891 resultados para Quantitative gene expression
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The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.
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Funding: This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613960 (SMARTBEES) (http://www.smartbees-fp7.eu/) and Veterinary Medicines Directorate, Department for Environment Food & Rural Affairs (Project # VM0517) (https://www.gov.uk/government/organisations/veterinary-medicines-directorate). CHM was supported by a Biosciences Knowledge Transfer Network Biotechnology and Biological Sciences Research Council (KTN-BBSRC CASE) Studentship (BB/L502467/1) (http://www.bbsrc.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We gratefully acknowledge Mr Sebastian Bacz’s expert help and advice with beekeeping.
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Thesis (Master's)--University of Washington, 2016-06
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The aim of our work was to show how a chosen normal-isation strategy can affect the outcome of quantitative gene expression studies. As an example, we analysed the expression of three genes known to be upregulated under hypoxic conditions: HIF1A, VEGF and SLC2A1 (GLUT1). Raw RT-qPCR data were normalised using two different strategies: a straightforward normalisation against a single reference gene, GAPDH, using the 2(-ΔΔCt) algorithm and a more complex normalisation against a normalisation factor calculated from the quantitative raw data from four previously validated reference genes. We found that the two different normalisation strategies revealed contradicting results: normalising against a validated set of reference genes revealed an upregulation of the three genes of interest in three post-mortem tissue samples (cardiac muscle, skeletal muscle and brain) under hypoxic conditions. Interestingly, we found a statistically significant difference in the relative transcript abundance of VEGF in cardiac muscle between donors who died of asphyxia versus donors who died from cardiac death. Normalisation against GAPDH alone revealed no upregulation but, in some instances, a downregulation of the genes of interest. To further analyse this discrepancy, the stability of all reference genes used were reassessed and the very low expression stability of GAPDH was found to originate from the co-regulation of this gene under hypoxic conditions. We concluded that GAPDH is not a suitable reference gene for the quantitative analysis of gene expression in hypoxia and that validation of reference genes is a crucial step for generating biologically meaningful data.
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For obtaining accurate and reliable gene expression results it is essential that quantitative real-time RT-PCR (qRT-PCR) data are normalized with appropriate reference genes. The current exponential increase in postgenomic studies on the honey bee, Apis mellifera, makes the standardization of qRT-PCR results an important task for ongoing community efforts. For this aim we selected four candidate reference genes (actin, ribosomal protein 49, elongation factor 1-alpha, tbp-association factor) and used three software-based approaches (geNorm, BestKeeper and NormFinder) to evaluate the suitability of these genes as endogenous controls. Their expression was examined during honey bee development, in different tissues, and after juvenile hormone exposure. Furthermore, the importance of choosing an appropriate reference gene was investigated for two developmentally regulated target genes. The results led us to consider all four candidate genes as suitable genes for normalization in A. mellifera. However, each condition evaluated in this study revealed a specific set of genes as the most appropriated ones.
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The prognosis of glioblastomas is still extremely poor and the discovery of novel molecular therapeutic targets can be important to optimize treatment strategies. Gene expression analyses comparing normal and neoplastic tissues have been used to identify genes associated with tumorigenesis and potential therapeutic targets. We have used this approach to identify differentially expressed genes between primary glioblastomas and non-neoplastic brain tissues. We selected 20 overexpressed genes related to cell cycle, cellular movement and growth, proliferation and cell-to-cell signaling and analyzed their expression levels by real time quantitative PCR in cDNA obtained from microdissected fresh tumor tissue from 20 patients with primary glioblastomas and from 10 samples of non-neoplastic white matter tissue. The gene expression levels were significantly higher in glioblastomas than in non-neoplastic white matter in 18 out of 20 genes analyzed: P < 0.00001 for CDKN2C, CKS2, EEF1A1, EMP3, PDPN, BNIP2, CA12, CD34, CDC42EP4, PPIE, SNAI2, GDF15 and MMP23b; and NFIA (P: 0.0001), GPS1 (P: 0.0003), LAMA1 (P: 0.002), STIM1 (P: 0.006), and TASP1 (P: 0.01). Five of these genes are located in contiguous loci at 1p31-36 and 2 at 17q24-25 and 8 of them encode surface membrane proteins. PDPN and CD34 protein expression were evaluated by immunohistochemistry and they showed concordance with the PCR results. The present results indicate the presence of 18 overexpressed genes in human primary glioblastomas that may play a significant role in the pathogenesis of these tumors and that deserve further functional investigation as attractive candidates for new therapeutic targets.
