The Prostate Expression Database (PEDB) is a curated relational database and suite of analysis tools designed for the study of prostate gene expression in normal and disease states. Expressed Sequence Tags (ESTs) and full-length cDNA sequences derived from more than 40 human prostate cDNA libraries are maintained and represent a wide spectrum of normal and pathological conditions. Detailed library information including tissue source, library construction methods, sequence diversity and abundance are available in a library archive. Prostate ESTs are assembled into distinct species groups using the multiple alignment program CAP2 or Phrap and are annotated with information from Genbank, dbEST, and the Unigene public sequence databases. Annotated sequences in PEDB are searched using the BLAST algorithm or a gene description keyword. The differential expression of each EST species can be viewed across all libraries using a Virtual Expression Analysis Tool (VEAT), a graphical user interface written in Java for intra- and inter-library species comparisons. Navigation through the user sites is facilitated using a navigation bar located in the header of each database page.

Future developments to the database will provide:

functional sequence annotations

cDNA microarray expression data

proteomics-based gene expression data

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We have 84832 ESTs currently in our database

These libraries are made from normal and cancerous prostate tissue

There are 38 libraries in our database

18 libraries are maintained by FHCRC and UW, sequenced by our lab

20 libraries are from the NCI CGAP project

ESTs are constantly loaded into the database by downloading the sequence fasta files from NCBI for the NCBI libraries. These files are used to download the chromat (quality files) for each of the databases. The in-house library chromats are copied from archive directories.


phd files (quality data in a different format) must be generated from the fasta file and the phd files in order to continue. Since generating phd files adds data to the sequence, a new fasta file must be made and the phd files and the new fasta file are used in the filtering process.


Example of fasta and fasta.qual file we have in the database for an est:


FASTA FASTA.QUAL

>136921 122_12_L22_27 UW_LNCaP01


ctcgtctca ctataggga aagctggtac gcctgcagg taccggtccg gatttcccgg gtcgacccac gcgtccgtgt gaatgtctca ctacaaaatg acttgagtcc agtgaaatct cattagggtt taagaatatt tcagggatcc ttattgtttt gatttttgtt ttctgaaatt ggattttat tttattttat ctta >136921 122_12_L22_27 UW_LNCaP01



 

 Statistical Differential Expression Tool (non-java)

Head to Head comparison Displays a list of genes that are differentially expressed between two user-selected libraries. Shows frequency of EST per library, calculates a P value, and displays a Unigene accession number and description.

Virtual Expression Analysis Tool (java)

Example An example of the VEAT tool on a correctly configured browser

Choose Version This java tool allows researchers to display a cDNA library from PEDB on a plot, display a head to head comparison of two libraries or group libraries together under a user-defined name and display differences between groups

Prostate Proteome analyses of androgen-regulated gene expression. As described elsewhere in the PEDB, our efforts have focused on defining the prostate transcriptome through the production and assembly of Expressed Sequence Tags (ESTs) derived from prostate cDNA libraries representing a wide spectrum of normal and neoplastic states (1,2). These EST assemblies have been used to construct cDNA microarrays suitable for interrogating the prostate transcriptome in experiments designed to examine specific biological pathways that are hypothesized to be involved in prostate carcinogenesis. The molecular pathway mediating androgenic hormone action on prostate cells is a specific focus of our work (3,4). In order to fully understand the functional architecture of prostate gene networks, our next level of analysis incorporates studies of the prostate proteome. The infrastructure established for transcriptome studies further facilitates proteome analysis by providing a comprehensive prostate sequence database for identifying and annotating known and unknown proteins displayed by 2-D gel electrophoresis (2-DE) and analyzed by mass spectrometry (MS) (5). Our objectives for delineating the molecular network(s) influenced by androgen receptor activation are to identify specific targets that promote the differentiation and apoptotic potential of prostate cancer cells while reducing their proliferative drive.