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.
