RESUMO
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.
Assuntos
Bases de Dados Genéticas , Diabetes Mellitus/genética , Células Secretoras de Insulina/metabolismo , Pâncreas/metabolismo , Transcrição Gênica , Animais , Sítios de Ligação , Diabetes Mellitus/metabolismo , Perfilação da Expressão Gênica , Humanos , Internet , Camundongos , Análise de Sequência com Séries de Oligonucleotídeos , Pâncreas/crescimento & desenvolvimento , Regiões Promotoras Genéticas , Software , Fatores de Transcrição/metabolismo , Interface Usuário-ComputadorRESUMO
The mouse PancChip, a microarray developed for studying endocrine pancreatic development and diabetes, represents over 13,000 cDNAs. After computationally assigning the cDNAs on the array to known genes, manual curation of the remaining sequences identified 211 novel transcripts. In microarray experiments, we found that 196 of these transcripts were expressed in total pancreas and/or pancreatic islets. Of 50 randomly selected clones from these 196 transcripts, 92% were confirmed as expressed by qRT-PCR. We evaluated the coding potential of the novel transcripts and found that 74% of the clones had low coding potential. Since the transcripts may be partial mRNAs, we examined their translated proteins for transmembrane or signal peptide domains and found that about 40 proteins had one of these predicted domains. Interestingly, when we investigated the novel transcripts for their overlap with noncoding microRNAs, we found that 1 of the novel transcripts overlapped a known microRNA gene.