1. From Functional Genomics to Physiological Model: Using the Gene Ontology Fiona McCarthy, Shane Burgess, Susan Bridges The AgBase Databases, Institute of Digital Biology, Mississippi State University

2. From Functional Genomics to Physiological Model 1. A user’s guide to the Gene Ontology (GO) 2. Finding GO for farm animal species 3. Adding GO to your dataset 4. GO based tools for biological modeling 5. Examples: using GO for biological modeling

3. Presentation available at AgBase Websites available as handout

4. 1. A User’s Guide to GO

5. What is the Gene Ontology? Emily Dimmer, GOA EBI: “a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing” assign functions to gene products at different levels, depending on how much is known about a gene product is used for a diverse range of species structured to be queried at different levels, eg:  find all the chicken gene products in the genome that are involved in signal transduction  zoom in on all the receptor tyrosine kinases human readable GO function has a digital tag to allow computational analysis of large datasets

8. GO Mapping Example NDUFAB1 (UniProt P52505) Bovine NADH dehydrogenase (ubiquinone) 1, alpha/beta subcomplex, 1, 8kDa Biological Process (BP or P) GO:0006633 fatty acid biosynthetic process TAS GO:0006120 mitochondrial electron transport, NADH to ubiquinone TAS GO:0008610 lipid biosynthetic process IEA Cellular Component (CC or C) GO:0005759 mitochondrial matrix IDA GO:0005747 mitochondrial respiratory chain complex I IDA GO:0005739 mitochondrion IEA NDUFAB1 Molecular Function (MF or F) GO:0005504 fatty acid binding IDA GO:0008137 NADH dehydrogenase (ubiquinone) activity TAS GO:0016491 oxidoreductase activity TAS GO:0000036 acyl carrier activity IEA

9. GO Mapping Example NDUFAB1 (UniProt P52505) Bovine NADH dehydrogenase (ubiquinone) 1, alpha/beta subcomplex, 1, 8kDa Biological Process (BP or P) GO:0006633 fatty acid biosynthetic process TAS GO:0006120 mitochondrial electron transport, NADH to ubiquinone TAS GO:0008610 lipid biosynthetic process IEA Cellular Component (CC or C) GO:0005759 mitochondrial matrix IDA GO:0005747 mitochondrial respiratory chain complex I IDA GO:0005739 mitochondrion IEA NDUFAB1 Molecular Function (MF or F) GO:0005504 fatty acid binding IDA GO:0008137 NADH dehydrogenase (ubiquinone) activity TAS GO:0016491 oxidoreductase activity TAS GO:0000036 acyl carrier activity IEA aspect or ontology GO:ID (unique) GO term name GO evidence code

10. GO Mapping Example NDUFAB1 (UniProt P52505) Bovine NADH dehydrogenase (ubiquinone) 1, alpha/beta subcomplex, 1, 8kDa Biological Process (BP or P) GO:0006633 fatty acid biosynthetic process TAS GO:0006120 mitochondrial electron transport, NADH to ubiquinone TAS GO:0008610 lipid biosynthetic process IEA Cellular Component (CC or C) GO:0005759 mitochondrial matrix IDA GO:0005747 mitochondrial respiratory chain complex I IDA GO:0005739 mitochondrion IEA NDUFAB1 Molecular Function (MF or F) GO:0005504 fatty acid binding IDA GO:0008137 NADH dehydrogenase (ubiquinone) activity TAS GO:0016491 oxidoreductase activity TAS GO:0000036 acyl carrier activity IEA GO EVIDENCE CODES Direct Evidence Codes IDA - inferred from direct assay IEP - inferred from expression pattern IGI - inferred from genetic interaction IMP - inferred from mutant phenotype IPI - inferred from physical interaction Indirect Evidence Codes inferred from literature IGC - inferred from genomic context TAS - traceable author statement NAS - non-traceable author statement IC - inferred by curator inferred by computational analysis RCA - inferred from reviewed computational analysis ISS - inferred from sequence or structural similarity IEA - inferred from electronic annotation Other NR - not recorded (historical) ND - no biological data available

