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

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有影响的发现。了解疾病的遗传基础可以改善伴侣动物的健康和福利。农场动物研究可以改善与动物健康和生产有关的性状，最终提高全球粮食的可持续性。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化动物基因组中功能元素的综合图谱。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重大影响，这些数据必须可供不同学科的科学家和学生使用。FAANG数据的有效使用将需要能够轻松搜索和检索的数据挖掘工具，以及在生物信息学和网络基础设施等领域受过培训的工作人员。该项目解决了对高性能数据挖掘资源的需求，该资源能够对异构FAANG数据进行细粒度查询，并将其与现有信息（如已知基因的功能和研究数据集）集成。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，它集成了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)创建一个由从事家养动物物种遗传学研究的学生和科学家组成的FAANGMine用户社区。FAANGMine将使动物研究人员，无论是否具备编程技能，都能在他们的研究中利用FAANG数据，从而加速发现阐明表型变异的遗传基础。为了培养一个FAANGMine用户社区，该项目将通过与FAANGMine开发者的研讨会和实习生访问来培训30多名研究生和博士后。此外，本科生研究人员将通过开发示范项目为FAANGMine做出贡献。所有受训人员都将有机会使用由尖端“组学”技术生成的数据，提高对STEM职业道路的兴趣。该项目的结果将在http://FAANGMine.org.This上公布，该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.