Single-Species Microarrays and Comparative Transcriptomics

BACKGROUND: Prefabricated expression microarrays are currently available for only a few species but methods have been proposed to extend their application to comparisons between divergent genomes. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that the hybridization intensity of genomic DNA is a poor basis on which to select unbiased probes on Affymetrix expression arrays for studies of comparative transcriptomics, and that doing so produces spurious results. We used the Affymetrix Xenopus laevis microarray to evaluate expression divergence between X. laevis, X. borealis, and their F1 hybrids. When data are analyzed with probes that interrogate only sequences with confirmed identity in both species, we recover results that differ substantially analyses that use genomic DNA hybridizations to select probes. CONCLUSIONS/SIGNIFICANCE: Our findings have implications for the experimental design of comparative expression studies that use single-species microarrays, and for our understanding of divergent expression in hybrid clawed frogs. These findings also highlight important limitations of single-species microarrays for studies of comparative transcriptomics of polyploid species

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression

BACKGROUND: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication. RESULTS: On a wholly defined dataset, the PL-LM method was able to identify 75% of the differentially expressed genes within 10% of false positives. This accuracy was achieved both using the three replicates per conditions available in the dataset and using only one replicate per condition. CONCLUSION: The method achieves, on this dataset, a higher accuracy than the best set of tools identified by the authors of the dataset, and does so using only one replicate per condition

Molecular analysis of human endometrium: short-term tibolone signaling differs significantly from estrogen and estrogen + progestagen signaling

Tibolone, a tissue-selective compound with a combination of estrogenic, progestagenic, and androgenic properties, is used as an alternative for estrogen or estrogen plus progesterone hormone therapy for the treatment of symptoms associated with menopause and osteoporosis. The current study compares the endometrial gene expression profiles after short-term (21 days) treatment with tibolone to the profiles after treatment with estradiol-only (E2) and E2 + medroxyprogesterone acetate (E2 + MPA) in healthy postmenopausal women undergoing hysterectomy for endometrial prolapse. The impact of E2 treatment on endometrial gene expression (799 genes) was much higher than the effect of tibolone (173 genes) or E2 + MPA treatment (174 genes). Furthermore, endometrial gene expression profiles after tibolone treatment show a weak similarity to the profiles after E2 treatment (overlap 72 genes) and even less profile similarity to E2 + MPA treatment (overlap 17 genes). Interestingly, 95 tibolone-specific genes were identified. Translation of profile similarity into biological processes and pathways showed that ER-mediated downstream processes, such as cell cycle and cell proliferation, are not affected by E2 + MPA, slightly by tibolone, but are significantly affected by E2. In conclusion, tibolone treatment results in a tibolone-specific gene expression profile in the human endometrium, which shares only limited resemblance to E2 and even less resemblance to E2 + MPA induced profiles

Transcribed-ultra conserved region expression is associated with outcome in high-risk neuroblastoma