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Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.
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Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Quantitative reverse transcriptase real-time PCR (QRT-PCR) is a robust method to quantitate RNA abundance. The procedure is highly sensitive and reproducible as long as the initial RNA is intact. However, breaks in the RNA due to chemical or enzymatic cleavage may reduce the number of RNA molecules that contain intact amplicons. As a consequence, the number of molecules available for amplification decreases. We determined the relation between RNA fragmentation and threshold values (Ct values) in subsequent QRT-PCR for four genes in an experimental model of intact and partially hydrolyzed RNA derived from a cell line and we describe the relation between RNA integrity, amplicon size and Ct values in this biologically homogenous system. We demonstrate that degradation-related shifts of Ct values can be compensated by calculating delta Ct values between test genes and the mean values of several control genes. These delta Ct values are less sensitive to fragmentation of the RNA and are unaffected by varying amounts of input RNA. The feasibility of the procedure was demonstrated by comparing Ct values from a larger panel of genes in intact and in partially degraded RNA. We compared Ct values from intact RNA derived from well-preserved tumor material and from fragmented RNA derived from formalin-fixed, paraffin-embedded (FFPE) samples of the same tumors. We demonstrate that the relative abundance of gene expression can be based on FFPE material even when the amount of RNA in the sample and the extent of fragmentation are not known.
Doxycycline-mediated quantitative and tissue-specific control of gene expression in transgenic mice.
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The tet regulatory system in which doxycycline (dox) acts as an inducer of specifically engineered RNA polymerase II promoters was transferred into transgenic mice. Tight control and a broad range of regulation spanning up to five orders of magnitude were monitored dependent on the dox concentration in the water supply of the animals. Administration of dox rapidly induces the synthesis of the indicator enzyme luciferase whose activity rises over several orders of magnitude within the first 4 h in some organs. Induction is complete after 24 h in most organs analyzed. A comparable regulatory potential was revealed with the tet regulatory system where dox prevents transcription activation. Directing the synthesis of the tetracycline-controlled transactivator (tTA) to the liver led to highly specific regulation in hepatocytes where, in presence of dox, less than one molecule of luciferase was detected per cell. By contrast, a more than 10(5)-fold activation of the luciferase gene was observed in the absence of the antibiotic. This regulation was homogeneous throughout but stringently restricted to hepatocytes. These results demonstrate that both tetracycline-controlled transcriptional activation systems provide genetic switches that permit the quantitative control of gene activities in transgenic mice in a tissue-specific manner and, thus, suggest possibilities for the generation of a novel type of conditional mutants.
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To address the issue of melanocortin-1 receptor (MC1R) expression in non-melanocytic cells, we have quantitatively evaluated the relative expression levels of both MC1R mRNA and protein in a subset of different cell types. Using semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) at high cycle numbers, we detected MC1R mRNA in all cell types examined, including human embryonic kidney-293 (HEK 293) cells, a cell type widely used as a negative control in melanocortin expression studies. Quantitative real-time PCR revealed the highest levels of MC1R transcripts were in melanocytic cells, whereas the keratinocyte and fibroblast cell cultures examined had only a low level of expression, similar to that of HEK 293 cells. Antibody mediated detection of MC1R protein in membrane extracts demonstrated exogenous receptor in MC1R transfected cell lines, as well as endogenous MC1R in melanoma cells. However, radioligand binding procedures were required to detect MC1R protein of normal human melanocytes and no surface expression of MC1R was detected in any of the non-melanocytic cells examined. This was consistent with their low level of mRNA, and suggests that, if present, the levels of surface receptor are significantly lower than that in melanocytes. The capacity of such limited levels of MC1R protein to influence non-melanocytic skin cell biology would likely be severely compromised. Indeed, the MC1R agonist [NIe(4), D-Phe(7)] alpha-melanocyte stimulating hormone (NDP-MSH) was unable to elevate intracellular cyclic adenosine monophosphate (cAMP) levels in the keratinocyte and fibroblast cells examined, whereas a robust increase was elicited in melanocytes. Although there are a variety of cell types with detectable MC1R mRNA, the expression of physiologically significant levels of the receptor may be more restricted than the current literature indicates, and within epidermal tissue may be limited to the melanocyte
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Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.