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Building resource-efficient community databases using open-source software.

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Developing integrated crop databases is crucial for utilizing big data in plant breeding. This study presents five community databases built using open-source tools to support genomics and genetics research.

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Area of Science:

  • Plant genomics and breeding
  • Bioinformatics and data management
  • Agricultural science

Background:

  • Big data in nonmodel crop species is rapidly increasing.
  • Existing crop databases face insufficient and intermittent funding, leading to underutilization of valuable data.
  • There is a critical need for efficient methods to build and maintain community databases for crop research.

Purpose of the Study:

  • To address the need for integrated database resources for crop genomics, genetics, and breeding research.
  • To describe the system and methods for constructing, curating, and analyzing data in community crop databases.
  • To provide access to data and tools through five established crop databases.

Main Methods:

  • Development of five crop databases over ten years using an open-source platform and software.
  • Implementation of data curation and analysis protocols.
  • Integration of diverse datasets relevant to crop research.

Main Results:

  • Successful establishment of five community crop databases: Genome Database for Rosaceae (GDR), Genome Database for Vaccinium (GDV), Citrus Genome Database (CGD), Pulse Crop Database (PCD), and CottonGen.
  • These databases provide curated data and analytical tools for researchers.
  • The open-source approach facilitates sustainable database development.

Conclusions:

  • The developed crop databases offer essential integrated resources for the genomics, genetics, and breeding communities.
  • Utilizing open-source technology provides an efficient and sustainable model for building community databases.
  • These databases will enhance the utilization of big data in crop improvement efforts.