Gramene: Mapping Grasses for Global Food Security

1. GRAMENE A comparative mapping resource for the grasses www.gramene.org Gramene Workshop @ Plant Biology July 25, 2004 Molly Fogleman Doreen Ware Pankaj Jaiswal

2. Topics • General introduction to the grasses • Molly Fogleman • Gramene: a community resource • Doreen Ware • Answering biological questions with Gramene • Pankaj Jaiswal • Open Discussion We invite you to give feedback on this workshop by completing our survey. Gramene poster # 902

4. 49% of the world’s calories (human consumption) are provided by rice (23%), wheat (17%) and maize (9%) Wheat is the staple food for 35% of the world Rice is the staple food for almost half the world’s population Cereals as a Food Staple Source: Evolution and Adaptation of Cereal Crops, 2002 Science Publishers, Inc.

5. Diets high in grains can lead to reductions in: Coronary Heart Disease Cancer Diabetes The USDA Food Guide Pyramid The USDA recommends 6-11 servings of grains/day Source: www.usda.gov and Whole Grain Foods in Health and Disease, 2002 American Association of Cereal Chemists, Inc.

6. USA and World Grass Acreage Sources: USDA and the National Agricultural Statistics Service's March 2004 Historical Track Records for United States Crop Production FAOSTATS May 2004 Note: Figures have been rounded

7. Population vs. Acreage • Amount of land farmed in the US and the World is decreasing due to: • Urbanization • Erosion • High soil salinity levels • Agricultural Environmental Impacts in the US: • 48% of the impaired river miles • 41% of impaired lakes in the United States. • Nutrient, sediment and pesticide runoff Source: EPA 2003 Photo Source: USDA - National Resources Conservation Service

8. Question: How to Feed a Growing Population? • Genotypes (high yielding, pest resistance, drought tolerant, salt tolerant) from existing germplasms (gene pool)? • Bioengineered Food? Photo Source: The Washington Post PhotoVoyage: Rice a Global Grain

9. Source: National Plant Germplasm System (GRIN), July 2004

10. Phylogeny of the Grasses Source: Kellogg, 1998, PNAS

11. Macrosynteny: Markers, QTLs, and Genes are found in similar positions Source: MD Gale & KM Devos, 1998, PNAS

12. Why use Rice as a leverage? • Smallest genome • Sequenced genome • Extensive genetic & physical map resources • Thousands of genes and quantitative trait loci mapped • Large mutant & germplasm collections

13. Gramene a community resource Doreen Ware USDA-ARS Cold Spring Harbor Laboratory www.gramene.org

14. trait candidate 1 candidate 2 candidate 3 Genomics by Proxy Maize, Barley, Sorghum, Oat, Wheat… Rice

15. Timeline and Funding • Gramene www.gramene.org • Funded October 2001 • Superceded USDA RiceGenes • First release of the database January 2002 • Funding Sources • USDA CREES IFAS • USDA ARS Specific Cooperative Agreement • NSF Research Coordination Network • NSF Plant Genome Initiative

16. Web pages accessed by month

17. Project Participants • Community Collaborators • Publicly funded projects • Individual researchers • Gramene Staff (Cornell and CSHL) • Curators • Information content • Software developers • Visualization tools and data management • Outreach • Scientific community and Secondary Educators

18. Collaborators and Contributors http://www.gramene.org/collaborators

19. Community Resource • Integrative set of web-based tools for discovery • Semi-automated • Curated • Software applications • CMap: Generic Model Organism Systems Database Project (GMOD) www.gmod.org • Controlled vocabularies • Open Biological Ontologies (OBO) • Plant Ontology (POC workshop July 27 ) • Gene Ontology • Trait Ontology • Environment Ontology

20. What’s in Gramene • High-throughput data • Rice genome • Rice proteins • Functional annotation of gene products • Grass EST collections • Curated data • Genetic maps • Physical maps • Protein annotation • Mutant (phenotypic variant) • Quantitative Trait Loci (QTL) • Documentation and Help Guide

21. Search Tools • Genome browser • BLAST • CMap viewer • Marker • Protein • Ontology • Mutants • QTL • Literature

22. Web Interfaces • Standard • Customizable • Links • Within the database • Between database • Data sources

23. Navigation bar standard

24. Genome browser display • Data sets (Genbank, public projects, curated annotations) • Semi Automated Alignment pipeline • Ensembl browser for the database structure and visualization. Developed by EBI/Sanger for the human genome project

25. Ensembl Genome Browser

26. Pages provide links within and between databases

27. Views are customizable • Select tracks to display • Compact and expand • Color

28. Genome annotation of rice • Gene model • Validation • Comparative analysis using other cereal sequence • Tissue expression • Functional assignment (GO)

29. Associate the biology of the organism with sequence • Phenotypes: mutants and QTLs • Integrated map feature genetic markers

30. Comparative Map display • Maps and Correspondences (public projects, curated) • Literature • Community curation • Alignment from sequence • Database structure and browser • CMap –GMOD project

31. Correspondences in comparative map display • Rice Genome Assembly is the reference map in the comparative map browser • Sequence features and hybridized markers provide the correspondence within species and between species maps

32. Wheat 4D, Rice 3, and Maize 1

33. …….add Sorghum C syntenic

34. Protein Browser • Data sets • SwissProt rice proteins, annotations and associated literature • Ontologies (controlled vocabulary) • Custom database structure and visualization software

35. Protein Page

36. KEGG

38. SwissProt

39. SwissProt linkback

40. Waxy associations to the Ontology browser

41. Links to search, features, literature

42. Phenotypes assays • What do you want to capture? • How will you integrate this information into a database?

43. Common fields for curation of mutants and QTL • Observable/measurable difference resulting from: • one or more mutations (alleles) • at specific genetic loci (mapped genes) • that interact with the rest of the genetic background (germplasm accession) • under a given set of environmental conditions (temperature, light, moisture, nutrition, space) • as part of a biotic regime (i.e., exposed to specific microbes, insects, plants) • measured in given location(s) & time(s) (season, year) • at specific stage(s) of development.

44. Ontologies used in Gramene • Gene Ontology • Molecular Function • Biological process • Cellular location • Plant Ontology • Anatomy • Development • Trait Ontology

45. Find all rice mutants in my favorite colinear region of rice associated with dwarfism. What genes within a starch content QTL are predicted to be involved in carbohydrate metabolism? Find protein orthologs between rice & maize whose stage-specific expression patterns have changed. What Ontologies Let You Ask

46. QTL search with trait category “Development”

47. Answering biological questions with Gramene Gramene workshop @ Plant Biology July 25, 2004 Pankaj Jaiswal

48. TASKS • Map a cloned rice resistance gene to its putative location in the rice genome • Compare its position to that of other mapped resistance genes • What do we already know ? • The rice disease resistance gene Pi-ta • Genetically mapped to chromosome 12 Rybka et al. (1997). • It has also been sequenced Bryan et al. (1997).

49. There are three protein accessions • one of which is a hypothetical protein similar to Pi-ta. • The other two, with accessions AAO45178 and AAK00132, are the Pi-ta sequences. • (You may click on their respective links to verify that they are indeed the sequences of interest.) Download the amino acid sequence for the Pi-ta protein for rice from the NCBI website

50. Copy the sequence Gramene BLAST Search