<p>Abstract</p> <p>Background</p> <p>Neuroblastoma is the most common, pediatric, extra-cranial, malignant solid tumor. Despite multimodal therapeutic protocols, outcome for children with a high-risk clinical phenotype remains poor, with long-term survival still less than 40%. Hereby, we evaluated the potential of non-coding RNA expression to predict outcome in high-risk, stage 4 neuroblastoma.</p> <p>Methods</p> <p>We analyzed expression of 481 Ultra Conserved Regions (UCRs) by reverse transcription-quantitative real-time PCR and of 723 microRNAs by microarrays in 34 high-risk, stage 4 neuroblastoma patients.</p> <p>Results</p> <p>First, the comparison of 8 short- versus 12 long-term survivors showed that 54 UCRs were significantly (<it>P </it>< 0.0491) over-expressed in the former group. For 48 Ultra Conserved Region (UCRs) the expression levels above the cut-off values defined by ROC curves were strongly associated with good-outcome (OS: 0.0001 <<it>P </it>< 0.0185, EFS: 0.0001 <<it>P </it>< 0.0491). Then we tested the Transcribed-UCR (T-UCR) threshold risk-prediction model on an independent cohort of 14 patients. The expression profile of 28 T-UCRs was significantly associated to prognosis and at least 15 up-regulated T-UCRs are needed to discriminate (<it>P </it>< 0.0001) short- from long-survivors at the highest sensitivity and specificity (94.12%). We also identified a signature of 13 microRNAs differently expressed between long- and short-surviving patients. The comparative analysis of the two classes of non-coding RNAs disclosed that 9 T-UCRs display their expression level that are inversely correlated with expression of 5 complementary microRNAs of the signature, indicating a negative regulation of T-UCRs by direct interaction with microRNAs. Moreover, 4 microRNAs down-regulated in tumors of long-survivors target 3 genes implicated in neuronal differentiation, that are known to be over-expressed in low-risk tumors.</p> <p>Conclusions</p> <p>Our pilot study suggests that a deregulation of the microRNA/T-UCR network may play an important role in the pathogenesis of neuroblastoma. After further validation on a larger independent set of samples, such findings may be applied as the first T-UCR prognostic signature for high-risk neuroblastoma patients.</p

Reconstruction of the Core and Extended Regulons of Global Transcription Factors

The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual α-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the α-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks

Global profiling of histone and DNA methylation reveals epigenetic-based regulation of gene expression during epithelial to mesenchymal transition in prostate cells

<p>Abstract</p> <p>Background</p> <p>Previously we reported extensive gene expression reprogramming during epithelial to mesenchymal transition (EMT) of primary prostate cells. Here we investigated the hypothesis that specific histone and DNA methylations are involved in coordination of gene expression during EMT.</p> <p>Results</p> <p>Genome-wide profiling of histone methylations (H3K4me3 and H3K27me3) and DNA methylation (DNAMe) was applied to three cell lines at different stages of a stepwise prostate cell model involving EMT and subsequent accumulation of malignant features. Integrated analyses of epigenetic promoter modifications and gene expression changes revealed strong correlations between the dynamic changes of histone methylations and gene expression. DNA methylation was weaker associated with global gene repression, but strongly correlated to gene silencing when genes co-modified by H3K4me3 were excluded. For genes labeled with multiple epigenetic marks in their promoters, the level of transcription was associated with the net signal intensity of the activating mark H3K4me3 minus the repressive marks H3K27me3 or DNAMe, indicating that the effect on gene expression of bivalent marks (H3K4/K27me3 or H3K4me3/DNAMe) depends on relative modification intensities. Sets of genes, including epithelial cell junction and EMT associated fibroblast growth factor receptor genes, showed corresponding changes concerning epigenetic modifications and gene expression during EMT.</p> <p>Conclusions</p> <p>This work presents the first blueprint of epigenetic modifications in an epithelial cell line and the progeny that underwent EMT and shows that specific histone methylations are extensively involved in gene expression reprogramming during EMT and subsequent accumulation of malignant features. The observation that transcription activity of bivalently marked genes depends on the relative labeling intensity of individual marks provides a new view of quantitative regulation of epigenetic modification.</p

The fallacy of placing confidence in confidence intervals

Interval estimates – estimates of parameters that include an allowance for sampling uncertainty – have long been touted as a key component of statistical analyses. There are several kinds of interval estimates, but the most popular are confidence intervals (CIs): intervals that contain the true parameter value in some known proportion of repeated samples, on average. The width of confidence intervals is thought to index the precision of an estimate; CIs are thought to be a guide to which parameter values are plausible or reasonable; and the confidence coefficient of the interval (e.g., 95 %) is thought to index the plausibility that the true parameter is included in the interval. We show in a number of examples that CIs do not necessarily have any of these properties, and can lead to unjustified or arbitrary inferences. For this reason, we caution against relying upon confidence interval theory to justify interval estimates, and suggest that other theories of interval estimation should be used instead

Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. manifested a reversed pattern.We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment