P1012
Parasitic Plant Genome Database: A Resource for Parasitic Orobanchaceae Transcritptomes

Date: Monday, January 13, 2014
Room: Grand Exhibit Hall
Eric Kenneth Wafula , Penn State University, University Park, PA
Loren Honaas , Penn State University, University Park, PA
Paula Ralph , Penn State University, University Park, PA
Yeting Zhang , Penn State University, University Park, PA
Zhenzhen Yang , Penn State University, University Park, PA
Lena Sheaffer , Penn State University, University Park, PA
Norman Wickett , Chicago Botanical Garden, Chicago, IL
Kan Huang , University of Virginia, Charlottesville, VA
Yongde Bao , University of Virginia, Charlottesville, VA
Monica Fernandez-Aparicio , Virginia Tech University, Blacksburg, VA
Malay Das , Presidency University, Kolkata, VA, India
Pradeepa Bandaranayake , Department of Crop Science, University of Peradeniya, Peradeniya, Sri Lanka
Biao Wu , University of California-Davis, Davis, CA
Michael P. Timko , University of Virginia, Charlottesville, VA
John Yoder , University of California-Davis, Davis, CA
James H. Westwood , Virginia Tech University, Blacksburg, VA
Claude dePamphilis , Penn State University, University Park, PA
Parasitic flowering plants are pests on several agronomic crops and can cause dramatic reduction in yield representing a major risk to food security in many developing economies. Despite the large potential negative economic impact, parasitic plants are relatively understudied and control strategies are poorly developed. Orobanchaceae is the only plant family with species that span the full trophic spectrum of parasitism ranging from obligate holoparasites to facultative parasites and free-living nonparasites. We have developed an extensive database of nearly two billion stage-specific expressed gene sequences for Triphysaria versicolor, Striga hermonthica, Phelipanche aegyptiaca and Lindenbergia philippensis to leverage the evolutionary framework presented by Orobanchaceae. This resource presents a comparative functional genomic analysis framework for parasitic plants that will contribute to the discovery of the genome-wide changes that led to the establishment of parasitism, identify genes and pathways critical to parasite biology, and provide subsequent targets for functional analysis that may lead to new control technologies. The Parasitic Plant Genome Database provides sequence data, transcript assemblies, translations and homology-based functional annotations, BLAST (sequence similarity) searches, and search by keyword or Gene Ontology classification. In addition, we provide expanded annotation information, domain predictions, metabolic pathway predictions, expression levels for every assembled transcript in each developmental stage, as well as gene family classifications and pre-computed phylogenies for gene families. The Parasitic Plant Genome Database is freely available at http://ppgp.huck.psu.edu.