<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells
<p>Abstract</p> <p>Background</p> <p>Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. These cytokines modify the expression of hund...
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doaj-7effac1b0ae742beb860c0d8dd59a06c2020-11-25T02:18:56ZengBMCBMC Bioinformatics1471-21052007-02-01815510.1186/1471-2105-8-55<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cellsEizirik Decio Lvan Helden JacquesNaamane Najib<p>Abstract</p> <p>Background</p> <p>Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1β-activated transcription factor (TF) nuclear factor (NF)-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements.</p> <p>Results</p> <p>The performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV) loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee.</p> <p>Conclusion</p> <p>The present <it>in silico </it>analysis allowed us to identify novel regulatory targets of NF-κB using a supervised classification method based on putative binding motifs. This provides new insights into the gene networks regulating cytokine-induced beta-cell dysfunction and death.</p> http://www.biomedcentral.com/1471-2105/8/55 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eizirik Decio L van Helden Jacques Naamane Najib |
spellingShingle |
Eizirik Decio L van Helden Jacques Naamane Najib <it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells BMC Bioinformatics |
author_facet |
Eizirik Decio L van Helden Jacques Naamane Najib |
author_sort |
Eizirik Decio L |
title |
<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells |
title_short |
<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells |
title_full |
<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells |
title_fullStr |
<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells |
title_full_unstemmed |
<it>In silico </it>identification of NF-kappaB-regulated genes in pancreatic beta-cells |
title_sort |
<it>in silico </it>identification of nf-kappab-regulated genes in pancreatic beta-cells |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2007-02-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Pancreatic beta-cells are the target of an autoimmune attack in type 1 diabetes mellitus (T1DM). This is mediated in part by cytokines, such as interleukin (IL)-1β and interferon (IFN)-γ. These cytokines modify the expression of hundreds of genes, leading to beta-cell dysfunction and death by apoptosis. Several of these cytokine-induced genes are potentially regulated by the IL-1β-activated transcription factor (TF) nuclear factor (NF)-κB, and previous studies by our group have shown that cytokine-induced NF-κB activation is pro-apoptotic in beta-cells. To identify NF-κB-regulated gene networks in beta-cells we presently used a discriminant analysis-based approach to predict NF-κB responding genes on the basis of putative regulatory elements.</p> <p>Results</p> <p>The performance of linear and quadratic discriminant analysis (LDA, QDA) in identifying NF-κB-responding genes was examined on a dataset of 240 positive and negative examples of NF-κB regulation, using stratified cross-validation with an internal leave-one-out cross-validation (LOOCV) loop for automated feature selection and noise reduction. LDA performed slightly better than QDA, achieving 61% sensitivity, 91% specificity and 87% positive predictive value, and allowing the identification of 231, 251 and 580 NF-κB putative target genes in insulin-producing INS-1E cells, primary rat beta-cells and human pancreatic islets, respectively. Predicted NF-κB targets had a significant enrichment in genes regulated by cytokines (IL-1β or IL-1β + IFN-γ) and double stranded RNA (dsRNA), as compared to genes not regulated by these NF-κB-dependent stimuli. We increased the confidence of the predictions by selecting only evolutionary stable genes, i.e. genes with homologs predicted as NF-κB targets in rat, mouse, human and chimpanzee.</p> <p>Conclusion</p> <p>The present <it>in silico </it>analysis allowed us to identify novel regulatory targets of NF-κB using a supervised classification method based on putative binding motifs. This provides new insights into the gene networks regulating cytokine-induced beta-cell dysfunction and death.</p> |
url |
http://www.biomedcentral.com/1471-2105/8/55 |
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