Crop Plant Trait Ontology Workshop Agenda

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Dates: Sept 13-15th, 2012 (Thursday through Saturday)

Location: Oregon State University

Return to the main Crop_Plant_Trait_Ontology_Workshop_OSU_2012 page

Weds Sept. 12th, 6-8pm

Dinner on your own those who arrive early

Snack and refreshments will be available at Finley Hall or Arnold dining center will be open until 7pm

Thursday September 13

Location: CH2M Hill Alumni Center Williamette Room

* 8:00- 9am Continental Breakfast in Williamette Room

  • 9:00- 9:15 Welcome and Introductions - Pankaj Jaiswal, OSU

Ruth Bastow: Insights and follow-up from EBI Crop Ontology Meeting


    • Goals:
    • Improve current ontologies for UK/EU crops
    • Improve community uptake and use
    • Widen participation and involvement
    • Make the best of funding and resources (build on PO and GCP)

Melissa Haendel; "Introduction to Ontologies" OHSU Library


    • Main points:
    • Ontology- A formal conceptualization of a specified domain of interest.
    • Terms are defined
    • Relationships between terms are defined
    • Terms are arranged in a structured hierarchy
    • The true path rule- The pathway from a subClass all the way to its top level parent must be universally true.

Laurel Cooper, OSU Plant Ontology and the Trait Ontology


    • Goals:
    • Revise and expand the existing Trait Ontology
    • Refer Plant Trait Ontology to link the crop- and clade- specific ontologies
    • Develop a reference set of ontologies for all plants
    • CROP- Common Reference Ontology for Plants

* 10:30- 10:45 coffee break

Organizing Committee Talks

Elizabeth Arnaud, Bioversity /Generation Challenge Program


    • Goals for Crop Ontology:
    • Add new crops: barley, pigeon pea, sweet potato, yam
    • Add translations
    • Add the Crop wild relative ontology
    • Cross reference with main data sources
    • Use as search tool for Integrated Breeding Platform
    • Automatic submission to PO and TO
    • Contribute to Reference Plant Trait Ontology

File:Arnaud GCP-9-13-12.pdf

Naama Menda- Sol Genomics Network


    • Goals:
    • Complete mapping to PO
    • Map terms to TO
    • Annotate expression data with PO terms
    • Generate EQ statements for Solanaceae known genes

Rex Nelson- SoyBase


    • Goals:
    • Soybean specific ontology – SOY
    • Integrate PO, TO, GO, CHEBI, and PATO into SOY
    • Soybean QTL and traits annotated with SOY, PO, TO identifiers
    • Annotate gene functions/ mutations with PO, TO, GO, CHEBI, PATO identifiers as part of PhenotypeRCN project
    • Search SoyBase by TO and GO annotations and produce full report of all major data and classes

Mary Schaeffer- MaizeGDB


  • 11:45- 12:00 0pen time for questions and discussion

* 12:00- 1:00 Lunch: Soup and Salad Buffet; Elle/Burlingham Room #111

Flash Talks- Session 1

Bob Benson, Syngenta traits


    • Goals:
    • The “Native Trait” approach to discovering and developing improved performing products.
    • (DNA sequence info => Mapped genetic elements => Polymorphisms => Germplasm panels => Marker trait associations => Create directed novel gene combinations)
    • Range phenotypic expression across germplasm in water limited growing conditions
    • Manage the drought stress environment

Sharon Lewis; Syngenta- Information governance


    • Goals:
    • Raise productivity in sustainable ways
    • Improve farm productivity
    • Reduce agriculture's environmental footprint
    • Build rural prosperity
    • Create continued sales growth across all regions
    • Innovate across technologies to transform the way plants are grown
    • Need to move ahead with EO,
    • Need an "Agronomic Practices Ontology: e.g. plowing, irrigation, planting, fertilizer regimes, compare to CO, have lists
    • Use BBCH scale- prefer over stage terms, also used in Europe and EU- need to make sure to BBCH are synonyms are used in the PSDS

Alice Clara Augustine, Monsanto

(No slides presented)

    • Discovery- testing genes, starts with ontology, esp TO
    • put genes into crops in the field to test -> develop product
    • change in languages- the 'Tower of Babel'
    • Trait Ontology terms are part of the hypothesis and are used in the regulatory package

