Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip studies

BACKGROUND: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with known concentration are often used to assess the relative performance of probe set algorithms. Given the fact that the spiked-in cRNAs do not represent endogenously expressed genes in experiments, it becomes increasingly important to have methods to study whether a particular probe set algorithm is more appropriate for a specific dataset, without using such external reference data. RESULTS: We propose the use of the probe set redundancy feature for evaluating the performance of probe set algorithms, and have presented three approaches for analyzing data variance and result bias using two sample t-test statistics from redundant probe sets. These approaches are as follows: 1) analyzing redundant probe set variance based on t-statistic rank order, 2) computing correlation of t-statistics between redundant probe sets, and 3) analyzing the co-occurrence of replicate redundant probe sets representing differentially expressed genes. We applied these approaches to expression summary data generated from three datasets utilizing individual probe set algorithms of MAS5.0, dChip, or RMA. We also utilized combinations of options from the three probe set algorithms. We found that results from the three approaches were similar within each individual expression summary dataset, and were also in good agreement with previously reported findings by others. We also demonstrate the validity of our findings by independent experimental methods. CONCLUSION: All three proposed approaches allowed us to assess the performance of probe set algorithms using the probe set redundancy feature. The analyses of redundant probe set variance based on t-statistic rank order and correlation of t-statistics between redundant probe sets provide useful tools for data variance analysis, and the co-occurrence of replicate redundant probe sets representing differentially expressed genes allows estimation of result bias. The results also suggest that individual probe set algorithms have dataset-specific performance

Prediction of synergistic transcription factors by function conservation

A new strategy is proposed for identifying synergistic transcription factors by function conservation, leading to the identification of 51 homotypic transcription-factor combinations

Promoter analysis of intestinal genes induced during iron-deprivation reveals enrichment of conserved SP1-like binding sites

<p>Abstract</p> <p>Background</p> <p>Iron-deficiency leads to the induction of genes related to intestinal iron absorption and homeostasis. By analyzing a large GeneChip^®dataset from the rat intestine, we identified a large cluster of 228 genes that was induced by iron-deprivation. Only 2 of these genes contained 3' iron-response elements, suggesting that other regulation including transcriptional may be involved. We therefore utilized computational methods to test the hypothesis that some of the genes within this large up-regulated cluster are co-ordinately regulated by common transcriptional mechanisms. We thus identified promoters from the up-regulated gene cluster from rat, mouse and human, and performed enrichment analyses with the Clover program and the TRANSFAC database.</p> <p>Results</p> <p>Surprisingly, we found a strong statistical enrichment for SP1 binding sites in our experimental promoters as compared to background sequences. As the TRANSFAC database cannot distinguish among SP/KLF family members, many of which bind similar GC-rich DNA sequences, we surmise that SP1 or an SP1-like factor could be involved in this response. In fact, we detected induction of SP6/KLF14 in the GeneChip^®studies, and confirmed it by real-time PCR. Additional computational analyses suggested that an SP1-like factor may function synergistically with a FOX TF to regulate a subset of these genes. Furthermore, analysis of promoter sequences identified many genes with multiple, conserved SP1 and FOX binding sites, the relative location of which within orthologous promoters was highly conserved.</p> <p>Conclusion</p> <p>SP1 or a closely related factor may play a primary role in the genetic response to iron-deficiency in the mammalian intestine.</p

Identification of interacting transcription factors regulating tissue gene expression in human

<p>Abstract</p> <p>Background</p> <p>Tissue gene expression is generally regulated by multiple transcription factors (TFs). A major first step toward understanding how tissues achieve their specificity is to identify, at the genome scale, interacting TFs regulating gene expression in different tissues. Despite previous discoveries, the mechanisms that control tissue gene expression are not fully understood.</p> <p>Results</p> <p>We have integrated a function conservation approach, which is based on evolutionary conservation of biological function, and genes with highest expression level in human tissues to predict TF pairs controlling tissue gene expression. To this end, we have identified 2549 TF pairs associated with a certain tissue. To find interacting TFs controlling tissue gene expression in a broad spatial and temporal manner, we looked for TF pairs common to the same type of tissues and identified 379 such TF pairs, based on which TF-TF interaction networks were further built. We also found that tissue-specific TFs may play an important role in recruiting non-tissue-specific TFs to the TF-TF interaction network, offering the potential for coordinating and controlling tissue gene expression across a variety of conditions.</p> <p>Conclusion</p> <p>The findings from this study indicate that tissue gene expression is regulated by large sets of interacting TFs either on the same promoter of a gene or through TF-TF interaction networks.</p

Plasma exosomes from children with juvenile dermatomyositis are taken up by human aortic endothelial cells and are associated with altered gene expression in those cells

