A SAGE approach to discovery of genes involved in autophagic cell death CATGGCGATATTGT CATGGCGCCAATAT CATGGCGCGCATTT CATGGCGTGGGGAT CATGGCTAATAAAT CATGGCTCAAGGAG.

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A SAGE approach to discovery of genes involved in autophagic cell death CATGGCGATATTGT CATGGCGCCAATAT CATGGCGCGCATTT CATGGCGTGGGGAT CATGGCTAATAAAT CATGGCTCAAGGAG CATGGCTGGACTCC CATGGCTGTGGCCA CATGGCTTTCGTGT CATGGCTTTTTGGC CATGGGAACCGACA CATGGGACCGCCCC CATGGGACCGCTCA CATGGGATCACAAT CATGGGCAACGATC CATGGGCAGCAAGC CATGGGCAGCAATT S. Gorski, Genome Sciences Centre, BC Cancer Agency

Types of Programmed Cell death (PCD) (adapted from Baehrecke, 2002) I. Apoptosis II. Autophagic PCD

(adapted from Jiang et al., 1997) autophagic stage-specific synchronous known cell death genes are regulated transcriptionally hr (APF, 18°C) Reverse transcription diap2 rpr hid RT-PCR analysis Drosophila salivary gland PCD 16 hr24 hr26 hr

Overview of SAGE method (Velculescu et al. 1995)

Tag-to-gene Mapping in Drosophila (E. Pleasance, M. Marra and S. Jones, submitted) AAAAA CATGAGGAGTGAAT Gene X Platform: Queryable ACEDB database Resources: Drosophila genomic sequence and annotation (GadFly Release 2) predicted UTRs 259,620 ESTs and full-length cDNAs (BDGP) 5,181 salivary gland 3’ ESTs (GSC)

Salivary gland SAGE Library and tag mapping summary SAGE Library Tags analyzed Transcripts Total transcripts 16 hr34,9893,126 4, hr31,2153, hr30,8232, % 6.2% 6.5% 25.3%

1244 genes are expressed differentially (p<.05) prior to salivary gland PCD 512 genes have associated biological annotations (Gene Ontology in Flybase) 732 genes have unknown functions 377 of these genes were unpredicted (GadFly Release 2) 48 correspond solely to salivary gland ESTs

Validation of SAGE Data I. Quantitative RT-PCR comparison 91/96 (95%) differentially expressed genes were concordant with respect to direction of change (cc = 0.5) II. Identification of known genes Tag Frequency BR-CE74E75E93rprarkdronciap2crq SG16 SG20 SG23 BFTZ-F1 EcR/USP BR-C E74 E93 rpr hid ark dronc crq iap2 Cell Death E75

Gene expression is reduced in a salivary gland death-defective mutant Fold-difference In expression (16 hr vs 23 hr) E93 is an ecdysone-induced gene that encodes a DNA binding protein required for salivary gland cell death (Lee et al., 2000, 2001)

Genes associated with autophagic PCD Expression fold- difference (16 hr vs 23 hr) Protein synthesis Hormone related Trans- cription* Signal transduction Immune response/ TNF-related Apoptosis Autophagy

Strategy for characterizing differentially expressed genes Mutant analysis existing mutants RNAi in vivo (Gal4/UAS) Prioritization mammalian ortholog data mining RNAi in mammalian cells RNAi in tumour models RNAi in Drosophila cells

Mining Expression Data in Drosophila Keyword16 hr23 hrGeneScoreSwissProt IDDatabase Description death015dronc251ICE6_HUMANCASPASE-6 PRECURSOR tumor451botv2044EXL3_HUMANTUMOUR SUPPRESSOR EXL3-LIKE II. Cross-species Expression Profile Comparisons Differential gene expression in Drosophila autophagic cell death Differential gene expression in human cancer (e.g. CGAP) CG4091 upregulated 102-fold in 16 hr vs 23 hr salivary glands SCC-S2 downregulated 7-fold in human mammary gland ductual carcinoma vs normal Orthologs GadFly-SwissProt Homology (tBLASTX) Keyword search of SwissProt comments, keywords and id fields I. Keyword-based Data Mining e.g. Keyword apoptosis: 20 associations; keyword cancer: 33 associations

Mutant analyses indicate that akap200 is required for PCD wild-type (41 hr APF)akap200 EP2254 (41 hr APF) Tag16 hr23 hrP valueGeneGO Molecular Function CGAATAATCC E-19Akap200Protein kinase A anchoring

Acknowledgements BC Cancer Agency BC Cancer Foundation Genome Sciences Centre Victor Ling Marco Marra Suganthi Chittaranjan Doug Freeman Carrie Anderson Shaun Coughlin Claire Hou Steven Jones Erin Pleasance Richard Varhol Scott Zuyderduyn GSC Sequencing Group University of Maryland Biotech Institute Eric Baehrecke University of Washington Stephen Jackson

