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United States Department of Agriculture

Agricultural Research Service

Title: Qtl Data at Maizegdb: Curation and "then Some"

Authors
item Schaeffer, Mary
item Baran, Sanford - IOWA STATE UNIVERSITY
item Lawrence, Carolyn

Submitted to: Maize Genetics Conference Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: January 20, 2006
Publication Date: March 9, 2006
Citation: Schaeffer, M.L., Baran, S.B., Lawrence, C.J. 2006. QTL data at maizeGDB: curation and "then some" [abstract]. 48th Annual Maize Genetics Conference Program and Abstracts. p. 231.

Technical Abstract: Discovery of candidate genes for agronomically important traits, such as disease or pest resistance often begins with one or more quantitative trait locus (QTL) experiments. Each experiment approximates the chromosomal locations sites (QTLs) that contribute to expression of the trait. These loci may not be detected in other QTL experiments, due either to environmental factors, and/or a lack of allelic diversity for a region in other mapping panels. Before devoting effort to marker assisted selections, or to candidate gene cloning, it would be helpful to have facile access to systematized information about all known QTLs for traits of interest, coupled to other information about germplasm, nearby loci, and sequence information. In the mid 90's, MaizeDB began curating QTL information from the literature. To permit this work to continue at MaizeGDB, a new, Web accessible curation interface has been designed and implemented. The new design accommodates a legacy trait hierarchy developed at MaizeDB and recently harmonized with the rice Trait Ontology at Gramene, and trait descriptors used by GRIN (the Germplasm Resources Information Network). It incorporates new utilities to facilitate and to control the quality of data entry. The curation module will be accessible to any maize cooperator wishing to add a new experiment to MaizeGDB. In addition to describing the curation tool, we will show a consensus map for several traits represented in MaizeGDB. We will report on our collaboration with Susan McCouch and staff at CIMMYT and GrainGenes towards a common template for entry of bulk QTL data for rice, maize, Triticeae and oats.

Last Modified: 11/27/2014
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