This proposal is a resubmission of a renewal of R01 HG003328, """"""""Genome Plasticity and Evolution in de novo Yeast Species."""""""" In the previous funding cycle we developed new tools to interrogate hybrid genomes and analyze mitotically-proliferating cell populations undergoing adaptive evolution. Application of these tools has enlarged our mechanistic understanding of reproductive isolation, genome stability under selection, and clonal interference. We now seek to build upon these discoveries, and to answer, mechanistically, long-standing questions concerning how asexual populations explore adaptive landscapes, specifically: To what extent and by what mechanisms are evolutionary trajectories constrained across the adaptive landscape? Is the topography of that landscape different for haploids and diploids? Do the adaptive mutations that accumulate within a lineage interact additively, synergistically, or antagonistically? Do early-arising mutations constrain a lineage's subsequent evolvability? And, does prolonged adaptation to one environment limits an organism's ability to evolve in another? We propose four integrated aims that together will uncover fundamental aspects of adaptive evolution in a model eukaryote. Our discoveries can be generalized to all mitotically-proliferating cell lineages, including stems cells and cancers.
The Specific Aims of our proposal are: (1) to comprehensively analyze several independent evolving haploid lineages at the phenotypic and molecular levels;(2) to likewise analyze several independent evolving diploid lineages at the phenotypic and molecular levels;(3) to identify adaptive mutations and to establish the incidence and magnitude of higher-order interactions among such adaptive mutations that accumulate within lineages, and (4) to determine whether early-arising adaptive mutations, or the accumulation of multiple adaptive mutations constrains evolvability in a model Eukaryote.
In Specific Aim 1, we will follow up on our detailed molecular characterization of a yeast population that evolved under aerobic glucose limitation. We will combine ultra-high-throughput sequencing with our newly-developed, FACS-based method for following population dynamics, track the appearance of adaptive clones, and then precisely determine the molecular basis for the benefit conferred by each mutation.
In Specific Aim 2 we will essentially repeat this, but using diploid cells, to determine if the adaptive landscape is similar or different.
In Specific Aim 3, we will investigate the physiological and fitness effects that arise from combining individual mutations, and then sets of mutations, in a common genetic background.
In Specific Aim 4, we will build upon our work in Specific Aim 1, first testing how early-arising adaptive mutations constrain subsequent mutational and phenotypic trajectories, then testing whether the fittest clones we isolate at the end of long-term aerobic, glucose-limiting experiments are constrained, relative to their common ancestor, in their capacity to further evolve under anaerobic, glucose-limitation. The specific pair of environments in which we propose to address Question 4 is directly relevant to the study of cancer. Many highly proliferative tumors exist under hypoxic conditions and exhibit high glycolytic potential, relative to the cells from which they arose. As we will test the ability of cells evolved under glucose-limited oxic conditions to adapt to glucose-limited anoxic conditions, we expect to gain insight not only into the issue of evolvability, but also to discover multiple genetic mechanisms that enable a type of metabolic reprogramming that characteristically occurs in mitotically-proliferating tumor cells during the progression of cancer.

Public Health Relevance

Narrative Herein, we propose to analyze at the molecular level how haploid vs. diploid yeast respond to a given selective pressure, how adaptive mutations interact, and whether accumulation of such mutations limits a cell line's capacity to respond to a different type of selection. Because yeast is a model eukaryote, and because there are a great many genomic tools available for yeast, experimental evolutionary genomics using this model species has extraordinary potential to shed light on multiple biomedically-relevant evolutionary processes. Examples of such processes that occur in human somatic tissues are T cell response to infection, and tumor progression. Our discoveries may therefore be expected to positively impact human health.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG003328-06
Application #
8123467
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Felsenfeld, Adam
Project Start
2004-07-01
Project End
2013-07-31
Budget Start
2011-08-01
Budget End
2013-07-31
Support Year
6
Fiscal Year
2011
Total Cost
$562,841
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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
Sellis, Diamantis; Kvitek, Daniel J; Dunn, Barbara et al. (2016) Heterozygote Advantage Is a Common Outcome of Adaptation in Saccharomyces cerevisiae. Genetics 203:1401-13
Venkataram, Sandeep; Dunn, Barbara; Li, Yuping et al. (2016) Development of a Comprehensive Genotype-to-Fitness Map of Adaptation-Driving Mutations in Yeast. Cell 166:1585-1596.e22
Zhu, Yuan O; Sherlock, Gavin; Petrov, Dmitri A (2016) Whole Genome Analysis of 132 Clinical Saccharomyces cerevisiae Strains Reveals Extensive Ploidy Variation. G3 (Bethesda) 6:2421-34
Levy, Sasha F; Blundell, Jamie R; Venkataram, Sandeep et al. (2015) Quantitative evolutionary dynamics using high-resolution lineage tracking. Nature 519:181-6
Spor, Aymé; Kvitek, Daniel J; Nidelet, Thibault et al. (2014) Phenotypic and genotypic convergences are influenced by historical contingency and environment in yeast. Evolution 68:772-790
Rosenzweig, Frank; Sherlock, Gavin (2014) Experimental evolution: prospects and challenges. Genomics 104:v-vi
Blundell, Jamie R; Levy, Sasha F (2014) Beyond genome sequencing: lineage tracking with barcodes to study the dynamics of evolution, infection, and cancer. Genomics 104:417-30
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Chiotti, Kami E; Kvitek, Daniel J; Schmidt, Karen H et al. (2014) The Valley-of-Death: reciprocal sign epistasis constrains adaptive trajectories in a constant, nutrient limiting environment. Genomics 104:431-7

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