Cancer is a disease of adaptation in which some cells acquire beneficial mutations that allow them to proliferate within the body. Cancer, and adaptation in diploids in general, is driven by beneficial mutations that must be at least partly dominant to be detected by natural selection and might even be commonly overdominant in fitness (i.e. more beneficial as heterozygotes than as homozygotes). It is therefore likely that adaptation in diploids will be driven by a qualitatively different set of mutations than in haploid and might obey a qualitatively different set of rules. In order to understand the dynamics of adaptation in diploids and to contrast it with that of haploids it is necessary to (i) identify a lrge number of individual beneficial mutations in both haploids and diploids, (ii) determine their molecular nature, and (iii) measure their fitness with high precision in both heterozygotes and homozygotes. Unfortunately this has not been possible due to the difficulty of isolating more than a handful of large-effect beneficial mutations in any system. Here, we will use an ultra- high resolution barcoding system to uniquely tag hundreds of thousands of yeast cells making it possible to identify thousands of adaptive mutations in large haploid and diploid yeast populations (~108 cells/population). We will identify and measure the fitness, molecular nature, and heterozygous effects of hundreds of distinct beneficial mutations arising in the same environment in haploids and diploids. We will use these data to test theoretical predictions about dominance of adaptive mutations arising and spreading in haploids and diploids and will generate the first detailed joint distribution of molecular identity/fitness benefit/heterozygote effect of several hundred individual adaptive mutations. We anticipate that the insight gained from this project will (i) inform our understanding of adaptation in a regime - large populations - that is especially relevant for human diseases such as cancer and (ii) reveal the likely qualitatively different ways in which evolution proceeds in haploids and diploids.
Cancer is both deadly and difficult to treat because cancerous cells undergo rapid evolutionary adaptation in large populations. Using an innovative molecular tagging system we will be able to study adaptation in a high- throughput way in order to develop the quantitative and predictive understanding of adaptation necessary to understand and treat cancer.
| Li, Yuping; Venkataram, Sandeep; Agarwala, Atish et al. (2018) Hidden Complexity of Yeast Adaptation under Simple Evolutionary Conditions. Curr Biol 28:515-525.e6 |
| 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 |
| 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 |
| 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 |
| 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 |
