Nucleic Acids Research Advance Access first published online on October 27, 2006
This version published online on November 7, 2006
Nucleic Acids Research, doi:10.1093/nar/gkl748
© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
EPConDB: a web resource for gene expression related to pancreatic development, beta-cell function and diabetes
Joan M. Mazzarelli*,
John Brestelli,
Regina K. Gorski,
Junmin Liu,
Elisabetta Manduchi,
Deborah F. Pinney,
Jonathan Schug,
Peter White,
Klaus H. Kaestner and
Christian J. Stoeckert, Jr
Department of Genetics, School of Medicine, Center for Bioinformatics, University of Pennsylvania Philadelphia, PA 19104, USA
*To whom correspondence should be addressed. Tel: +1 610 521 1738; Fax: +1 215 573 3111; Email: mazz{at}pcbi.upenn.edu
Received August 9, 2006. Accepted September 22, 2006.
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ABSTRACT
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EPConDB (
http://www.cbil.upenn.edu/EPConDB ) is a public web
site that supports research in diabetes, pancreatic development
and beta-cell function by providing information about genes
expressed in cells of the pancreas. EPConDB displays expression
profiles for individual genes and information about transcripts,
promoter elements and transcription factor binding sites. Gene
expression results are obtained from studies examining tissue
expression, pancreatic development and growth, differentiation
of insulin-producing cells, islet or beta-cell injury, and genetic
models of impaired beta-cell function. The expression datasets
are derived using different microarray platforms, including
the BCBC PancChips and Affymetrix gene expression arrays. Other
datasets include semi-quantitative RT–PCR and MPSS expression
studies. For selected microarray studies, lists of differentially
expressed genes, derived from PaGE analysis, are displayed on
the site. EPConDB provides database queries and tools to examine
the relationship between a gene, its transcriptional regulation,
protein function and expression in pancreatic tissues.
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INTRODUCTION
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Diabetes mellitus is a significant health problem affecting
177 million people worldwide with
4 million deaths per year
attributed to the presence of the disease (
http://www.who.int/diabetes/facts/en/).
Diabetes, resulting from either the immuno-destruction or inadequate
function of insulin-secreting beta cells located in pancreatic
islets, occurs when glucose levels in the blood are not maintained
within a normal range. Over time, high blood glucose levels
can cause damage to almost every organ of the body.
EPConDB, the Endocrine Pancreas Consortium Database, is a public web site that was developed in order to serve the bioinformatics needs of the diabetes research community. The web site provides information about genes expressed in the pancreas. EPConDB, a resource of the Beta Cell Biology Consortium (BCBC, http://www.betacell.org), collects information and data from public sources, BCBC members and diabetes researchers and presents it in a useful manner. Users can easily query EPConDB for annotations and expression results. EPConDB also contains information about reagents publicly available through the BCBC, including the human and mouse PancChips (1,2) and the mouse PromoterChips (3,4). A major research focus of many BCBC members is the analysis of the transcriptional networks guiding the development and differentiation of the endocrine pancreas. EPConDB provides information to assist in the identification of transcription factor binding sites or cis-regulatory modules controlling the transcriptional program regulating development and function of the endocrine pancreas.
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CONTENT
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EPConDB is transcript-based and uses DoTS (Database Of Transcribed
Sequences,
http://www.allgenes.org), a human and mouse transcript
index, which was created from all available mRNA and EST sequences
from GenBank and dbEST. Currently, EPConDB uses release 9 of
human DoTS and release 10 of mouse DoTS. DoTS transcripts are
consensus sequences created from clustering and assembling the
sequences (
Figure 1) and are assigned identifiers, e.g. DT.443798.
Computational annotation is applied to the human and mouse DoTS
transcripts (
5,
6), including Entrez Gene (
7) assignment and
coding potential, and the annotations are included in EPConDB.
DoTS annotation was instrumental in the discovery of novel mouse
transcripts, expressed in the pancreas (
6). DoTS transcripts
are assembled to preserve alternative transcripts, so it is
possible to have more than one DoTS transcript associated with
a particular gene. For example, human
PAX4 has two alternatively
spliced forms (DT.40127947 and DT. 91748890). Associations between
DoTS transcripts and elements on microarray platforms provide
a link to the expression results for Entrez Genes and binding
sites regulating their expression (
Figure 1).
