1. Making best use of TAIR tools and datasets Philippe Lamesch Donghui Li The Arabidopsis Information Resource www.arabidopsis.org contact us: curator@arabidopsis.org

2. TAIR: The Arabidopsis Information Resource collect, curate and distribute information on Arabidopsis information freely available from arabidopsis.org

3. Gene structure – Philippe Lamesch Gene function – Donghui Li Metabolic pathway – Donghui Li New tools – Philippe Lamesch Outline

4. Slides available from TAIR www.arabidopsis.org

5. TAIR is used worldwide Visits per month (source: Google Analytics)

6. TAIR usage in Asia: June 2009-June 2010

7. What we do: (1) Arabidopsis genome annotation

8. What we do: (2) manual literature curation Controlled vocabulary annotations Gene Ontology (GO) http://www.geneontology.org/ Plant Ontology (PO) http://www.plantontology.org/ Gene name, symbol Allele, phenotype Summary statement composition

9. What we do: (3) metabolic pathway curation AraCyc A metabolic pathway database for Arabidopsis thaliana that contains information about both predicted and experimentally determined pathways, reactions, compounds, genes and enzymes. PlantCyc and PMN (Plant Metabolic Network)

10. What we do: (4) work with ABRC to distribute research material

11. Part I: The Arabidopsis genome annotation A new approach for improving the Arabidopsis genome annotation Where to find gene structure related data at TAIR The Arabidopsis gene structure confidence ranking

12. Arabidopsis genome annotation Arabidopsis genome sequenced almost 10 years ago High quality sequence with few gaps TIGR did initial genome annotation TAIR took over responsibility in 2005 Current TAIR9 stats: 27,379 protein coding genes 4827 pseudogenes or transposable elements 1312 ncRNAs

13. Genome annotation at TAIR Add novel genes Update exon/intron structures of existing genes Delete mispredicted genes Merge and split genes Change gene types Add splice-variants

14. Genome annotation at TAIR Annotate atypical gene classes * * * ** * * Trans. element Short protein-coding genes Transposable element genes Pseudogenes uORFs (genes within UTR of other genes) Add novel genes Update exon/intron structures of existing genes Delete mispredicted genes Merge and split genes Change gene types Add splice-variants

15. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: Use ESTs and cDNAs and a assembly tool called PASA to improve gene structures TAIR10 TAIR10: Use new experimental data and new prediction tools to further improve gene structure predictions

16. Using PASA and ESTs/cDNAs Clustered transcripts NCBI Genome annotation TAIR6-TAIR9

17. Clustered transcripts Resulting gene model NCBI Using PASA and ESTs/cDNAs Genome annotation TAIR6-TAIR9

18. Clustered transcripts Resulting gene model Previous gene model NCBI comparison Novel genes New Splice-variants Gene structure updates Using PASA and ESTs/cDNAs Genome annotation TAIR6-TAIR9

19. ESTs cDNAs Radish sequence alignments Eugene prediction dicot sequence alignments monocot sequence alignments Aceview gene predictions 2 gene isoforms Manual annotation at TAIR: Apollo Short MS peptide

20. TAIR10: using proteomics and RNA-seq data to improve genome annotation 4-step process: 1.Mapping RNA seq & Peptides 2.Assembly/Gene built 3.Manual review 4.Integration (genome release/Gbrowse)

21. Mapping and Assembly 1.Mapping RNA-seq sequences (Tophat (C. Trapnell), Supersplat (T.C. Mockler)) Peptides (6-frame translation, spliced exon graph) 2.Assembly approaches Augustus (M. Stanke) o Uses spliced RNA seq reads, peptides o Aim: Identify additional splice-variants, update existing genes TAU (T.C. Mockler) o Uses spliced RNA seq reads o Aim: Identify additional splice-variants Cufflinks (C. Trapnell) o Uses spliced and unspliced RNA seq data o Aim: Identify novel genes

22. Augustus TopHat, SuperSplat 145,000 RNA-seq junctions based on >1 read 203,000 clustered spliced RNA-seq junctions (spliced RNA-seq junction) RNA-seq datasets (Mockler Lab, Ecker Lab) 200 Million aligned RNA-seq reads

23. Augustus 145,000 RNA-seq junctions based on >1 read 260,000 peptides (Baerenfaller et al, Castellana et al) Augustus gene prediction + ESTs & cDNAs + AGI models 11% of RNA-seq junctions incorporated into Augustus models 64% of peptide sequences incorporated into Augustus models Predicted Augustus models: 5461 distinct models 1596 novel models

