P0952 Gramene Genetic Diversity Module: A Plant Genotype-Phenotype Association Data Repository

Jon Zhang , Cornell University, Ithaca, NY
Genevieve DeClerck , Cornell University/Gramene.org, Ithaca, NY
Athikkattuvalasu Karthikeyan , Cornel University, Wheeling, IL
Shuly Avraham , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Terry Casstevens , Cornell University, Apex, NC
Charles Chen , Cornell University, Ithaca, NY
Jer-Ming Chia , Cold Spring Harbor Labs, Cold Spring Harbor, NY
Ken Youens-Clark , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Aaron Chuah , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Paul Derwet , European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
Shiran Pasternak , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Liya Ren , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
William Spooner , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Joshua Stein , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Jim Thomason , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Qi Sun , Cornell University, Ithaca, NY
Sharon Wei , Cold Spring Harbor Laboratory, Cold Spring Harbor, NY
Pankaj Jaiswal , Oregon State University, Corvallis, OR
Doreen Ware , Cold Spring Harbor Laboratory-USDA-ARS, Cold Spring Harbor, NY
Edward S. Buckler , USDA-ARS-Cornell University, Ithaca, NY
Susan McCouch , Cornell University, Ithaca, NY
Identifying genotypic variation has become a routine procedure given the increasing number of high-throughput sequencing and array-based genotyping technologies. However, it is still a challenge for the plant research community to associate this data with phenotypic variation. More specifically, groups attempting to illuminate genotypic-phenotypic associations are encountering bottlenecks in areas of data post-processing, data storage, computationally intense analysis of results. The Gramene Genetic Diversity Module is designed to help overcome these challenges. Using the Genomic Diversity and Phenotype Data Model (GDPDM;maizegenetics.net/gdpdm), this module of Gramene is able to compress genotype data by several orders of magnitude facilitating integration and analysis of genotypic and phenotypic data. Gramene Diversity currently hosts a number of important variation datasets for rice, maize, Arabidopsis, sorghum, and wheat. Recent curational activity has been on large-scale SNP genotype datasets in rice, maize and Arabidopsis, with associated phenotype data assigned to ontology term. New terms are created when necessary. In addition to the data, Gramene Diversity offers several options for querying, analyzing, and bulk downloading of the data. Recently we have added a GWAS results visualization tool (www.gramene.org/db/jshc2010), our newest addition to an array of analytical options. Gramene Diversity is updated twice a year as part of the biannual Gramene release, the latest of which (Build 34) was in the Fall of 2011.