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Figure 1 Concepts and data used in the EPConDB web site. DoTS Transcripts, which are consensus sequences generated by the assembly of ESTs and mRNAs, are associated with elements on microarray platforms based upon their GenBank accession numbers and RefSeqs. Using the arrays, gene expression is determined under multiple experimental conditions. For the PromoterChip, the tiles are assigned DoTS transcripts based upon Entrez Genes. Transcription factor binding site predictions are made in regions conserved between human and mouse that are in or near a PromoterChip tile. Using the PromoterChip, binding sites can be determined experimentally and employed to validate binding site predictions. Overall, the relationship between a gene, its transcriptional regulation and expression under various conditions can be examined. The colored lines represent sequences used to create a DoTS transcript, black lines represent mRNAs or RefSeqs, grey lines ESTs, red lines represent annotated 5' ESTs and blue lines annotated 3' ESTs.
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EPConDB presents expression results obtained using the BCBC
microarrays, e.g. mouse PancChip 6 and human PancChip 1 (
1,
2);
other microarray platforms, e.g. Affymetrix gene expression
arrays (
8) (
Figure 1); and additional expression platforms,
e.g. MPSS [massively parallel signature sequencing (
9)] and
RT–PCR (
10). The expression studies are fully annotated
according to the MIAME (
11) standards including biomaterials
and experimental protocols. Links to RAD (RNA Abundance Database)
(
12) from EPConDB provide additional study information. Currently,
there are 24 studies from 18 different laboratories that can
be downloaded from the EPConDB Experiments page. Annotation
files and protocols, associated with each of the BCBC arrays
are available from the EPConDB Downloads page.
For the BCBC Mouse PromoterChips (5A and 5B), EPConDB supplies the association between DoTS transcripts and the promoter elements (tiles) along with predicted transcription factor binding sites (Figure 1). The mouse PromoterChip 5A has tiles covering proximal and distal promoters while the 5B array has tiles covering proximal and distal promoters, enhancers, microRNA genes and highly conserved regions (13). The binding site predictions are made by considering conserved putative sites in or near a tile. The sites were predicted using positional weight matrices from TRANSFAC (14) and JASPAR (15) and a scoring threshold set to control the false positive and true positive prediction rate. Transcription factor binding data from ‘ChIP-on-chip’ experiments using BCBC mouse PromoterChips (3,4) detects transcription factor target genes and can also be used to validate the predicted binding sites (Figure 1).
EPConDB provides lists of differentially expressed genes, derived from the PaGE (Patterns from Gene Expression) (16) analysis of multiple pancreatic microarray studies. The gene lists are accessed from the Experiments Page and can also be generated using the queries for Up or Down regulated Expression (Table 1). Using these queries, a user can set the fold change parameter to find transcripts differentially expressed within a specified range (Figure 2).
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Figure 2 (A) The results page from a query for transcripts with Down regulated Expression in total pancreas as compared with islet tissue having a fold change in expression between 8-fold and 10-fold and a PaGE confidence of 0.9. Twenty-nine transcripts, including a transcript for the gene, Isl1, ISL1 transcription factor, LIM/homeodomain (islet 1), were returned from the query. (B) The transcript page for DT.489821, a DoTS transcript associated with the gene, Isl1. On the transcript page, annotations are displayed including a link to the T1DBase/EPConDB Gene Page and links to the T1DBase Genome Browser. Links to other views for the transcript such as Protein features, EST anatomy and Expression Profile are also available. (C) The Expression Profile link displays gene expression profiles derived from expression studies. Clicking on an individual profile displays the graph and additional information about the study. (D) The T1DBase GBrowse view shows the transcript aligned to the genome. Other views include the BCBC PromoterChip elements and predicted transcription factor binding sites.
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QUERIES AND DATA-MINING TOOLS
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Queries of EPConDB allow investigators to obtain information
about their genes of interest and to find lists of genes with
common features, e.g. genes regulated by a particular transcription
factor and expressed in a particular tissue. Queries are listed
on the EPConDB Query Transcripts page, accessible from the blue
navigation bar, and are listed in
Table 1. The queries are organized
according to finding transcripts by an identifier, expression
in a tissue, regulation, presence on a microarray, chromosomal
location and annotation, e.g. function. EPConDB provides appropriate
forms for each query, allowing users to specify search parameters
(e.g. human or mouse). Example queries for expression in a tissue
include a novel measure of tissue specificity, termed
Q-value
(
17), to identify transcripts expressed in the pancreas, and
the Transcription Factor Expression query to find transcription
factors expressed in fetal or adult tissues (
10). An example
query for regulation includes using the Predicted Transcription
Factor Target Genes query to find genes regulated by a specific
transcription factor based upon the presence of a predicted
binding site. An example transcript that resulted from a query
for transcripts with Down regulated Expression in pancreas as
compared with purified islets is shown in
Figure 2A.
