Spontaneous mutations are the ultimate cause of genetic differences between individuals, and are therefore key to understanding the evolutionary process and many human diseases. However, the rates and patterns of mutation are difficult to measure because mutations are rare and are immediately subjected to natural selection. Recent advances in DNA sequencing technology, combined with the development of high- throughput assays of components of fitness, such as growth rate, present a unique opportunity to obtain a dramatically more precise and comprehensive view of the spectrum of spontaneous mutations. Mutation rates and patterns can be measured directly using mutation-accumulation (MA) lines, which are constructed in the laboratory by many generations of repeated population bottlenecking. The bottlenecks keep effective population size low and therefore prevent natural selection from purging deleterious mutations. In this project, a collection of 149 diploid MA lines of the genetically well-characterized yeast species, Saccharomyces cerevisiae, will be used. The lines were passaged for 2100 generations and therefore collectively capture over 300,000 cell divisions (600,000 replications of a haploid genome). Haploids have been used previously to estimate mutational spectra in yeast, but diploidy has several critical advantages, including better shielding of deleterious mutations, avoidance of genomic instability, and facilitation of downstream genetic analyses.
In Aim 1, the complete genome sequences of all 149 MA lines and their common ancestral line will be obtained using next-generation (Illumina) technology. This will yield almost two orders of magnitude more direct data on spontaneous mutations than previously achieved.
In Aim 2, genetic analysis will be performed to identify each diploid MA line that carries a highly deleterious mutation. For each such line, high-coverage sequencing of pooled haploid progeny will identify the highly deleterious mutation molecularly.
In Aim 3, high-throughput growth-rate assays will be performed on haploid progeny from each diploid MA line. The growth-rate assays will provide an estimate of the distribution of marginal fitness effects of spontaneous mutations. This will be a major advance because the rate of deleterious mutations is typically inaccessible to direct measurement, yet is a fundamental parameter in theoretical models of evolution. Moderately deleterious mutations will be identified molecularly by high-coverage sequencing of pooled haploid progeny.
In Aim 4, a collection of 96 haploid lines of mating-type a, each derived from a different diploid MA line, will be established, as a community resource for studying the effects of mutations on complex traits. The complete genotype of each line will be obtained by sequencing. For maximum utility, two sets of lines derived from these 96 lines will also be made: haploids of mating-type a and homozygous a/a diploids. This project will have an immediate and major impact on research in quantitative genetics, systems biology and evolutionary genetics and genomics, by accelerating future investigations of the links between mutations and their phenotypic effects.

Public Health Relevance

All genetic differences between cells, individuals, populations and species originate as mutations in their DNA. Accurate measurements of the rates at which different types of mutation occur are essential to understanding genetic variation at all levels, including variation associated with human diseases. This project will use strains of the genetically well-characterized yeast species, Saccharomyces cerevisiae, to obtain much more precise and informative estimates of mutation rates than are currently available;the project will also elucidate the genetic basis of a large number of spontaneous mutations that alter growth rate.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Eckstrand, Irene A
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New York University
Schools of Arts and Sciences
New York
United States
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