ABI Development: A Genomic Data Mining Resource to Accelerate Genome-to-Phenome Discovery in Domesticated Animals

ABI 开发：加速家养动物基因组到表型组发现的基因组数据挖掘资源

• 批准号: 1759896
• 负责人: Christine Elsik
• 金额: $ 86.98万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1759896&HistoricalAwards=false
• 关键词: ABI; Development; Genomic; Data; Mining

Research on domesticated animals has significant impacts on society. For example, species such as pig, sheep, chicken and dog are used to model human biology, leading to discoveries with implications in human health and well-being. Understanding the genetic basis of disease leads to improved health and welfare of companion animals. Farm animal research leads to improvement of traits related to animal health and production, ultimately enhancing global food sustainability. To accelerate scientific discovery in animal genetics, an international consortium called "FAANG" (Functional Annotation of Animal Genomes) aims to generate comprehensive maps of functional elements in genomes of domesticated animals. Data generated by FAANG will enhance the use of animal models in the biological and biomedical sciences. It will hasten discoveries in fundamental biology, as well as those that impact human health, animal well-being and agricultural production. In order for the FAANG effort to have substantial impacts on science and society, the data must be accessible to scientists and students of diverse disciplines. Effective use of the FAANG data will require data mining tools that enable easy search and retrieval, along with a workforce trained in areas such as bioinformatics and cyberinfrastructure.This project addresses the need for a high performance data mining resource that enables fine-grained querying and integrating the heterogeneous FAANG data with existing information, such as functions of known genes and research datasets. The specific aims of the project are to 1) develop FAANGMine - a high-performance data mining system that integrates genome assemblies and currently available annotation data for FAANG species, 2) extend FAANGMine by integrating new data generated by the FAANG Consortium, 3) create a FAANGMine user community that consists of students and scientists working on genetics of domesticated animal species. FAANGMine will empower animal researchers, with or without programming skills, to leverage the FAANG data in their research, thereby accelerating discoveries that elucidate the genetic basis of phenotypic variation. With the goal of fostering a FAANGMine user community, the proposed project will train over 30 graduate students and postdoctoral fellows through workshops and trainee visits with the FAANGMine developers. Moreover, undergraduate researchers will contribute to FAANGMine by developing demonstration projects. All trainees will have opportunities to work with data generated from cutting edge "omics" technologies, raising interest in STEM career pathways. The results of this project will be available at http://FAANGMine.org.This 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.

对驯养动物的研究对社会有重大影响。例如，猪、羊、鸡和狗等物种被用来模拟人类生物学，从而导致对人类健康和福祉产生影响的发现。了解疾病的遗传基础可以改善伴侣动物的健康和福利。农场动物研究导致改善与动物健康和生产相关的性状，最终提高全球粮食可持续性。为了加速动物遗传学的科学发现，一个名为“FAANG”（动物基因组功能注释）的国际联盟旨在生成驯养动物基因组中功能元件的综合图谱。FAANG产生的数据将加强动物模型在生物和生物医学科学中的应用。它将加速基础生物学的发现，以及那些影响人类健康，动物福利和农业生产的发现。为了使FAANG的努力对科学和社会产生实质性影响，数据必须向不同学科的科学家和学生开放。FAANG数据的有效利用将需要数据挖掘工具，使易于搜索和检索，随着劳动力的生物信息学和网络基础设施等领域的培训沿着。该项目解决了需要一个高性能的数据挖掘资源，使细粒度查询和集成的异构FAANG数据与现有的信息，如功能的已知基因和研究数据集。该项目的具体目标是：1）开发FAANGMine -一个高性能的数据挖掘系统，该系统集成了FAANG物种的基因组组装和当前可用的注释数据，2）通过整合FAANG联盟生成的新数据来扩展FAANGMine，3）创建一个FAANGMine用户社区，由从事驯养动物物种遗传学研究的学生和科学家组成。FAANGMine将使动物研究人员，无论是否具有编程技能，都能在他们的研究中利用FAANG数据，从而加速阐明表型变异遗传基础的发现。为了培养FAANGMine用户社区，拟议项目将通过与FAANGMine开发人员的研讨会和实习访问，培训30多名研究生和博士后研究员。此外，本科研究人员将通过开发示范项目为FAANGMine做出贡献。所有学员都将有机会使用尖端“组学”技术生成的数据，提高对STEM职业途径的兴趣。该项目的结果将在www.example.com上公布http://FAANGMine.org.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。