928 resultados para Differentially Expressed Genes


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An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local false discovery rate is provided for each gene, and it can be implemented so that the implied global false discovery rate is bounded as with the Benjamini-Hochberg methodology based on tail areas. The latter procedure is too conservative, unless it is modified according to the prior probability that a gene is not differentially expressed. An attractive feature of the mixture model approach is that it provides a framework for the estimation of this probability and its subsequent use in forming a decision rule. The rule can also be formed to take the false negative rate into account.

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An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

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Microarray platforms have been around for many years and while there is a rise of new technologies in laboratories, microarrays are still prevalent. When it comes to the analysis of microarray data to identify differentially expressed (DE) genes, many methods have been proposed and modified for improvement. However, the most popular methods such as Significance Analysis of Microarrays (SAM), samroc, fold change, and rank product are far from perfect. When it comes down to choosing which method is most powerful, it comes down to the characteristics of the sample and distribution of the gene expressions. The most practiced method is usually SAM or samroc but when the data tends to be skewed, the power of these methods decrease. With the concept that the median becomes a better measure of central tendency than the mean when the data is skewed, the tests statistics of the SAM and fold change methods are modified in this thesis. This study shows that the median modified fold change method improves the power for many cases when identifying DE genes if the data follows a lognormal distribution.

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Genetic evidence has implicated several genes as being critical for heart development. However, the inducers of these genes as well as their targets and pathways they are involved with, remain largely unknown. Previous studies in the avian embryo showed that at HH4 Cerberus (cCer) transcripts are detected in the anterior endomesoderm including the heart precursor cells and later in the left lateral plate mesoderm. We have identified a promoter element of chick cCer able to drive EGFP expression in a population of cells that consistently exit from the anterior primitive streak region, from as early as stage HH3+, and that later will populate the heart. Using this promoter element as a tool allowed us to identify novel genes previously not known to potentially play a role in heart development. In order to identify and study genes expressed and involved in the correct development and differentiation of the vertebrate heart precursor cell (HPC) lineages, a differential screening using Affymetrix GeneChip system technologies was performed. Remarkably, this screening led to the identification of more than 700 transcripts differentially expressed in the heart forming regions (HFR). Bioinformatic tools allowed us to filter the large amount of data generated from this approach and to select a few transcripts for in vivo validation. Whole-mount in situ hybridization and sectioning of selected genes showed heart and vascular expression patterns for these transcripts during early chick development. We have developed an effective strategy to specifically identify genes that are differentially expressed in the HPC lineages. Within this set we have identified several genes that are expressed in the heart, blood and vascular lineages, which are likely to play a role in their development. These genes are potential candidates for future functional studies on early embryonic patterning.

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Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Wilms tumor (WT) or nephroblastoma is a genetically heterogeneous pediatric renal tumor that accounts for 6–7% of all childhood cancers in the U.S. WT1, located at 11p13, is the sole WT gene cloned to date. Additional genomic regions containing genes that play a role in the development of Wilms tumor include 11p15, 7p, 16q, 1p, 17q and 19q. This heterogeneity has made it extremely difficult to develop an understanding of the pathways involved in the development of WT, even in the 5–20% of tumors that show mutations at the WT1 locus. My research addresses this gap in our current comprehension of the development of WT. ^ I have used two complementary approaches to extend the current understanding of molecular changes involved in the development of WT. In order to minimize complexities due to genetic heterogeneity, I confined my analysis to the WT1 pathway by assessing those genetically defined tumors that carry WT1 mutations. WT1 encodes a zinc finger transcription factor, and in vitro studies have identified many genes that are potentially regulated in vivo by WT1. However, there is very little in vivo data that suggests that they are transcriptionally regulated endogenously by WT1. In one approach I assessed the role of WT1 in the in vivo regulation of PDGFA and IGF2, two genes that are strong contenders for endogenous regulation by WT1. Using primary tissue samples, I found no correlation between the level of RNA expression of WT1 with either PDGFA or IGF2, suggesting that WT1 does not play a critical role in their expression in either normal kidney or WT. ^ In a parallel strategy, using differential display analysis I compared global gene expression in a subset of tumors with known homozygous inactivating WT1 mutations (WT1-tumors) to the gene expression in a panel of appropriate control tissues (fetal kidney, normal kidney, rhabdoid tumor and pediatric renal cell carcinoma). Transcripts that are aberrantly expressed in this subset of Wilms tumors are candidates for endogenous transcriptional regulation by WT1 as well as for potentially functioning in the development of WT. By this approach I identified several differentially expressed transcripts. I further characterized two of these transcripts, identifying a candidate WT gene in the process. I then performed a detailed analysis of this WT candidate gene, which maps to 7p. Future studies will shed more light on the role of these differentially expressed genes in WT. ^

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A reciprocal subtraction differential RNA display (RSDD) approach has been developed that permits the rapid and efficient identification and cloning of both abundant and rare differentially expressed genes. RSDD comprises reciprocal subtraction of cDNA libraries followed by differential RNA display. The RSDD strategy was applied to analyze the gene expression alterations resulting during cancer progression as adenovirus-transformed rodent cells developed an aggressive transformed state, as documented by elevated anchorage-independence and enhanced in vivo oncogenesis in nude mice. This approach resulted in the identification and cloning of both known and a high proportion (>65%) of unknown sequences, including cDNAs displaying elevated expression as a function of progression (progression-elevated gene) and cDNAs displaying suppressed expression as a function of progression (progression-suppressed gene). Sixteen differentially expressed genes, including five unknown progression-elevated genes and six unknown progression-suppressed genes, have been characterized. The RSDD scheme should find wide application for the effective detection and isolation of differentially expressed genes.

