High-resolution study of adaptation in haploid and diploid populations of yeast

点击翻译按钮获取中文摘要

 DESCRIPTION (provided by applicant): 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.