Sonia Dias- Trait Information Portal


    • Ontologies for Agrobiodiversity Conservation and Use
    • PGR secure: characterization of crop wild relative and landrace resources

PGR Secure Goals:

    • To produce a web-based crop wild relative (CWR) and landrace (LR) Trait Information Portal (TIP)
    • Case study genera: Avena, Beta, Brassica and Medicago
    • Triontology: crop wild relative (CWR) and landrace (LR) and CO for case study genera
    • Should be available mid-October- link up to external ontologies


    • An ontology that describes the crops, themes, traits, anatomical and morphological structures and growth and developmental stages, etc
    • Describe crops, CWR and LR structures and entities and the relationships between them
    • A semantic framework for meaningful cross-species queries across crops, inventories and traits (genotyping and phenotype datasets)
    • EURISCO:a web-based catalogue that provides information on more than 1.1M accessions of ex situ plant collections maintained in Europe
    • Develop a staging area for inclusions of characterization and evaluation data using ontologies
    • Up-grade staging for passport data
    • Collaborate for integration of other ontologies
    • Contribute to existing ontologies i.e. CO, TO, GO...
    • Analysis tools
    • Visualization for cross – species/domain search

Pawel Krajewski, transPLANT


Head, Laboratory of Biometry, Institute of Plant Genetics, Polish Academy of Sciences, Poznań, Poland

POLAPGEN-BD- Biotechnological tools for breeding cereals with increased resistance to drought

    • Goals:
    • Generate and describe genetic diversity
    • Phenotypic expression of drought tolerance
    • Data analysis and integration
    • Describe and predict environmental conditions
    • GERMINATE schema- with JHI
    • mainly focused on spring barley

Jacques Legouis; INRA, France


  • Goals:
    • PHENOME – high-throughput phenotyping network
    • Various scales: field platforms (plot/farm), field semi-controlled platforms(plot scale), greenhouse platforms (plant/organ), metabolomic/structural (Scale: organ)
    • BREEDWHEAT – breeding for sustainable wheat varieties
    • Interested in a diverse list of traits (see slides):
  1. At different scales: – plot, plant, tiller, organ, tissue
  2. At different stages - times, Biomass at flowering, harvest, stem nitrate content at sunrise / sunset
  3. With different units- Flowering time (d, das, °Cd,…)
  4. In different ways- Canopy temperature
  5. infrared thermometer/ infrared camera
  6. Measured/ calculated traits – Grain protein deviation
  7. Response across treatments/locations – Joint regression

Cyril Pommier, INRA France; Ephesis


    • Goals:
    • Data standardization -
      • Inside species groups
      • Help new projects
      • Recommended for international collaboration and publications
      • Ease data interoperability and re-usability
    • Ease inclusion of INRA's traits to international standards

John Doonan, UK Phenomics Center IBERS, Aberystwyth University, Wales


    • Goals:
    • Integration of biological and chemical phenomics
    • Development of laser scanning technologies
    • Calibrating technology for grasses and perennial crops
    • Providing transnational access to NCCP
    • Establishing data standards and ref expt

Dan Bolser, EBI, Ensembl, potato genomics


    • Goals:
    • Species specific vs. species independent anatomical ontologies.
      • Mapping?
    • Overview of ontologies...
      • Whats well/poorly represented?
      • What does the ontology think a plant looks like?
      • Can I learn about plant biology from an ontology?
    • Composing terms to describe phenotypes
      • REST services?

* 2:30- 2:40 coffee break

Flash Talks- Session 2

Reinhard Simon, International Potato Center

Integrated IT and Computational Research, CIP Media:Simon_CIP-9-13-12.pdf

potato trait ontology

    • Goals:
    • Help build the institutional memory of research data
    • Make data accessible and providing tools for scientists
    • Statistics, GIS, database and application development, bioinformatics, data curation
    • Key central data store organized around germplasm using biomart
    • Using ontologies for improving quality, data exchange and data mining for germplasm resources
    • Traits of interest in potato breeding:
      • Tuber yield and related phenology (stolons, tuber initiation, tuber filling, plant senescence, flowering, earliness)
      • Reaction to abiotic stress (drought, salinity)
      • Reaction to biotic stress (late blight, bacterial wilt, virus)
      • Reproductive biology
      • Quality (processing & nutritional)

