Title
Gramene QTL database: development, content and applications.
Abstract
Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene-phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research.
Year
DOI
Venue
2009
10.1093/database/bap005
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Keywords
Field
DocType
biomedical research,bioinformatics,databases
Data mining,Association mapping,Quantitative trait locus,Data domain,Candidate gene,Computer science,Functional genomics,Data type,Bioinformatics,Database
Journal
Volume
Issue
ISSN
2009
0
1758-0463
Citations 
PageRank 
References 
6
0.60
6
Authors
14
Name
Order
Citations
PageRank
Junjian Ni18716.24
anuradha pujar248131.83
Ken Youens-Clark314117.11
Immanuel Yap47110.30
Pankaj Jaiswal518030.06
Isaak Tecle6364.92
Chih-Wei Tung7728.35
Liya Ren87610.54
S. White9701161.53
Xuehong Wei10757.85
Shuly Avraham11588.82
Doreen Ware1226836.91
Lincoln D. Stein131555247.25
Susan McCouch1414020.77