BACKGROUND: The pathology of juvenile dermatomyositis (JDM) is characterized by prominent vessel wall and perivascular inflammation. This feature of the disease has remained unexplained and under-investigated. We have hypothesized that plasma exosomes, which play an important role in inter-cellular communication, may play a role in the vascular injury associated with JDM. OBJECTIVE: To characterize the circulating exosomes of children with JDM and determine whether the small RNA cargoes within those exosomes are capable of altering transcriptional programs within endothelial cells. DESIGN/METHODS: We purified exosomes from plasma samples of children with active, untreated JDM (n = 6) and healthy controls (n = 9). We characterized the small RNA cargoes in JDM and control exosomes by RNA sequencing using the Illumina HiSeq 2500 platform. We then incubated isolated exosomes from healthy controls and children with JDM with cultured human aortic endothelial cells (HAEC) for 24 h. Fluorescence microscopy was used to confirm that both control and JDM exosomes were taken up by HAEC. RNA was then purified from HAEC that had been incubated with either control or JDM exosomes and sequenced on the Illumina platform. Differential expression of mRNAs from HAEC incubated with control or JDM exosomes was ascertained using standard computational methods. Finally, we assessed the degree to which differential gene expression in HAEC could be attributed to the different small RNA cargoes in JDM vs control exosomes using conventional and novel analytic methods. RESULTS: We identified 10 small RNA molecules that showed differential abundance when we compared JDM and healthy control exosomes. Fluorescence microscopy of labeled exosomes confirmed that both JDM and control exosomes were taken up by HAEC. Differential gene expression analysis revealed 59 genes that showed differential expression between HAEC incubated with JDM exosomes vs HAEC incubated with exosomes from controls. Statistical analysis of gene expression data demonstrated that multiple miRNAs exerted transcriptional control on multiple genes with HAEC. CONCLUSIONS: Plasma exosomes from children with active, untreated JDM are taken up by HAEC and are associated with alterations in gene expression in those cells. These findings provide new insight into potential mechanisms leading to the targeting of vascular tissue by the immune system in JDM

Optimal Delay Time of CT Perfusion for Predicting Cerebral Parenchymal Hematoma After Intra-Arterial tPA Treatment

Background and Purpose: Cerebral hemorrhage is a serious potential complication of stroke revascularization, especially in patients receiving intra-arterial tissue-type plasminogen activator (tPA) therapy. We investigated the optimal pre-intervention delay time (DT) of computed tomography perfusion (CTP) measurement to predict cerebral parenchymal hematoma (PH) in acute ischemic stroke (AIS) patients after intra-arterial tissue plasminogen activator (tPA) treatment.Methods: The study population consisted of a series of patients with AIS who received intra-arterial tPA treatment and had CTP and follow-up computed tomography/magnetic resonance imaging (CT/MRI) to identify hemorrhagic transformation. The association of increasing DT thresholds (&gt;2, &gt;4, &gt;6, &gt;8, and &gt;10 s) with PH was examined using receiver operating characteristic (ROC) analysis and logistic regression.Results: Of 94 patients, 23 developed PH on follow-up imaging. Receiver operating characteristic analysis revealed that the greatest area under the curve for predicting PH occurred at DT &gt; 4 s (area under the curve, 0.66). At this threshold of &gt; 4 s, DT lesion volume ≥ 30.85 mL optimally predicted PH with 70% sensitivity and 59% specificity. DT &gt; 4 s volume was independently predictive of PH in a multivariate logistic regression model (P &lt; 0.05).Conclusions: DT &gt; 4 s was the parameter most strongly associated with PH. The volume of moderate, not severe, hypo-perfusion on DT is more strongly associated and may allow better prediction of PH after intra-arterial tPA thrombolysis

Genomic Analysis Highlights the Role of the JAK-STAT Signaling in the Anti-proliferative Effects of Dietary Flavonoid—‘Ashwagandha’ in Prostate Cancer Cells

Phytochemicals are dietary phytoestrogens that may play a role in prostate cancer prevention. Forty percent of Americans use complementary and alternative medicines (CAM) for disease prevention and therapy. Ashwagandha (Withania somnifera) contains flavonoids and active ingredients like alkaloids and steroidal lactones which are called ‘Withanolides’. We hypothesize that the immunomodulatory and anti-inflammatory properties of Ashwagandha might contribute to its overall effectiveness as an anti-carcinogenic agent. The goal of our study was gain insight into the general biological and molecular functions and immunomodulatory processes that are altered as a result of Ashwagandha treatment in prostate cancer cells, and to identify the key signaling mechanisms that are involved in the regulation of these physiological effects using genomic microarray analysis in conjunction with quantitative real-time PCR and western blot analysis. Ashwagandha treatment significantly downregulated the gene and protein expression of proinflammatory cytokines IL-6, IL-1β, chemokine IL-8, Hsp70 and STAT-2, while a reciprocal upregulation was observed in gene and protein expression of p38 MAPK, PI3K, caspase 6, Cyclin D and c-myc. Furthermore, Ashwagandha treatment significantly modulated the JAK-STAT pathway which regulates both the apoptosis process as well as the MAP kinase signaling. These studies outline several functionally important classes of genes, which are associated with immune response, signal transduction, cell signaling, transcriptional regulation, apoptosis and cell cycle regulation and provide insight into the molecular signaling mechanisms that are modulated by Ashwagandha, thereby highlighting the use of this bioflavanoid as effective chemopreventive agent relevant to prostate cancer progression