Victoria Blake, USDA, ARS, CA GrainGenes TCAP project


    • Goals:
    • Combine genotype/phenotype data for associated analysis with TASSEL
    • Create genotype data for graphical genotyping with FlapJack
    • Create two independent databases for barley and wheat to support the T-CAP project

Luke Ramsay, Barley traits Hutton Institute


    • Goals:
    • Manipulating recombination distribution and frequency in barley
    • Add malting quality traits to TO

C Tom Hash, ICRISAT, sorghum


    • Goals:
    • Prioritization of breeding targets
    • Use of appropriate experimental designs
    • Generation of high quality phenotype data
    • Thorough statistical analysis of the resulting data sets

Ken McNally, International Rice Research Institute


    • Goals:
    • Harnessing genetic diversity to chart new productivity, quality, and health horizons
    • Characterizing genetic diversity and creating novel gene pools

Michael Dingkuhn, International Rice Research Institute


    • Goals:
    • Multi-phenotyping on shared reference panels
    • Yield potential and abiotic stresses
    • Multi-environment field phenomics for trait GxE
    • Complementary HTP platforms

Sunita Kumari, KBase


    • Goals:
    • Integration of the data to extract knowledge from the wealth of high-throughput data in plant biology
    • Establish a framework for developing capability that will allow interactive, data-driven analysis and exploration across multiple-omics experiments
    • Provide researchers access to comprehensive data sets from high-throughput experiments together with relevant analytical tools and resources
    • Provide a platform for researchers to analyze their own experimental data and have these results incorporated into the data exploration framework

Plant Ontology Tools for Annotation: Live Software Demo

Justin Preece, OSU

  • Semantic Image Annotator (SIA)- pre-release; the public release will be announced on the PO mailing list and available for download at the Jaiswal Lab web site soon
  • Plant Annotation Wiki
  • 4:30- 5:00 Open time for questions and discussion

* 5:00- 6:00 break, free time

* 6:00- 7:00 Pizza dinner- Elle/Burlingham Room #111

  • 7:00 to 9:00pm 'Hands-on' Session

Ontology editing: Using OBO Edit- tutorial and practice

  • You can download and install OBO-Edit from here: OBO-Edit

Note: the newest version of Mac OS Mountain Lion appears to have a default setting blocking installations from sites other than Apple Apps store. This can be turned off.

Steps to setting up the OBO-Edit after doing download and install:

  1. Select "New Ontology"
  2. Set up save profile
  3. set up a number space using ID Manager
  4. Set auto commit text edits
  5. Create a root class
  6. Create a root relation- part_of
  7. Populate the ontology

Requesting terms using the SourceForge trackers

Please see the link: How to use the Source Forge tracker

Before using the PO Source Forge tracker you should:

  1. Register (create a login)
  2. Log in to your account
  3. Search the tracker for existing items on the same topic

Friday September 14

* 8:00- 9am Continental Breakfast in Williamette Room

9:00- 9:10 Welcome and Announcements

Sushma Naithani, OSU Horticulture


    • Goals:
    • Genome annotation and curation of metabolic pathways

Laurent DeLuc, OSU Horticulture, grape research


    • Goals:
    • Create an integrative approach to identify the mechanisms that govern grape berry ripening
    • Development of new traits to describe the enhancement with non destructive measurement
    • Imaging tools to capture the fruit growth and ripening

9:30-9:40 Pankaj

* 9:50- 10:50 coffee break

  • 10:00- 11:00 Creating the 'CROP Initiative' (Common Reference Ontologies for Plants)
    • Pankaj: Introduction

Barry Smith: Webex presentation Ontology site, Department of Philosophy site


    • Goals:
    • Support the annotation of meta-data related to:
      • Data about biological samples produced from various technologies
      • Data produced from remote sensing equipment
      • Images
      • Physical holdings
      • Anything that has an environment

Streaming recording link

Download recording link

11:00- 12:00 discussion

* 12:00-1:00 Lunch: Assorted Wraps with Soup and Salad; Elle/Burlingham Room #111

