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，但其对进化的精确贡献仍然是生物学的基本问题。这项研究结合了下一个Gen测序与经典突变积累（MA）研究，以描述序列级突变率。研究人员将使用整个基因组测序来量化植物拟南芥多种遗传背景中突变的突变率和突变谱。测序将在拟南芥的哥伦比亚登录中得出的100个MA线进行，这些线已在六个自然野外环境中进行了评估。额外的测序将包括来自另外8组MA线的40条线，这些线路是由来自法国和瑞典的自然收集的创建者基因型确定的，以及已鉴定出的自然北美选择的50条线，其中包含与经典MA线相似的独特的单倍型分组和差异模式。这些数据将以更高的精度估算序列水平自发突变的类型和速率，并使研究团队能够分解突变的频谱并将其连接到现场性能。这些数据集的合成将确定哪些类型的突变更可能是有益，有害或中性的，以及某些类型的已识别突变的影响是否在环境中是否一致。社会，科学和教育对我们对植物突变的理解的更广泛影响。突变率在植物育种，预测杂草中除草剂耐药性的演化以及预测植物对重大环境变化（例如气候变化）的进化反应方面很重要。本科生将尽早访问序列数据，并有机会参加该项目。研究人员将开发一个基于网络的教育模块，该模块允许学生学习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以及4）如何使用描述真实突变的数据库。