Müller cells acquire a complex and specific reactive phenotype in diabetes characterized by the induction of acute-phase response proteins and other inflammation-related genes. The concomitant upregulation of IL-1beta in the retina of diabetic rats points to this cytokine as a possible mediator of the acute-phase response mounted by Müller cells in diabetes.
We have developed a new tool to visualize expression data on metabolic pathways and to evaluate which metabolic pathways are most affected by transcriptional changes in whole-genome expression experiments. Using the Fisher Exact Test, the method scores biochemical pathways according to the probability that as many or more genes in a pathway would be significantly altered in a given experiment by chance alone. This method has been validated on diauxic shift experiments and reproduces well known effects of carbon source on yeast metabolism. The analysis is implemented with Pathway Analyzer, one of the tools of Pathway Processor, a new statistical package for the analysis of whole-genome expression data. Results from multiple experiments can be compared, reducing the analysis from the full set of individual genes to a limited number of pathways of interest. The pathways are visualized with OpenDX, an open-source visualization software package, and the relationship between genes in the pathways can be examined in detail using Expression Mapper, the second program of the package. This program features a graphical output displaying differences in expression on metabolic charts of the biochemical pathways to which the open reading frames are assigned.[Supplementary materials are available at
CtBP (C-terminal binding protein) is an evolutionarily conserved NAD(H)-dependent transcriptional corepressor, whose activity has been shown to be regulated by the NAD/NADH ratio. Although recent studies have provided significant new insights into mechanisms by which CtBP regulates transcription, the biological function of CtBP remains incompletely understood. Here, we report that genetic inactivation of the Caenorhabditis elegans homolog, ctbp-1, results in life span extension, which is suppressed by reintroduction of the ctbp-1 genomic DNA encoding wild-type but not NAD(H)-binding defective CTBP-1 protein. We show that CTBP-1 possibly modulates aging through the insulin/IGF-1 signaling pathway, dependent on the forkhead transcription factor DAF-16, but independent of the NAD-dependent histone deacetylase SIR-2.1. Genome-wide microarray analysis identifies >200 potential CTBP-1 target genes. Importantly, RNAi inhibition of a putative triacylglycerol lipase gene lips-7(C09E8.2) but not another lipase suppresses the life span extension phenotype. Consistently, metabolic analysis shows that the triacylglycerol level is reduced in the ctbp-1 deletion mutant, which is restored to the wild-type level by RNAi inhibition of lips-7. Taken together, our data suggest that CTBP-1 controls life span probably through the regulation of lipid metabolism.aging ͉ CtBP ͉ transcription corepressor C tBP is a transcriptional corepressor that is evolutionarily conserved from Caenorhabditis elegans to human (1). CtBP shares sequence homology with the NAD/NADH-dependent 2-hydroxy acid dehydrogenases (2-Hacid DH) (2), and has been shown to exhibit dehydrogenase activity in vitro (3-5), although the physiological substrates and functional significance of this enzymatic activity remain unclear. CtBP binds NAD and NADH, and the NAD/NADH ratio appears to regulate the interactions of CtBP with DNA-binding transcription factors (6, 7), suggesting a potential role for CtBP as a sensor of cellular redox states. CtBP represses transcription by recruiting multiple histone modifying enzymes including the histone H3 lysine 9 (H3K9) methyltransferase G9a/HMTase1 and the histone H3 lysine 4 (H3K4) demethylase LSD1 (3,8). Previous studies suggest a role for CtBP in mouse development, apoptosis, and hypoxia-induced tumor migration (9-12). However, by and large, the biology of CtBP is still incompletely understood.Aging is a complex process regulated by an interacting network of factors. The insulin/insulin-like growth factor-1 (IGF-1) signaling pathway, the JNK anti-stress pathway and the mitochondria respiratory chain, have all been shown to regulate the aging process (13). Besides genetic factors, environmental conditions including stress and nutrient availability, have also been demonstrated to influence longevity (13-15). Transcription factors including DAF-16 and the NAD-dependent histone deacetylase SIR2 are at the converging points to integrate these different signals and regulate longevity through modulating gene transcription (13,15). Similar...
BackgroundIn a recent genomic study, Leung et al. used a factorial microarray analysis to identify Smarca4 (Brg1)-regulated genes in micro-dissected zebrafish retinas. Two hundred and fifty nine genes were grouped in three-way ANOVA models which carried the most specific retinal change. To validate the microarray results and to elucidate cellular expression patterns of the significant genes for further characterization, 32 known genes were randomly selected from this group. In situ hybridization of these genes was performed on the same types of samples (wild-type (WT) and smarca4a50/a50 (yng) mutant) at the same stages (36 and 52 hours post-fertilization (hpf)) as in the microarray study.ResultsThirty out of 32 riboprobes showed a positive in situ staining signal. Twenty seven out of these 30 genes were originally further classified as Smarca4-regulated retinal genes, while the remaining three as retinal-specific expression independent of Smarca4 regulation. It was found that 90.32% of the significant microarray comparisons that were used to identify Smarca4-regulated retinal genes had a corresponding qualitative expression change in the in situ hybridization comparisons. This is highly concordant with the theoretical true discovery rate of 95%. Hierarchical clustering was used to investigate the similarity of the cellular expression patterns of 25 out of the 27 Smarca4-regulated retinal genes that had a sufficiently high expression signal for an unambiguous identification of retinal expression domains. Three broad groups of expression pattern were identified; including 1) photoreceptor layer/outer nuclear layer specific expression at 52 hpf, 2) ganglion cell layer (GCL) and/or inner nuclear layer (INL) specific expression at both 36 & 52 hpf, and 3) GCL and/or INL specific expression at 52 hpf only. Some of these genes have recently been demonstrated to play key roles in retinal cell-type specification, differentiation and lamination. For the remaining three retinal-specific genes that are independent of Smarca4 regulation, they all had a subtle expression difference between WT and smarca4a50/a50 retinas as detected by in situ hybridization. This subtle expression difference was also detected by the original microarray analysis. However, the difference was lower than the fold change cut-off used in that study and hence these genes were not inferred as Smarca4-regulated retinal genes.ConclusionsThis study has successfully investigated the expression pattern of 32 genes identified from the original factorial microarray analysis. The results have demonstrated that the true discovery rate for identifying Smarca4-regulated retinal genes is 90.3%. Hence, the significant genes from the microarray study are good candidates for cell-type specific markers and will aid further investigation of retinal differentiation.
Genes never act alone in a biological system, but participate in a cascade of networks. As a result, analyzing microarray data from a pathway perspective leads to a new level of understanding the system. The authors' group has recently developed Pathway Processor (http://cgr.harvard.edu/cavalieri/pp.html), an automatic statistical method to determine which pathways are most affected by transcriptional changes and to map expression data from multiple whole‐genome expression experiments on metabolic pathways. This unit presents applications of the Pathway Processor software.
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