24. Categorisation/Review TAU Models RNA-seq Junctions Augustus Model TAIR confidence rank TAIR Model Peptides (Splice variants, NMD targets) (correction) (colour reflects matching model) Incorrect junction in TAIR model Unsupported exon

25. Example Augustus update

26. Example 2 Augustus update

27. Example Augustus splice variant

28. Example 2 August splice variant

29. Augustus/TAU/Cufflinks Augustus Incorporate 64% of peptides not contained in TAIR, 11 % for RNA-seq junctions 5461 potential updated genes 1596 potential novel genes TAU 30,083 junctions distinct to Augustus or TAIR models 10,902 junctions incorporated into 10,491 TAU models Cufflinks 367 novel assemblies which fall above the 100 bp & >15 FPKM filter #TE-filter applied to AUG and cufflinks models 4

30. Preliminary Results 4 Augustus/TAU/Cufflinks predicted models are classified into categories: Novel genes Updated genes Splice-variants B-list Rejects

31. Preliminary Results 4 Augustus/TAU/Cufflinks predicted models are classified into categories: Novel genes 21 Updated genes 812 Splice-variants 2134 B-list 1586 Rejects 2318

32. Where can you find gene structure data on TAIR? ON GENE MODEL PAGE Graphic of exon-intron structure Coordinates of each exon ON GBROWSE Graphic display of structure and overlapping evidence data ON FTP SITE GFF files with exact structures of each gene model Files with gene confidence ranking information

33. Gene Locus Page

34. Gene Model Page

35. Where can you find gene structure data on TAIR? ON GENE MODEL PAGE Graphic of exon-intron structure Coordinates of each exon ON GBROWSE Graphic display of structure and overlapping evidence data ON FTP SITE GFF files with exact structures of each gene model Files with gene confidence ranking information

36. Gbrowse

37. GBrowse Header Main Browser Window Track Menu

38. Where can you find gene structure data on TAIR? ON GENE MODEL PAGE Graphic of exon-intron structure Coordinates of each exon ON GBROWSE Graphic display of structure and overlapping evidence data ON FTP SITE GFF files with exact structures of each gene model Files with gene confidence ranking information

39. FTP site

42. Where can you find gene structure data on TAIR? ON GENE MODEL PAGE Graphic of exon-intron structure Coordinates of each exon ON GBROWSE Graphic display of structure and overlapping evidence data ON FTP SITE GFF files with exact structures of each gene model Files with gene confidence ranking information

43. Gene Confidence Rank Attributes confidence scores to all exons and gene models based on different types of experimental and computational evidence

44. Assigning A Confidence Rank E1 E4

45. Full support No support

46. New Tools at TAIR N-Browse GBrowse Synteny viewer

47. New Tools at TAIR N-Browse (in collaboration wit the Kris Gunsalus Lab, NYU) GBrowse Synteny viewer

48. N-Browse

49. N-Browse: Finding information about edges (interactions)

50. N-Browse: How to select and move nodes

51. N-Browse: How to visualize GO terms from a selected set of nodes

52. N-Browse: How to load your own file and overlay it with the curated interaction data

53. N-Browse: How to save your session and export your data

54. New Tools at TAIR N-Browse GBrowse Synteny viewer

55. GBrowse Header Main Browser Window Track Menu

56. Alternative gene annotations Eugene (transcript, proteins +) Thierry-Mieg (NCBI) Gnomon (transcript, proteins) Souvorov (NCBI) Aceview (transcript) Sebastien Aubourg Hanada et al 2007 (3633 predicted genes) Identify possible corrections

57. Proteomic Data High-density Arabidopsis proteome map (Baerenfaller. 2008) Incorrect start codon

58. VISTA plot Gbrowse track

59. Transcriptome data

60. Orthologs and Gene Families

61. Variation

62. Promoter Elements

63. Methylation

64. Decorated Fasta file

67. New Tools at TAIR N-Browse GBrowse Synteny viewer Data provided by Pedro Pattyn at the University of Ghent

68. AT5G48000 AT5G48010 AT5G47990

70. www.arabidopsis.org curator@arabidopsis.org www.arabidopsis.org/biocyc curator@arabidopsis.org www.plantcyc.org curator@plantcyc.org

71. Acknowledgements Curators: - Peifen Zhang - Tanya Berardini - David Swarbreck - Kate Dreher - Rajkumar Sasidharan Tech Team : - Bob Muller - Larry Ploetz - Raymond Chetty - Anjo Chi - Vanessa Kirkup - Cynthia Lee - Tom Meyer - Shanker Singh - Chris Wilks AraCyc and TAIR PI and Co-PI Eva Huala Sue Rhee Metabolic Pathway Software: - Peter Karp and SRI group