DoTS transcript annotation is displayed on the EPConDB transcript page (Figure 2B). Links to other annotations or views, available for the transcript, are included on the page. Expression profiles are accessed using the Expression Profile link and are displayed as graphs (Figure 2C). The transcript page also provides links to BCBC web pages describing publicly available antibody reagents. As part of a collaboration between EPConDB and T1DBase (www.t1dbase.org) (18), a type 1 diabetes-specific bioinformatics resource, EPConDB has integrated the T1DBase genome browser (GBrowse) (19), as shown in Figure 2D. The genome browser includes tracks for the BCBC promoter chip tiles, predicted transcription factor binding sites and DoTS transcripts.
As a user queries EPConDB, the web site keeps track of the results using the query history mechanism accessible from the ‘My Transcripts’ button located on each page. The results from queries can be further combined to narrow lists of transcripts. Using the Reportmaker tool, the resulting list of transcripts, are formatted and assembled into a report that can be downloaded. An online tutorial, available from the Help link on the navigation bar, supplies additional query examples. Queries for finding DoTS transcripts, Entrez Genes and accession numbers, associated with elements on the BCBC arrays, are readily available from the EPConDB Home page. A user can also use BLAST (20) to perform similarity searches for their sequence of interest against the human and mouse DoTS transcripts.
A Binding Site Collection Query available from the Analysis link allows users to search for arrangements of binding sites in promoters or introns. The search is performed on genomic sequence using DoTS transcripts aligned to the sequence to guide the search. Users select the distance constraint relative to the putative start of transcription, one or more binding sites to include in the search, how close to each other the binding sites must be and whether or not the order of the binding sites is important. A list of binding sites for pancreas-related factors is provided or the user can define their own sites.
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IMPLEMENTATION
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The EPConDB web interface (version 3.42) is currently implemented
as a Java Servlet. Plans are underway to convert the web site
to Java Server Pages, using a web development kit actively maintained
(
http://www.gusdb.org/wdk/). The underlying database accessed
by EPConDB is a relational database utilizing the Genomics Unified
Schema (GUS,
http://www.gusdb.org ) (
21) and Oracle 10g. The
expression studies are contained in RAD (
http://www.cbil.upenn.edu/RAD ), (
12) a portion of the GUS schema reserved for storing expression
data, analysis and annotations.
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DISCUSSION AND FUTURE PLANS
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Expression studies are continuously added to EPConDB, and contributions
from all sources for relevant studies are welcome. The gene
expression profiles are updated to include results from these
studies. Additional studies are analyzed for differentially
expressed genes and the resulting Gene Lists are added to the
Up or Down regulated Expression Queries. New binding site predictions
for other pancreatic transcription factors (e.g. Nkx2.2) are
included in the Predicted Transcription Factor Target Genes
Query. New versions of human and mouse DoTS transcripts are
under development and will be incorporated into EPConDB.
Current plans for EPConDB include integrating data from transcription factor binding studies including ChIP-on-chip and SACO (serial analysis of chromatin occupancy) (22). The data can provide evidence for the validation of computationally predicted binding sites, thus providing high confidence target genes for transcription factors. As the number of expression studies in EPConDB increases, gene lists, created from joint analysis of multiple studies reflecting genes differentially expressed in the same context (e.g. differentiation of pancreatic cells) will be presented on EPConDB. There is also interest in incorporating data into EPConDB from protein expression studies, including sequences influenced by microRNAs (23) regulating their translation. It is the goal of EPConDB to provide insight into the cis-regulatory modules operating in gene expression networks crucial for the development and differentiation of the endocrine pancreas through integration and analysis of these different data sources.
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ACKNOWLEDGEMENTS
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EPConDB is supported by NIDDK grant, UO1 56947. Funding to pay
the Open Access publication charges for this article was provided
by the NIDDK.
Conflict of interest statement. None declared.
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ABSTRACT
INTRODUCTION