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About the Planteome Project

  • The Planteome Project (http://planteome.org/) is a newly-funded (NSF Award #1340112 Dec. 2014) initiative which will build on the work done in the Plant Ontology Project (link), and will create a centralized platform where reference ontologies for plants will be used to access cutting-edge data resources for plant traits, phenotypes, diseases, genomes and semantically-queried genetic diversity and gene expression data across a wide range of plant species.
  • The Planteome will continue to develop and enrich the existing reference ontologies, the Plant Ontology (PO), Plant Trait Ontology (TO), and the Plant Environment Ontology (EO) and will encompass relevant aspects of other reference ontologies such as the Gene Ontology (GO), Cell type Ontology (CL), Chemical Entities of Biological Interest (ChEBI), Protein Ontology (PR) and the Phenotypic Qualities Ontology (PATO).
  • The Planteome fits into the existing biological ontology landscape, and will be an active participant in the OBO Foundry (http://obofoundry.org/crit.shtml), adhering to all of its principles. We will collaborate with the existing reference ontologies and contribute to their enrichment in terms and definitions of common importance to plant biology.

Specific Aims of the Project

1. A set of common reference ontologies to describe major knowledge domains of plant biology, comprising plant phenotype and traits, environments, and biotic and abiotic stresses, including plant diseases.

2. Standards, workflows and tools for ontology development, curation and improved annotation of genes, genomes, phenotype and germplasm.

3. An online informatics portal and data warehouse for ontology-based, annotated plant genome data and plant genomes.

4. Smart and semantic data query, analysis, visualization, and community-based annotation and curation tools.

5. Outreach involving K-12 and undergraduate students, and the plant research community.

Planteome Project Management

Planteome All-Hands Monthly meetings

Planteome_cROP_Grant_Proposal

Scientific Advisory Board

Position Paper- Setting Standards for Plant Phenotyping

Planteome Collaborations

Planteome Project Working Groups

Planteome Ontology Development and Coordination Working Group

Planteome_Image_Annotation_Working_Group

Data storage and AmiGO2 Working Group


Planteome Outreach

2015:

Plant and Animal Genome Meeting, January 9-13, 2015 San Diego, CA

Link to Conference program: Plant and Animal Genome Meeting XXIII

  • DivSeek Meeting- Friday January 9th from 8am-5pm
  • Systems Biology and Ontologies Workshop, Saturday January 10th from 8:00-10:10 AM. Organizers: Laurel Cooper, Sushma Naithani and Pankaj Jaiswal
  • Plant Phenotypes Workshop, Sunday, January 11, 2015. Organizers: Mary Schaeffer and Chi-Ren Shyu
  • Crop Ontology Meeting Monday, January 12, 2015. Organizers: Elizabeth Arnaud and Rex Nelson

2015 Maize Genetics Conference- March 12-15, 2015, St. Charles, Illinois, USA

Poster presentation: # P235 Comparative Phenomics in Plants.

Harper, Lisa1; Oellrich, Anika2; Walls, Ramona3; Cannon, Ethy4; Cannon, Steven5; Cooper, Laurel6; Gardiner, Jack4; Gkoutos, George7; He, Mingze4; Hoehndorf, Robert8; Jaiswal, Pankaj6; Lloyd, Johnny9; Kalberer, Scott5; Meinke, David10; Menda, Naama11; Moore, Laura6; Nelson, Rex5; Pujar, Anuradha12; Lawrence, Carolyn4; Huala, Eva13

1. USDA ARS Albany, CA 2. Wellcome Trust Sanger Institute, Hinxton, United Kingdom 3. The iPlant Collaborative, Tucson, AZ 4. Iowa State University, Ames, IA 5. USDA-ARS-CICGRU, Ames, IA 6. Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 7. Computer Science Department, Aberystwyth University, Aberystwyth, United Kingdom 8. King Abdullah University of Science & Technology, Thuwal, Saudi Arabia 9. Michigan State University, East Lansing, MI 10. Oklahoma State University, Stillwater, OK 11. Boyce Thompson Institute for Plant Research, Ithaca, NY 12. Cornell Univer sity, Ithaca, NY 13. Phoenix Bioinformatics, Redwood City, CA

Plant phenotype comparisons enable us to expl ore the relationship between gene function, sequence similarity and consequently to ma ke predictions for crop improvements. Plant phenotypes are described primarily using free text and are inconsistent between species, making computer facilitated queries difficult; however, asse ssing this data manually is impossible due to the ever increasing plethora of available phenotype data. To address this issue, we undertook a pilot project to formalize phenotype descriptors for six plant species, focusing on mutant phenotypes associated with sequenced genes. To do this, we selected free text descriptions of 1742 unique phenotypes for 2741 genes from maize, rice, Arabidopsis, soybean, tomato, and Medicago and manually converted them into a common Entity-Quality format using taxonomically broad ontologies; e.g., the Plant Ontology and the Gene Ontology. The power of this method lies in the fact that hierarchical ont ologies allow even distantly related phenotypes to be identified computationally. Similarity scores were calculated for each pair of phenotypes and the resulting associations were loaded into a database and query tool called PhenomeNet (http://phenomebrowser.net/plant/ query.php). PhenomeNet enables researchers to query these associations with locus names, gene identifiers, and phenotypic descriptions. To the user, this is roughly similar to using BLAST to identify si milar sequences. Although the phenotype dataset must be greatly expanded to be a useful research tool, our work demonstrates that comparing phenotypes among divergent plant species can be automated. Funding acknowledgement: National Science Foundation (NSF), United States Department of Agriculture (USDA)

Data Harmonization Workshop, Beltsville, MD. June 11-12th 2015

AgMIP and USDA have organized a for the crop modeling research community

Data Harmonization

Upcoming Meetings of Interest:

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