Collaborative: RUI: The natural history of mutations: sequence and fitness data from Arabidopsis thaliana mutation accumulation lines

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Mutation is the source of genetic variation and organismal diversity, yet its precise contribution to evolution remains a fundamental problem in biology. This study combines next gen sequencing with classical mutation accumulation (MA) studies to describe sequence-level mutation rates. The researchers will employ whole genome sequencing to quantify the mutation rate and the spectrum of mutations in multiple genetic backgrounds of the plant Arabidopsis thaliana. Sequencing will be done on 100 MA lines derived from the Columbia accession of Arabidopsis thaliana, which have been assessed for performance in six natural field environments. Additional sequencing will include 40 lines from each of 8 additional sets of MA lines, established from naturally-collected founder genotypes from France and Sweden, and 50 lines from natural North American selections that have been identified to contain a unique haplotype grouping and divergence pattern of mutations similar to that found in classical MA lines. These data will estimate with much greater accuracy the type and rates of spontaneous mutation at the sequence level and will allow the research team to decompose the spectrum of mutations and connect them to field performance. The synthesis of these datasets will enable the determination of which types of mutations are more likely to be beneficial, deleterious or neutral, and whether the effects of certain types of identified mutations are consistent across environments. There are societal, scientific and educational broader impacts to improving our understanding of mutations in plants. Mutation rates are important in plant breeding, in predicting evolution of herbicide resistance in weeds, and in predicting evolutionary responses of plants to major environmental changes such as climate change. Undergraduate students will have early access to sequence data and the opportunity to participate in the project. The researchers will develop a web-based educational module that allows students to learn 1) the causes and types of mutation 2) strategies for studying mutation 3) the importance of mutation to evolution and to human health and 4) how to use databases describing real mutations.