this work will significantly impact two broad areas of research. First, experiments will rigorously evaluate the ability of evolve and resequence (E&R) experiments to identify causative genes and sites important in adaptation at the molecular level. Furthermore, we will be able to empirically evaluate optimal experimental designs that will enable high power E&R experiments in other systems, as well as population genetics approaches designed to identify genetic signatures of adaptation in polymorphism/divergence data. Second we can directly address several long-standing questions regarding the molecular basis of adaptation. What is the role of standing variation versus de novo mutations in short-term adaptation? Are variants typically regulatory or coding? Is evolution from standing variation typically highly replicable (it isn't under asexual experimental evolution)? Or is evolution initially replicable, then much more heterogeneous? Are the selection coefficients associated with alleles involved in adaptation generally static or dynamic (i.e. does allele frequency change stall out)? Open sharing of all data and strains will allow the broader community to use this resource to empirically test other important hypotheses about the nature of adaptation in sexual outbreds.

Public Health Relevance

The bulk of heritable human disease is due to standing genetic variation. One intriguing hypothesis is that the genetic variation impacting complex diseases represents unintended trade-offs associated with past bouts of adaptation. A deeper understanding of how adaptation occurs at the molecular level may allow us to identify 'signatures' that we could look for in humans, and ultimately lead to better treatments and diagnoses. In this proposal we will 'trick' yeast into behaving as a sexual outbred, in order to test ideas about how adaptation occurs at the molecular level in diploid sexual like humans.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM115562-02
Application #
9143159
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Janes, Daniel E
Project Start
2015-09-15
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of California Irvine
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
046705849
City
Irvine
State
CA
Country
United States
Zip Code
92617
Baldwin-Brown, James G; Weeks, Stephen C; Long, Anthony D (2018) A New Standard for Crustacean Genomes: The Highly Contiguous, Annotated Genome Assembly of the Clam Shrimp Eulimnadia texana Reveals HOX Gene Order and Identifies the Sex Chromosome. Genome Biol Evol 10:143-156
Sanjak, Jaleal S; Long, Anthony D; Thornton, Kevin R (2017) A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets. PLoS Genet 13:e1006573
Mahdipour-Shirayeh, A; Darooneh, A H; Long, A D et al. (2017) Genotype by random environmental interactions gives an advantage to non-favored minor alleles. Sci Rep 7:5193
King, Elizabeth G; Long, Anthony D (2017) The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster. G3 (Bethesda) 7:1643-1652
Chakraborty, Mahul; Baldwin-Brown, James G; Long, Anthony D et al. (2016) Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage. Nucleic Acids Res 44:e147
Sanjak, Jaleal S; Long, Anthony D; Thornton, Kevin R (2016) Efficient Software for Multi-marker, Region-Based Analysis of GWAS Data. G3 (Bethesda) 6:1023-30
Baldwin-Brown, James G; Long, Anthony D; Thornton, Kevin R (2014) The power to detect quantitative trait loci using resequenced, experimentally evolved populations of diploid, sexual organisms. Mol Biol Evol 31:1040-55