PCxN: The pathway co-activity map: a resource for the unification of functional biology

Transcription

1 PCxN: The pathway co-activity map: a resource for the unification of functional biology Sheffield Institute for Translational Neurosciences Center for Integrative Genome Translation GENOME INFORMATICS Cold Spring Harbor, October 28 - October 31,

2 Process and pathways Protein Kinase activity Process Cyclin dependent pathways Cell Cycle regulation Transcription regulation Processes and pathways Known pathway Known pathway Known pathway Pathways

3 Key Pathways Give me the key pathways that drive [PHENOTYPE]

4 Pathway context What does this pathway do? I m not in interested in this as I don t know [GENESET NAME] How good a target/validation will this be?

5 Context search BLAST Unknown protein sequence MESKALLVLTLAVWLQSLTASRGGVAAADQRRDFIDIESKFALRTPEDTAEDTCHLIPGV Functional match Altschul 1990 J Mol Biol.

6 How do pathways relate to each other? How does my geneset relate to other curated and data derived genesets / pathways? Can I position my experimental signature on a high level map of cellular function? What are the core pathways driving a phenotype? What is the relationship between genetic/ genomic upstream perturbation and the functional phenotype?

7 Describing function We identified multiple pathways that are aberrantly regulated in leukemic stem cells compared with normal Several pathways, including Wnt signaling, MAP Kinase signaling, and Adherens Junction are currently known to be important Novel pathways included Ribosome and T Cell Receptor Signaling The largest functional group is the protein kinase activity of GO molecular function, which contains 103 genes Majeti et al 2009 PNAS

8 Function is not systematically described Curated pathways drive understanding but genomic and functional coverage is incomplete Pathway coverage is for about 6000 genes Many different descriptions of the same pathways exist Data driven pathway definitions require context

9 Data driven: Network maps of the cell Sets of gene clusters tested for enrichment of existing GO terms

10 Data driven: Network maps of the cell GO terms clustered by shared genes and gene interactions Biological machinery captured by both datadriven and manually curated ontologies.

11 Understanding the relative role of a function Gene set enrichment - edges represent mutual overlap Isserlin et al F1000research 2014

12 Systematic pathway representation Gene expression Pathway Expression Compare to database Pathway expression distribution Pathway Fingerprint Gene A Gene B 1 Pathway A Pathway B..... Gene C Gene D 0-1 Gene E Gene F Pathprint: Altschuler et al. Genome Medicine 2012

13 Pathway Co-expression Gene set enrichment methods Pathway co-expression Detect differential expression enrichment Detect common pathway relationships Single-study, relative enrichment of a given gene set Large and diverse collection of studies

14 Building a map of active relationships between pathways Pathway sets Gene Expression Data CP: Canonical pathways (MSigDB) GO: Biological 58,475 Affy Human Genome U133 Plus 2.0 Arrays (GEO) Processes (MSigDB)

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16 Ribosome co-expressed pathways

17 Gene ontology as co-expression

18 Are correlated pathways meaningful? TYPE II DIABETES MELLITUS Top 10 correlated pathways BIOCARTA B LYMPHOCYTE_PATHWAY BIOCARTA CCR5 PATHWAY BIOCARTA LYMPHOCYTE PATHWAY BIOCARTA MONOCYTE PATHWAY KEGG MAPK SIGNALING PATHWAY PID AMB2 NEUTROPHILS PATHWAY PID IL8CXCR1 PATHWAY PID IL8CXCR2 PATHWAY PID NTEGRIN2 PATHWAY PID P38 ALPHA BETA PATHWAY

19 Association and enrichment TYPE II DIABETES MELLITUS Top 10 correlated pathways BIOCARTA B LYMPHOCYTE_PATHWAY BIOCARTA CCR5 PATHWAY BIOCARTA LYMPHOCYTE PATHWAY BIOCARTA MONOCYTE PATHWAY KEGG MAPK SIGNALING PATHWAY PID AMB2 NEUTROPHILS PATHWAY PID IL8CXCR1 PATHWAY PID IL8CXCR2 PATHWAY PID NTEGRIN2 PATHWAY PID P38 ALPHA BETA PATHWAY Significantly enriched Genes from disease compendia

20 Are GSEA enriched pathways correlated? TYPE II DIABETES Gene expression study GEO (GSE25462) 25 skeletal muscle samples: 10 subjects with type 2 diabetes 15 subjects with no family history

21 GSEA pathways PCxN.org Top 10 enriched genesets KEGG SYSTEMIC LUPUS ERYTHEMATOSUS REACTOME CLASS A1 RHODOPSIN LIKE RECEPTORS KEGG TYPE I DIABETES MELLITUS KEGG NEUROACTIVE LIGAND RECEPTOR INTERACTION REACTOME IMMUNOREGULATORY INTERACTIONS BETWEEN LYMPHOID AND NON LYMPHOID CELL PID TOLL ENDOGENOUS PATHWAY NABA SECRETED FACTORS KEGG AUTOIMMUNE THYROID DISEASE KEGG_ASTHMA KEGG_ALLOGRAFT_REJECTION

22 GSEA pathways Top 10 enriched genesets KEGG SYSTEMIC LUPUS ERYTHEMATOSUS REACTOME CLASS A1 RHODOPSIN LIKE RECEPTORS KEGG TYPE I DIABETES MELLITUS KEGG NEUROACTIVE LIGAND RECEPTOR INTERACTION REACTOME IMMUNOREGULATORY INTERACTIONS BETWEEN LYMPHOID AND NON LYMPHOID CELL PID TOLL ENDOGENOUS PATHWAY NABA SECRETED FACTORS KEGG AUTOIMMUNE THYROID DISEASE KEGG_ASTHMA KEGG_ALLOGRAFT_REJECTION

23 GSEA pathways Seeds Neighbours Expanded GSEA enriched pathways KEGG SYSTEMIC LUPUS ERYTHEMATOSUS REACTOME CLASS A1 RHODOPSIN LIKE RECEPTORS KEGG TYPE I DIABETES MELLITUS KEGG NEUROACTIVE LIGAND RECEPTOR INTERACTION REACTOME IMMUNOREGULATORY INTERACTIONS BETWEEN LYMPHOID AND NON LYMPHOID CELL PID TOLL ENDOGENOUS PATHWAY NABA SECRETED FACTORS KEGG AUTOIMMUNE THYROID DISEASE KEGG_ASTHMA KEGG ALLOGRAFT REJECTION REACTOME CHEMOKINE RECEPTORS BIND CHEMOKINES REACTOME BINDING AND ENTRY OF HIV VIRION PID IL12 STAT4 PATHWAY PID IL12 2PATHWAY KEGG HEMATOPOIETIC CELL LINEAGE KEGG GRAFT VERSUS HOST DISEASE* KEGG CHEMOKINE SIGNALING PATHWAY BIOCARTA T HELPER PATHWAY BIOCARTA TCRA PATHWAY KEGG CYTOKINE CYTOKINE RECEPTOR INTERACTION

24 Clustered co-expressed pathways Six major biological functional groups

25 Systematic functional representation High level data derived map of biological interactions Novel contextual relationships that provide mechanistic insight An expansion of GSEA connecting enriched genesets and expanding novel correlations Scaling to de novo genesets, disease gene signatures, drug response signatures

26 We are HIRING PCxN.org Yered Hammurabi Pita-Juarez Sheffield Institute for Translational Neuroscience Centre for Genome Translation David Jones Gabriel Altschuler Sandeep Amberkar Wenbin Wei Claire Green hidelab.wordpress.com