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Functional Genomics Consortium: NIDDK (Kaestner) and (Permutt)

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Presentation on theme: "Functional Genomics Consortium: NIDDK (Kaestner) and (Permutt)"— Presentation transcript:

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

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

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. The schema is compliant with the minimum annotations recommended by MGED. MIAME: Minimum Information About a Microarray Experiment (common set of concepts that need to be captured in a database to describe gene expression experiments adequately for interpretation, reproduction or critical assessment). MAML: MicroArray Mark-up Language (XML Document Type Definitions of the concepts).

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 797,028 assemblies 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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