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Lab Members Marie Scearce John Brestelli Catherine Lee Athanasios Arsenlis Phuc Le

Functional Genomics Consortium: NIDDK 56947 (Kaestner) and 56954 (Permutt). Lab Members Marie Scearce John Brestelli Catherine Lee Athanasios Arsenlis Phuc Le Marko Vatamaniuk Collaborators: Gerard Gradwohl (Strasburg) Ihor Lemischka (Princeton). CBIL Chris Stoeckert

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Lab Members Marie Scearce John Brestelli Catherine Lee Athanasios Arsenlis Phuc Le

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  1. Functional Genomics Consortium:NIDDK 56947 (Kaestner) and 56954 (Permutt) Lab Members Marie Scearce John Brestelli Catherine Lee Athanasios Arsenlis Phuc Le Marko Vatamaniuk Collaborators: Gerard Gradwohl (Strasburg) Ihor Lemischka (Princeton) CBIL Chris Stoeckert Elisabetta Manduchi Greg Grant Joan Mazzarelli Phuc Le Angel Pizzaro Deborah F. Pinney Jonathan Crabtree Shannon McWeeney Brian Brunk Consortium Alan Permutt Hiroshi Inoue Doug Melton Sandra Clifton Deana Pape Buddy Brownstein

  2. Functional Genomics of the Developing Endocrine Pancreas • cDNA libraries from pancreatic tissue • Consortium libraries (Currently > 34,000 ESTs) • Pancreatic transcripts: 10,364 EST assemblies (from 25,866 mouse ESTs) • Novel transcripts: 3190 assemblies with only consortium ESTs • relevant dbEST libraries • Microarray studies on pancreatic tissue • Genome wide-survey for genes expressed • Pancreas chip • Validated sequences of interest • Novel sequences from libraries Goal: Identify genes expressed in the developing endocrine pancreas

  3. www.cbil.upenn.edu/EPConDB

  4. CBIL Project Architecture PlasmoDB AllGenes EPConDB Sequence & annotation Gene index (ESTs and mRNAs) Microarray expression data experimental annotation Relational DB (Oracle) with Perl object layer GUS RAD

  5. Identify shared TF binding sites Genomic alignment and comparative Sequence analysis TESS (Transcription Element Search Software) RAD GUS EST clustering and assembly

  6. EPConDB: Content and Features • Pancreas clone sets • Panc Chip Clone sets 1.0, 1.5, 2.0 • Transcripts found in consortium libraries • Novel transcripts discovered from consortium libraries • Microarray results • Using Incyte’s GEM (genome-wide survey) • Using Panc Chip • Genes expressed in pancreas • AllGenes queries: function, chromosomal location, keyword, accession, libraries • Pathways

  7. EPConDB Pathway query

  8. EPConDB Boolean Query

  9. EPConDB History Query

  10. The Future of EPConDB • Display new microarray results • Kaestner: labeling study, developmental series, mutant mice • Central repository for pancreatic experiments • 2-color cDNA, long oligos, Affymetrix, SAGE, etc. • Provide tools for microarray import/export • MGED: MIAME-compliance, MAGE, Ontology [Standard Annotation] • John Hutton/ Ron Taylor (UCHSC) • Beta Cell Biology Consortium? • Starting point for analysis • Provide tools: Xcluster, PaGE, Speed Normalization Package • Download datasets • Coordinate experiments to facilitate comparison • Integrate experiments • With genomic data (AllGenes), proteomics? Atlases? • Build networks Goal: Comprehensive understanding of pancreatic gene expression

  11. Microarray Analysis: Xcluster Xcluster provided by Gavin Sherlock 2001

  12. Microarray Analysis: Data download

  13. Microarray Gene Expression Database group (MGED) International effort on microarray data standards: • Develop standards for storing and communicating microarray-based gene expression data • defining the minimal information required to ensure reproducibility and verifiability of results and to facilitate data exchange (MIAME, MAGEML-MAGEDOM) • collecting (and where needed creating) controlled vocabularies/ ontologies. • developing standards for data comparison and normalization. http://www.mged.org

  14. Future EPConDB Query Result

  15. Microarray Analysis: R statistics

  16. Microarray Analysis: PaGE

  17. Assembled Transcripts About 3 million human EST and mRNA sequences used Combined into 797,028assemblies Cluster into 150,006 “genes” Can identify a protein for 76,771 genes And predict a function for 24,127 genes About 2 million mouse EST and mRNA sequences used Combined into 355,770 assemblies Cluster into 74,024 “genes” Can identify a protein for 34,008 genes And predict a function for 15,403 genes

  18. AllGenes Enhancements: Annotated Entries

  19. AllGenes Enhancements: Genomic Data

  20. Update: Consortium Libraries so far Total Sequences: > 29,000 Mouse in DOTS: 21,196 PancreasAssemblies: 7,294 NOVEL 3,122!

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