Precise estimates of mutation rate and spectrum in yeast
Yuan O Zhu1, Mark L Siegal2, David W Hall3
1Department of Genetics, Stanford University, Stanford, CA 94305-5120;Department of Biology, Stanford University, Stanford, CA 94305-5020; yuanzhu@stanford.edu dpetrov@stanford.edu.
Summary
Mutation accumulation experiments in yeast reveal new insights into genetic variation. This study quantifies mutation rates and patterns, including indels and aneuploidies, providing a deeper understanding of genome evolution.
Area of Science:
- Genetics
- Evolutionary Biology
- Molecular Biology
Background:
- Mutation is the primary source of genetic variation.
- Mutation accumulation (MA) lines offer an unbiased method to study spontaneous mutations.
- Previous MA experiments were limited by sequencing costs, leading to imprecise mutation rate estimates.
Purpose of the Study:
- To identify spontaneous mutation events and estimate mutation rates using whole-genome sequencing in yeast.
- To investigate the contribution of different mutation classes (e.g., indels, aneuploidies) to large-effect mutations.
- To measure context-dependent mutation rates and identify patterns related to DNA sequence and methylation.
Main Methods:
- Utilized whole-genome sequencing of 145 diploid mutation accumulation (MA) lines in Saccharomyces cerevisiae.
- Accumulated approximately 1,000 spontaneous mutation events over ~311,000 generations.
- Analyzed mutation patterns, considering potential effects of mild selection on deleterious mutations.
Main Results:
- Identified nearly 1,000 spontaneous mutation events, providing precise estimates of mutation rates.
- Indels and aneuploidies (especially monosomies) were found to be disproportionately likely to cause large-effect mutations.
- Confirmed a strong AT bias in yeast mutations and detected context-dependent mutation rate increases at CpG sites, suggesting cytosine methylation's role.
Conclusions:
- This study provides the most comprehensive analysis of spontaneous mutations in yeast MA lines to date.
- The findings enhance our understanding of mutation processes, their impact on genetic variation, and the role of selection.
- The results offer valuable data for evolutionary genetics and the study of genome stability.
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