Improving Plant Breeding in Polyploid Crops Using Models for Demography and Selection

利用人口统计学和选择模型改进多倍体作物育种

• 批准号: 1811784
• 负责人: Paul Blischak
• 金额: $ 21.6万
• 依托单位: Blischak Paul D
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1811784&HistoricalAwards=false
• 关键词: Improving; Plant; Breeding; Polyploid; Crops

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2018. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Dr. Paul Blischak is "Improving Plant Breeding in Polyploid Crops Using Models for Demography and Selection." The host institution for the fellowship is the University of Arizona and the sponsoring scientists are Drs. Michael Barker and Ryan Gutenkunst.The process of domestication impacts levels of genetic diversity through the selection of individuals with desirable characteristics. Discovering what genes are associated with these agriculturally important traits can therefore be difficult as a result of this initial population bottleneck. Many agricultural species also have additional sets of chromosomes as a result of whole genome duplication (polyploidy), further complicating genetic analyses. This project focuses on the development of computational tools to identify domestication-related genes for crop improvement in polyploid species. These methods will be applied to canola (Brassica napus), an economically important polyploid crop responsible for the production of vegetable and synthetic oils, livestock feed, and biofuels. Training objectives include the development of statistical and computational methods and their application to the improvement of plant breeding efforts in polyploid crops. Broader impacts include the development of open-source software, tutorials, and teaching materials that can be used by plant breeders and educators.Tools for the analysis of genome-wide DNA sequence data that aim to understand the process of domestication in polyploid crops are generally lacking. The main goals of this research are (1) to develop statistical models for the analysis of historical demography in polyploid crops, (2) to use these methods to infer the demographic history of B. napus, and (3) to leverage this demographic information to better identify domestication-related genes. This will be achieved through the implementation of new models in the Python package DaDi (Diffusion Approximation for Demographic Inference), applying these models to B. napus, and using the results to perform genome-scale simulations for the identification of genes under positive selection. All data, scripts, and protocols for this project will be made available in public repositories, and all software will be freely available and open source. Keywords: Brassica, canola, demography, domestication, polyploidy, selectionThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一行动为NSF国家植物基因组计划2018财年生物学博士后研究奖学金提供了资金。该奖学金支持在东道主实验室为该研究员制定的研究和培训计划，该研究员还提出了扩大生物学参与度的计划。为Paul Blischak博士提供的这项研究和培训计划的标题是“使用人口学和选择模型改进多倍体作物的植物育种”。该奖学金的主办机构是亚利桑那大学，赞助科学家是Michael Barker博士和Ryan Gutenkunst博士。驯化过程通过选择具有理想特征的个体来影响遗传多样性水平。因此，由于最初的种群瓶颈，发现哪些基因与这些农业重要特征有关可能是困难的。由于全基因组复制(多倍体)，许多农业物种还拥有额外的染色体组，这进一步增加了遗传分析的复杂性。这个项目的重点是开发计算工具来识别与驯化相关的基因，用于多倍体物种的作物改良。这些方法将应用于油菜(Brassica Napus)，这是一种重要的经济多倍体作物，负责生产植物油和合成油、牲畜饲料和生物燃料。培训目标包括发展统计和计算方法，并将其应用于改进多倍体作物的植物育种工作。更广泛的影响包括开发可供植物育种者和教育者使用的开源软件、教程和教材。旨在了解多倍体作物驯化过程的全基因组DNA序列数据分析工具普遍缺乏。本研究的主要目的是(1)建立用于分析多倍体作物历史人口学的统计模型，(2)使用这些方法来推断甘蓝型油菜的人口学历史，以及(3)利用这些人口学信息来更好地识别与驯化相关的基因。这将通过在Python包DADI(人口统计推断的扩散近似)中实施新的模型来实现，将这些模型应用于甘蓝型油菜，并使用结果来执行基因组规模的模拟，以识别正选择下的基因。该项目的所有数据、脚本和协议将在公共存储库中提供，所有软件将免费提供和开放源码。关键词：油菜籽、油菜籽、人口学、驯化、多倍体、选择该奖项反映了NSF的法定使命，通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。