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: 1258053
• 负责人: Matthew Rutter
• 金额: $ 11.5万
• 依托单位: College of Charleston
• 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 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1258053&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。这项研究结合了下一代测序与经典的突变累积（MA）研究来描述序列水平的突变率。研究人员将采用全基因组测序来量化植物拟南芥的多种遗传背景中的突变率和突变谱。将对来源于拟南芥的哥伦比亚登录的100个MA系进行测序，这些MA系已经在六个自然田间环境中评估了性能。额外的测序将包括来自另外8组MA系中的每组的40个系，所述另外8组MA系从来自法国和瑞典的天然收集的创始者基因型建立，以及来自天然北美选择的50个系，所述天然北美选择已被鉴定为含有与在经典MA系中发现的突变相似的独特单倍型分组和突变趋异模式。这些数据将更准确地估计序列水平上自发突变的类型和速率，并使研究团队能够分解突变谱并将其与田间表现联系起来。这些数据集的综合将能够确定哪些类型的突变更有可能是有益的、有害的或中性的，以及某些类型的已识别突变的影响在不同环境中是否一致。有社会，科学和教育更广泛的影响，以提高我们对植物突变的理解。突变率在植物育种、预测杂草除草剂抗性的进化以及预测植物对主要环境变化（如气候变化）的进化反应中是重要的。本科生将有抢先体验序列数据和参与该项目的机会。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）如何使用描述真实的突变的数据库。