1:00- 1:30 Breakout Groups are organized and tasks are explained

1:30- 3:00 Breakout Group Session: "Find your trait of Interest"

  • Groups will explore the TO and find out if the traits they are interested in are represented

- Creating name, defining the trait, assigning a place in the hierarchy

- Can also be 'Hands-on' using OBO-Edit

  • Breakout Groups:

Quality: Pawel, Luke, Rex, Melissa, Sharon

Yield: Jaques, Mary, Ruth, Tom, Cyril, Michael, Laurel

Stress: Sunita, Sonia, Pankaj, Bob

Anatomy and Morphology: Victoria, Ken, Elizabeth, Alice Clara, Laura

Growth and Develoment: John, Laurent, Naama, Reinhard

Informatics: Justin E, Justin P, Dan, Alok?, Rex

3:00 coffee break and group photo

3:30- 5:00- Breakout Groups report on progress, discussion, questions


Amigo - Ontology Browser used by plant ontology

Amigo problems- upload to a new version

Amigo not many other solution

Amigo can load multiple ontologies at the same time and deal with parent child relationships from separate ontologies

Questions does Omego support OWL - yes new version should do


OWL still hard for humans

OBO easier to edit

Likely that everything will move to OWL


Some we get bulk uploads

Need incremental ways to add these in

using annotation wiki for smaller numbers would be useful


need to write a real good request so it could be understood eg acronyms need to defined or not used

cooking and brewing quality - relationship to OBI ontologies processing. probably needs a re think

Some were assays


Needs a lot of work.

Defined a new yield term

Moved through levels

Fruit yield

Grain needs to be a separate area not just a synonymn - need to know how to use tracker

Do we need above or below ground biomass

Need botanical/ontological first in many cases would be great if this was present now

pper level terms are really hard to define


Need to start at the top first!

Abiotic (temp water, light etc) and Biotic stress

Stress is a response

Decide upon 'Response to ………' this removes the idea of a negative response that is associated with stress

Biotic due to a specific agent with varied responses

Outcome of biotic stress e.g. rust or brown spot are shared by many different pathogens

Specturm of response needs to be taken into account e.g. resistant to susceptible

Need community standards on how to collect and store information re specific biotic stress to help people collect data. Should these be associated with the ontology?


Response to sub optimal water conditions

Phenological, morphological conditions

Should it be 'response to' or should it be 'adaptation' instead as some plants are 'pre determined' to deal with this from day one this is not a response it is genetic.

Developmental conditions also need to be taken into account.

GO looks at abiotic/biotic stimulus. GO should be at molecular

Growth and Development

Sprout should be before after tuberisation.

Tuber is after shoot in the ontology

Days to tuberisation

Tuber growth rate - don't usually measure this is it needed

All in the tracker but need to be added into PO and TO

Incompatibility- needs to be defined

partial incompatibility needs to be added in

morphological incompatibility- in some wild species of tomato

No term for fruit development?

Soybean - terms for nodulation

nodule developmental stages should be in PO

Need to check how nodule formation and step there under are described in GO

Need to define between a process leading to a condition at the end point which is the trait.

The end point needs to be a measurable trait to go into to TO.

Discussion over not putting a unit in the description. agreed that the ontologies need to be changed to remove units such as days

Flowering time or time to flowering - needs to be divided into days to flowering from sowing, days to flowering from emergence, days to heading each should be a separate child not a synonym.

There should be a set of description known as field term e.g. 50% flowering

Anatomy and Morphology

trait descriptions were not specific enough in many case need more information in most cases and a domain expert!

How are time series dealt with in PO/TO etc

Melissa - What are the use cases - build to our needs

Concrete queries for the new ontologies

* 5:00- 6:00 break, free time

  • 6:00- 6:30 Gathering

* 6:30- 9:00 Dinner and Social -Elle/Burlingham Room #111

Saturday September 15

* 8:00- 9am Continental Breakfast in Williamette Room

9:00- 9:30 Biological examples and ontology applications; Pankaj Jaiswal, OSU

9:30- 10:30 Group discussion

* 10:30- 10:45 Coffee break

10:45 Summary and conclusions

Wrap and to-do lists for follow-up

12:00 Boxed Lunches