Tripal, a community update after 10 years of supporting open source, standards-based genetic, genomic and breeding databases

Abstract

Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles.

The banana genome hub: a community database for genomics in the Musaceae

“…From a technical perspective, the BGH core has been developed with the Tripal toolkit (i.e. Drupal v7, Tripal v3), an open-source project supporting the development of biological databases [ 8 , 35 , 36 ] complemented by the development of additional modules [ 37 ]. All these elements are further described below.…”

“…Users have multiple ways to search for genes in the system, either using a gene locus (or a list of them), keywords, genomic coordinates powered by MegaSearch [ 38 ] or using the BLAST graphical interface searches from Sequenceserver [ 39 ] ( Figure 2A ). Results are connected to genome browsers [ 37 ] specific to each genome. Comparisons between genomes are facilitated by tracks showing gene annotations projected on other genomes using the lift-over tool.…”

CottonGen: The Community Database for Cotton Genomics, Genetics, and Breeding Research

“…To facilitate the utilization of cotton research data in basic discovery, translation, and crop improvement, CottonGen, over the last decade, has focused on integrating new whole genomic data with transcriptomic, genetic map, genetic marker, trait locus, phenotypic, and genotypic data. To accommodate the data mining needs that came with these new types and large volumes of data, various web interfaces were developed by the CottonGen team, such as MegaSearch [68], MapViewer [63], BIMS [13], Chado Loader, Chado Data Display, and Chado Search modules [69], or Tripal modules that other database teams developed such as the Synteny Viewer and Tripal BLAST [8]. The open-source database platform Tripal allows database teams to meet emerging demands for storage, querying, and the display of new data types more efficiently and quickly.…”

“…In addition, it began hosting the website of the International Cotton Genome Initiative (ICGI), a non-profit organization working to increase knowledge of the structure and function of the cotton genome for the benefit of the global community. The CottonGen database is constructed using the open-source Tripal genome database toolkit [6][7][8], which merges the power of Drupal, a popular web content management system, with that of Chado [9,10], a community-derived database schema for the storage of genomic, genetic, and breeding data [2].…”

Ten simple rules for developing visualization tools in genomics

“…When time and resources allow, making a popular tool available on several platforms and programming languages is a good option for sustainability. JBrowse is a good illustration since it is available in both web and desktop versions [ 5 ], can be embedded in large genome portals as a Drupal module [ 46 ], has an R markdown and R Shiny compliant version (JBrowseR [ 47 ]), and exists as a Jupyter package [ 48 ].…”