Use of Phenotypic Traits as Metadata for Genome Databases

Phenotypes, often referred to as traits, are often the result of interactions between many genes. It is often possible to associate genetically mapped traits (QTL) to a single or a small list of candidate genes using sequence-based markers present on both the genetic and sequence maps. In many agronomically important crop and animal systems, there is often no well-developed genetic map and little or no QTL data although, due to the rapid decrease in costs, there is frequently an annotated genomic sequence. Thus projection of phenotypic data and orthologous sequences from more-studied species to less-described but important ones can be used to facilitate genetic improvement in these species. The use of trait-based queries can be an important tool to help leverage the data from well-studied systems. To this end the USDA-ARS Legume Clade Database group is employing the Soybean Trait Ontology developed by the SoyBase Database group (SoyBase.org) to allow trait-based queries for soybean data. Trait-based querying has two important features. First it allows more intuitive queries where users can ask for data related to an easily recognized and universal search term such as “drought” or "oleic acid". Whenever possible, database records in SoyBase have been tagged with trait terms. This allows a trait-based search to return everything in the database related to the search term (genes, metabolic pathways, QTL, publications, etc.). The search can also return data for related traits that were not an exact lexical match to the query string. For example, because oleic acid is a component of seed oil, related information on other oils is readily found using the structure of the underlying ontology. Trait-based queries will allow soybean data to be identified and subsequently projected onto other legume genome sequences such as those in the Legume Information System (LIS, LegumeInfo.org) and PeanutBase.orgusing sequence homologies. A description of trait-based querying at SoyBase and how the query results can be used in cross-species studies will be presented.