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

合作：RUI：突变的自然历史：来自拟南芥突变积累系的序列和适应度数据

• 批准号: 1257902
• 负责人: Charles Fenster
• 金额: $ 64.47万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1257902&HistoricalAwards=false
• 关键词: Collaborative; RUI; natural; history; mutations

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.

突变是遗传变异和生物多样性的来源，但它对进化的确切贡献仍然是生物学中的一个基本问题。本研究结合了下一代测序和经典突变积累（MA）研究来描述序列水平的突变率。研究人员将利用全基因组测序来量化拟南芥在多种遗传背景下的突变率和突变谱。将对来自哥伦比亚大学拟南芥的100个MA系进行测序，并对这些系在六种自然野外环境中的表现进行了评估。额外的测序将包括来自另外8组MA系的40个系，这些系是从法国和瑞典自然收集的创始基因型中建立的，以及来自北美自然选择的50个系，这些系已被确定包含独特的单倍型分组和与经典MA系相似的突变分化模式。这些数据将在序列水平上更准确地估计自发突变的类型和速率，并使研究小组能够分解突变谱，并将它们与现场表现联系起来。这些数据集的综合将能够确定哪些类型的突变更可能是有益的、有害的或中性的，以及某些类型的已识别突变的影响是否在不同的环境中是一致的。提高我们对植物突变的理解对社会、科学和教育都有更广泛的影响。突变率在植物育种、预测杂草抗除草剂的进化以及预测植物对气候变化等主要环境变化的进化反应方面具有重要意义。本科生将能较早地接触到序列数据，并有机会参与该项目。研究人员将开发一个基于网络的教育模块，让学生学习：1)突变的原因和类型；2)研究突变的策略；3)突变对进化和人类健康的重要性；4)如何使用描述真实突变的数据库。