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Background/Aims: Prolactin (PRL) secretion and its gene expression are inhibited by dopamine. Prolactinomas are the most common secreting pituitary adenomas, and dopamine agonists (DA) are the first choice for their treatment. However, a subset of patients is resistant to DA. As the mechanisms involved in DA resistance are not fully understood, the aim of this study was to obtain new insights regarding the molecular differences between the prolactinomas that are responsive to DA and those that are resistant. Methods: Tumor tissue samples were collected from 17 patients who harbored prolactinomas, which were classified as responsive or resistant according to their clinical and laboratorial reaction to DA. The expression of 6 genes was evaluated by real-time polymerase chain reaction: dopamine receptor type 2 (DRD 2), nerve growth factor-beta (NGFB) and its receptor (NGFR), estrogen receptor-alpha (ERA), estrogen receptor-beta (ERB) and the pituitary tumor transforming gene (PTTG). Results: Median DRD 2 and NGFR expression in responsive patients was significantly higher than in resistant ones (p = 0.029 and p = 0.020, respectively). Moreover, the expressions of DRD 2 and NGFR were positively correlated with PRL decrease during treatment (r = 0.66, p = 0.005 and r = 0.57, p = 0.044, respectively). Furthermore, ERB expression was positively correlated to PTTG expression (r = 0.68, p = 0.032) and negatively correlated to NGFB expression (r = -0.75, p = 0.02). Conclusions: DRD2 and NGFR expressions are related to the responsiveness of prolactinoma to DA. However, PTTG, ERB and ERA expressions are not. Also ERB, ERA and PTTG expressions did not present a clear correlation to tumor aggressiveness. Furthermore, the response of prolactinomas to DA should be viewed as a spectrum ranging from the most responsive to the most resistant ones. Copyright (c) 2008 S. Karger AG, Basel

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To identify genes differentially expressed in a strain of the mold Aspergillus nidulans carrying a loss-of-function mutation in palA, a gene in the pH-responsive signal transduction pathway, suppression subtractive hybridization was performed between RNA isolated from the biA1 and biA1 palA1 strains grown under limiting inorganic phosphate at pH 5.0. We have identified several genes upregulated in the biA1 palA1 mutant strain that play important roles in mitotic fidelity, stress responses, enzyme secretion, signal transduction mechanisms, development, genome stability, phosphate sensing, and transcriptional regulation among others. The upregulation of eight of these transcripts was also validated by Northern blot. Moreover, we show that a loss of function mutation in the palA gene drastically reduced the neutral sugar content of the acid phosphatase PacA secreted by the fungus A. nidulans grown at pH 5.0 compared with a control strain.

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Regulatory T cells (Tregs) are characterized by a high expression of IL-2 receptor α chain (CD25) and of forkhead box P3 (FOXP3), the latter being essential for their development and function. Another major player in the regulatory function is the cytotoxic T-lymphocyte associated molecule-4 (CTLA-4) that inhibits cytotoxic responses. However, the regulation of CTLA-4 expression remains less well explored. We therefore studied the microRNA signature of circulating CD4(+) Tregs isolated from adult healthy donors and identified a signature composed of 15 differentially expressed microRNAs. Among those, miR-24, miR-145, and miR-210 were down-regulated in Tregs compared with controls and were found to have potential target sites in the 3'-UTR of FOXP3 and CTLA-4; miR-24 and miR-210 negatively regulated FOXP3 expression by directly binding to their two target sites in its 3'-UTR. On the other hand, miR-95, which is highly expressed in adult peripheral blood Tregs, positively regulated FOXP3 expression via an indirect mechanism yet to be identified. Finally, we showed that miR-145 negatively regulated CTLA-4 expression in human CD4(+) adult peripheral blood Tregs by binding to its target site in CTLA-4 transcript 3'-UTR. To our knowledge, this is the first identification of a human adult peripheral blood CD4(+) Treg microRNA signature. Moreover, unveiling one mechanism regulating CTLA-4 expression is novel and may lead to a better understanding of the regulation of this crucial gene.

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Schistosomiasis affects more than 200 million people worldwide; another 600 million are at risk of infection. The schistosomulum stage is believed to be the target of protective immunity in the attenuated cercaria vaccine model. In an attempt to identify genes up-regulated in the schistosomulum stage in relation to cercaria, we explored the Schistosoma mansoni transcriptome by looking at the relative frequency of reads in EST libraries from both stages. The 400 genes potentially up-regulated in schistosomula were analyzed as to their Gene Ontology categorization, and we have focused on those encoding-predicted proteins with no similarity to proteins of other organisms, assuming they could be parasite-specific proteins important for survival in the host. Up-regulation in schistosomulum relative to cercaria was validated with real-time reverse transcription polymerase chain reaction (RT-PCR) for five out of nine selected genes (56%). We tested their protective potential in mice through immunization with DNA vaccines followed by a parasite challenge. Worm burden reductions of 16-17% were observed for one of them, indicating its protective potential. Our results demonstrate the value and caveats of using stage-associated frequency of ESTs as an indication of differential expression coupled to DNA vaccine screening in the identification of novel proteins to be further investigated as potential vaccine candidates.