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Unique Database Provides Functional and Phylogenomic Information for Rice Glycosyltransferases
Published: July 29, 2010
Posted: October 01, 2010

JBEI researchers have made major advances in comprehensively identifying all rice glycosyltransferases (GT), an important class of enzymes involved in synthesizing polysaccharide sugars in plant cell walls. Because rice and other grasses such as switchgrass and Miscanthus share similar cell-wall characteristics, whole genome–scale analysis of rice has enabled the discovery of several candidate genes for more in-depth functional analysis that can help researchers understand and manipulate grass cell walls for biofuel production. This research has led to the development of JBEI’s Rice GT Database, a publicly available resource for integrating and displaying diverse sets of functional genomic information for GTs (ricephylogenomics.ucdavis.edu/cellwalls/gt/). The database contains information on 793 putative gene models for rice GTs, and the loci for these genes are distributed across all 12 rice chromosomes. In addition to defining phylogenetic relationships among groups of rice GT genes based on sequence similarity, JBEI researchers also compared the number of different GT gene models identified for rice, Arabidopsis, and poplar (Populus trichocarpa). From the hundreds of possible GT genes that have been identified, scientists revealed 33 rice-diverged GTs that are highly expressed in vegetative, aboveground tissues and that serve as prime targets for mutagenesis studies and enzyme activity screens.

Reference: This database was reported in Cao, P. J., et al. 2008. “Construction of a Rice Glycosyltransferase Phylogenomic Database and Identification of Rice-Diverged Glycosyltransferases,” Molecular Plant 1(5), 858–77.

Contact: John Houghton, SC-23.2, (301) 903-8288
Topic Areas:

  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Plant Systems and Feedstocks, Plant-Microbe Interactions
  • Research Area: Sustainable Biofuels and Bioproducts
  • Research Area: DOE Bioenergy Research Centers (BRC)
  • Research Area: Computational Biology, Bioinformatics, Modeling

Division: SC-33.2 Biological Systems Science Division, BER

 

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