11. Unknown Function vs No GO ND – no data  Biocurators have tried to add GO but there is no functional data available  Previously: “process_unknown”, “function_unknown”, “component_unknown”  Now: “biological process”, “molecular function”, “cellular component” No annotations (including no “ND”): biocurators have not annotated

12. 2. Finding GO for Farm Animals

13. GO Browsers QuickGO Browser (EBI GOA Project)  http://www.ebi.ac.uk/ego/ http://www.ebi.ac.uk/ego/  Can search by GO Term or by UniProt ID  Includes IEA annotations AmiGO Browser (GO Consortium Project)  http://amigo.geneontology.org/cgi-bin/amigo/go.cgi http://amigo.geneontology.org/cgi-bin/amigo/go.cgi  Can search by GO Term or by UniProt ID  Does not include IEA annotations

14. Getting GO http://www.ebi.ac.uk/GOA/downloads.html includes farm animals

15. Getting GO http://www.geneontology.org/GO.current.annotations.shtml# filter http://www.geneontology.org/GO.current.annotations.shtml# filter

16. Getting GO http://www.agbase.msstate.edu/

18. 3. Adding GO to your dataset

19. GO analysis of array data Probe data is linked to gene product data  gene, cDNA, ESTs IDs For some arrays, gene product data has corresponding GO data  available from vendor (updated?) Not all gene products will have GO annotation  will not be included in modeling Need to get the maximum amount of GO data to do biological modeling

20. Example: Netaffx

21. Secondary source of GO annotation

25. GORetriever + many more

26. GORetriever

27. GORetriever Results

29. save as text file For GOSlimViewer

30. GORetriever Results

31. But what about IDs not supported by GORetriever?

32. GOanna

35. GOanna Results

36. query IDs are hyperlinked to BLAST data (files must be in the same directory)

37. *WHAT IS A GOOD ALIGNMENT? If there is a good alignment* to a protein with GO  transfer GO to your record If there is not a good alignment or the record doesn’t have GO  literature

38. good alignment add to GO summary file (tab-delimited text file containing ID, GO:ID, aspect)

39. Contact AgBase to request GO annotation of specific gene products.

40. GOSlimViewer: summarizing results

41. GOSlimViewer results

42. response to stimulus amino acid and derivative metabolic process transport behavior cell differentiation metabolic process regulation of biological process cell communication nucleobase, nucleoside, nucleotide and nucleic acid metabolic process cell death cell motility macromolecule metabolic process multicellular organismal development catabolic process biological_process

43. response to stimulus amino acid and derivative metabolic process transport behavior cell differentiation metabolic process regulation of biological process cell communication nucleobase, nucleoside, nucleotide and nucleic acid metabolic process cell death cell motility macromolecule metabolic process multicellular organismal development catabolic process biological_process “process unknown” “function unknown” “component unknown” ??

44. B-cellsStroma immune response apoptosis cell-cell signaling Looking at function, not genes Pie Graphs – relative proportions

45. GOModeler: quantitative, hypothesis-driven modeling. Coming soon (contact AgBase) GOModeler

46. McCarthy et al “AgBase: a functional genomics resource for agriculture.” BMC Genomics. 2006 Sep 8;7:229.

47. 4. GO based tools for biological modeling

48. http://www.geneontology.org/

50. However…. many of these tools do not support farm animal species the tools have different computing requirements may be difficult to determine how up-to-date the GO annotations are… Need to evaluate tools for your system.

51. Evaluating GO tools Some criteria for evaluating GO Tools: 1. Does it include my species of interest (or do I have to “humanize” my list)? 2. What does it require to set up (computer usage/online) 3. What was the source for the GO (primary or secondary) and when was it last updated? 4. Does it report the GO evidence codes (and is IEA included)? 5. Does it report which of my gene products has no GO? 6. Does it report both over/under represented GO groups and how does it evaluate this? 7. Does it allow me to add my own GO annotations? 8. Does it represent my results in a way that facilitates discovery?

52. 5. Using GO for biological modeling

54. Using GO for biological modeling: hypothesis generating hypothesis driven