Mining Gene Expression Data in Drosophila I.Keyword-based Data Mining II. Cross-species Gene Expression Data Mining Differential gene expression in Drosophila autophagic cell death Differential gene expression in human cancer (e.g. CGAP) e.g. CG4091 upregulated prior to Drosophila autophagic PCD (p < ___).and human SCC-S2 (??) SCC-S2 downregulated in human breast cancer(?tissue) compared to normal breast tissue (p < ___) GadFly-SwissProt Homology (tBLASTX) Keyword search of SwissProt comments, keywords and id fields e.g. dronc result “unknown” result

Data mining by sequence similarity searches and keyword queries GadFly – Swissprot Homology (tBLASTX) Keyword query of Swissprot comments, keywords and identification fields tBLASTX search novel EST vs Swissprot Keyword 16 hr 23 hr Gene Sim (%) ScoreLengthSP IDDatabase Description death015dronc ICE6_HUMANCASPASE-6 PRECURSOR apoptosis40debcl BCL2_HUMANAPOPTOSIS REGULATOR BCL-2 apoptosis05Traf TRA1_HUMANTRAF1 autophagy07chrw RB24_MOUSERAS-RELATED PROTEIN RAB-24 cancer115CG MOT1_HUMANMONOCARBOXYLATE TRANSPORT tumor650CG LYOX_HUMANPROT-LYSINE 6-OXIDASE PREC. tumor451botv EXL3_HUMANTUMOUR SUPPRESSOR EXL3-LIKE

1244 genes are differentially expressed prior to salivary gland PCD 16 hour 23 hour 522 genes (12%) are upregulated (p < 0.05) 331 genes (8%) are downregulated 1244 genes 512 genes with biological annotations (Gene Ontology) 732 genes with unknown function 377 of these were unpredicted

Aims 1.Identify the genes involved in autophagic cell death in vivo. 2.Determine which genes are necessary and sufficient for autophagic cell death. 3.Determine if genes function in mammalian autophagic cell death. 4.Identify the autophagic cell death genes associated with human disease and investigate potential as molecular markers and/or therapeutic targets.

Overview of SAGE tag abundance SAGE Library Total tags analyzed Transcripts % of transcripts seen at frequency: > hr34,9893, hr31,2153, hr30,8232, Total number of different transcripts in all three libraries is 4,628.

Questions What is the relationship between Autophagic Cell Death and Cancer? common mechanism in breast and other cancers? gene mutation What is the therapeutic potential of autophagic cell death in cancer? solid tumours apoptotic-resistant tumours

Quantitative RT-PCR validates SAGE data Fold-difference by SAGE Fold-difference by QRT-PCR II. Correlation coefficient between fold-difference values (64 samples): I. Direction of Change: 91/96 samples = 95% concordance Correlation coefficient = 0.5

SAGE Identifies Genes Associated Previously With Salivary Gland Death Tag Frequency BFTZ-F1 EcR/USP BR-C E74 E93 rpr hid ark dronc crq iap2 Cell Death E75

SAGE Identifies Genes Associated Previously With Salivary Gland Death BFTZ-F1 EcR/USP BR-C E74 E93 rpr hid ark dronc crq iap2 Cell Death E75

1244 genes are differentially expressed prior to salivary gland PCD 16 hour 23 hour 522 genes (12%) are upregulated (p < 0.05) 331 genes (8%) are downregulated 1244 genes 512 genes with biological annotations (Gene Ontology) 732 genes with unknown function 377 of these were unpredicted

Genes fail to be differentially expressed in E93 mutant salivary glands Fold difference in expression (16 hr vs 23 hr) Genes E93 is an ecdysone-induced gene that encodes a chromosome binding protein required for salivary gland cell death (Lee et al., 2000, 2001)

An ecdysone induced transcriptional cascade regulates salivary gland cell death BFTZ-F1 EcR/USP BR-C E74 E93 rpr hid ark dronc crq diap2 Cell Death E75

Data mining by sequence similarity searches and keyword queries Keyword 16 hr 23 hr Gene Sim (%) ScoreLengthSP IDDatabase Description death apoptosis autophagy cancer tumor dronc debcl Traf1 chrw CG13907 CG11335 botv ICE6_HUMAN BCL2_HUMAN TRA1_HUMAN RB24_MOUSE MOT1_HUMAN LYOX_HUMAN EXL3_HUMAN CASPASE-6 PRECURSOR APOPTOSIS REGULATOR BCL-2 TRAF1 RAS-RELATED PROTEIN RAB-24 MONOCARBOXYLATE TRANSPORT PROT-LYSINE 6-OXIDASE PREC. TUMOUR SUPPRESSOR EXL3-LIKE GadFly – Swissprot Homology (tBLASTX) Keyword query of Swissprot comments, keywords and identification fields tBLASTX search novel EST vs Swissprot

Salivary gland SAGE Library and tag mapping summary Tag-to-gene mapping (Pleasance, Marra and Jones, submitted) 2866 (61.9%) - known or predicted genes 289 ( 6.2 %) - genomic DNA and EST (but no predicted gene) 1170 (25.3%) - genomic DNA and/or reverse strand of gene 303 ( 6.5%) - no match % 6.2% 6.5% 25.3%