82. Automated pipeline at TAIR Program for aligned sequence(PASA) Clustered transcripts Resulting gene model Previous gene model Based on a set of rules a decision is made comparison NCBI

83. Gene structure annotation in Arabidopsis NEW: 282 genes; 1056 exons UPDATED: 1254 models; 1144 exons NEW: 1291 genes; 683 exons UPDATED: 3811 models; 4007 exons NEW: 681 genes; 828 exons UPDATED: 10,792 models and 14,050 exons TAIR6

84. How do MOD curators annotate genomes? Experimental & Computational Evidence Automatic pipeline Manual annotation Genome annotation

85. How do MOD curators annotate genomes? Experimental & Computational Evidence Automatic pipeline Manual annotation Genome annotation ESTs cDNAs

86. How do MOD curators annotate genomes? Experimental & Computational Evidence Automatic pipeline Manual annotation Genome annotation

87. How do MOD curators annotate genomes? Experimental & Computational Evidence Automatic pipeline Manual annotation Genome annotation

88. How do MOD curators annotate genomes? Experimental & Computational Evidence Automatic pipeline Manual annotation Genome annotation Alternative gene models Short MS peptides Community submissions …

89. Manual annotation at different MODs Genome editing tool Evidence set Set of annotation rules + +

90. Manual annotation at different MODs Genome editing tool Evidence set Set of annotation rules + + Nucleotide sequence Short peptides Protein similarity Alternative predictions … Apollo (Arabidopsis, Fly) Aceview (Worm) Zmap/Otterlace (Human) Artemis (Pathogen Project) … Exon size Intron size Number of UTRs Coding/Non-coding ratio Splice-junctions …

91. Responsibilities of a gene structure curator ATG TGA GT AG Delete wrongly predicted genes

92. Responsibilities of a gene structure curator ATG TGA GT AG cDNA Update mispredicted exon-intron structure

93. Responsibilities of a gene structure curator ATG TGA GT AG cDNA Update mispredicted exon-intron structure

94. Responsibilities of a gene structure curator ATG TGA GT AG Annotate splice-variants ATGTGA GT AG

95. Responsibilities of a gene structure curator Annotate atypical gene classes * * * ** * * Trans. element Short protein-coding genes Transposable element genes Pseudogenes uORFs (genes within UTR of other genes)

96. Responsibilities of a gene structure curator ATG TGA GT AG Define gene type Protein-coding tRNA snRNA snoRNA rRNA …

97. Categorisation/Review 17,915 total gene models Categorise/Prioritise (CDS length, Blast similarity, gene confidence rank) TAU Models RNA-seq Junctions Augustus Model TAIR confidence rank TAIR Model Peptides (Splice variants, NMD targets) (correction) (colour reflects matching model) Incorrect junction in TAIR model Unsupported exon 5

98. Augustus RNA-seq Junctions = cluster reads Augustus Input: RNA-seq junctions, peptides, ESTs/cDNAs, TAIR models Provide evidence ranking and bonus scores Junction assembly Raw spliced RNA-seq reads (8,819,162 reads) (203,317 Junctions)

99. Examples of large-scale community datasets recently integrated into the Arabidopsis annotation Transposable elements (Quesneville Lab) Pseudogenes (Gerstein Lab) Short MS peptides (Baerenfaller et al, Castellana et al) Short genes (Hanada et al)

100. Model Organism Databases

101. Augustus- Results 4 Augustus models were classified into 4 categories: Novel genes 20 Updated genes 897 Splice-variants 1826 B-list 1173 Rejects 3137

102. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: ESTs and cDNAs serve as main source of experimental data used for genome annotation cDNA s & ESTs Automated annotation Annotated Arabidopsis genome PASA Program To Assemble Spliced Alignments

103. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: ESTs and cDNAs serve as main source of experimental data used for genome annotation cDNA s & ESTs Automated annotation Manual annotation Annotated Arabidopsis genome PASA Program To Assemble Spliced Alignments

104. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: ESTs and cDNAs serve as main source of experimental data used for Arabidopsis genome annotation cDNA s & ESTs Automated annotation Annotated Arabidopsis genome PASA Program To Assemble Spliced Alignments

105. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: ESTs and cDNAs serve as main source of experimental data used for genome annotation cDNA s & ESTs Automated annotation Manual annotation Annotated Arabidopsis genome PASA Program To Assemble Spliced Alignments

106. Arabidopsis gene structure annotation A new approach TAIR6-TAIR9: ESTs and cDNAs serve as main source of experimental data used for genome annotation cDNA s & ESTs Automated annotation Manual annotation Annotated Arabidopsis genome MS peptides RNA-seq data PASA Program To Assemble Spliced Alignments