Advance Search              Latest Recources





















Showing search results (1–1 of 1):

  1. PlantQTL-GE (View Publication)
    Full Name of the Resource : QTL based candidate gene identification and gene function analysis
    Resource Category : Databases -> Plant Databases -> Rice

    Brief Description : Quantitative trait locus analysis is an effective method for locating chromosomal regions harboring genetic variants that affect a continuously distributed, polygenic phenotype. However, the identification of genes affecting complex traits is one of the most difficult task in genetics. Here we introduced a database system, called PlantQTL-GE, to facilitate QTL based candidate gene identification and gene function analysis. We collected a large number of genes, gene expression information in microarray data and ESTs, and genetic markers from multiple sources of Oryza sativa and Arabidopsis thaliana. The system integrates these diverse data sources and has a uniform web interface for easy access. It supports QTL queries specifying QTL marker intervals or genomic loci, and displays, on rice or Arabidopsis genome, known genes, microarray data, ESTs and candidate genes and similar putative genes in the other plant. Candidate genes in QTL intervals are further annotated based on matching ESTs, microarray gene expression data and cis-elements in regulatory sequences. The system is freely available at http://www.scbit.org/qtl2gene/new/.
    Subject Area : Rice Genome Identification


    Institute/s :
    Shanghai Center for Bioinformation Technology, Shanghai, China
    Address of Institute/s :
    Shanghai Center for Bioinformation Technology, Shanghai 200235, China
    Country : China

    Associated Institutes :

    • School of Life Sciences, Fudan University, Shanghai, 200433, China
    • Shanghai Agro-Biological Gene Center, Shanghai 201106, China
    • Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
    • Shanghai Center for Bioinformation Technology, Shanghai 200235, China

    Associated Country : China; USA


    Authors/Contributors : Zhong, Y.
    Contact Email : yangzhong@fudan.edu.cn
    Year : 2007
    Language : English

    Keywords : Arabidopsis / genetics; Databases, Genetic; Gene Expression Profiling; Genes, Plant; Internet; Oryza sativa / genetics; Quantitative Trait Loci; User-Computer Interface