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Title: Breeder survey, tools, and resources to visualize diversity and pedigree relationships at MaizeGDB

item Sen, Taner
item BRAUN, BREMEN - Oak Ridge Institute For Science And Education (ORISE)
item SCHOTT, DAVID - Iowa State University
item Portwood, John
item Schaeffer, Mary
item Harper, Elisabeth
item GARDINER, JACK - Iowa State University
item CANNON, ETHALINDA - Iowa State University
item Andorf, Carson

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 1/16/2016
Publication Date: 3/17/2016
Citation: Sen, T.Z., Braun, B.L., Schott, D.A., Portwood II, J.L., Schaeffer, M.L., Harper, E.C., Gardiner, J.M., Cannon, E.K., Andorf, C.M. 2016. Breeder survey, tools, and resources to visualize diversity and pedigree relationships at MaizeGDB. In: 58th Annual Maize Genetics Conference, March 17-20, 2016, Jacksonville, Florida. p. 63.

Interpretive Summary:

Technical Abstract: In collaboration with maize researchers, the MaizeGDB Team prepared a survey to identify breeder needs for visualizing pedigrees, diversity data, and haplotypes, and distributed it to the maize community on behalf of the Maize Genetics Executive Committee (Summer 2015). We received 48 responses from researchers, of which more than half were self-identified as breeders. The researchers established their top priorities for visualization as: 1) SNPs in a region for a given list of lines, 2) haplotype analysis in a given list of lines, and 3) pedigree relationships. The survey identified the following two populations as the most beneficial to visualize: 1) 3000 inbred lines as described in Romay et al. (Genome Biol, 14:R55, 2013), and 2) Expired PVP lines (Plant Variety Protection Act). Driven in part by this stakeholder input, MaizeGDB are currently working in four areas: 1) Displaying immediate progenies of current stocks at the MaizeGDB Stock pages, 2) Curating the most recent ex-PVP lines listed in GRIN into MaizeGDB and displaying them on the MaizeGDB Stock pages, 3) Developing network views of pedigree relationships, and 4) Visualizing genotypes from diversity datasets.