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 The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform microRNA microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana™ microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods.
The aim of the present study was to define the effect of TGF-β1 on C2C12 myoblasts myogenesis. TGF-β1 together with its receptor is a negative auto-paracrine regulator of myogenesis, which influences the proliferation, differentiation, and functions of muscle cells. TGF-β1 exerts highly significant inhibitory effect on differentiation of C2C12 mouse myoblasts manifested by the impairment of cell fusion and very low expression of myosin heavy chain. The study of differentiating C2C12 mouse myoblasts treated with TGF-β1 revealed 502 genes (436 down-regulated and 66 up-regulated) with statistically different expression. TGF-β1-regulated genes were identified to be involved in 29 biological processes, 29 molecular functions groups and 59 pathways. The strongest inhibiting effect of TGF-β1 was observed in the cadherin and Wnt pathways. The key-genes that could play the role of TGF-β1 targets during myoblasts differentiation was identified such as: Max, Creb1, Ccna2, Bax, MdfI, Tef, Tubg1, Cxcl5, Rho, Calca and Lgals4.
Dendritic cells (DC) are professional antigen-presenting cells capable of initiating primary immune responses. They have been intensively studied and are used in both basic immunology research and clinical immunotherapy. However, the genetic pathways leading to DC differentiation and maturation remain poorly understood. Using focused microarrays with oligonucletotide probes for 120 genes encoding co-stimulatory molecules, chemokines, chemokine receptors, cytokines, cytokine receptors, TLRs, and several other related molecules, we analyzed the kinetics of gene expression for the overall differentiation process of monocytes into mature DC. In parallel, we compared the transcriptional profiles in DC maturation in the presence of LPS, TNF-α or trimeric CD40L. We found similar transcriptional profiles for early immature DC and immature DC, respectively generated by culturing monocytes with GM-CSF and IL-4 for three or six days. We identified sets of common and stimuli-specific genes, the expression of which changed following stimulation with LPS, TNF-α or CD40L. A dynamic analysis of the entire DC differentiation and maturation process showed that some important inflammatory and constitutive chemokines are transcribed in both immature and mature DC. The correlative expression kinetics of the gene pairs IL1R1/IL1R2, IL15/IL15RA, DC-SIGN/ICAM-2 and DC-SIGN/ICAM-3 imply that they all play crucial roles in mediating DC functions. Thus, our analysis with focused microarrays shed light on the transcriptional kinetics of DC differentiation and maturation, and this method may also prove useful for identifying novel marker genes involved in DC functions.
Metastasis is a final step in the progression of mammary gland cancer, usually leading to death. Potentially, a molecular signature of metastasis can be defined via comparison of primary tumors with their metastases. Currently, there is no data in the literature regarding the molecular portrait of metastases in dogs and only few reports regarding human cancer. This is the first report describing the transcriptomic signature of canine cancer metastatic cells. Two adenocarcinoma cell lines isolated from the canine mammary gland (CMT-W1 and CMT-W2) were compared with cell lines isolated from their lung metastases (CMT-W1M and CMT-W2M) with regards to the following cytometric parameters: cell cycle, ploidy, Bcl-2 expression, susceptibility to induced apoptosis, and transcriptomic profile. Cytometric analyses revealed significant differences in cell cycle and antiapoptotic potential between the examined cells. Using oligonucleotide microarrays, we found 104 up-regulated genes in the metastatic cell line CMT - W1M and 21 up-regulated genes in the primary CMT -W1 cell line. We also found 83 up-regulated genes in the CMT-W2M cell line and only 21 up-regulated genes in the CMT-W2 cell line. Among the up-regulated genes in both metastatic cell lines, we found 15 common genes. These differently expressed genes are involved mainly in signal transduction, cell structure and motility, nucleic acid metabolism, developmental processing, and apoptosis (GHSR, RASSF1, ARF1GAP, WDR74, SMOC2, SFRP4, DIAPH1, FSCN1, ALX4, SNX15, PLD2, WNT7B, POU6F2, NKG7, and POLR2F). Seven of them are involved in a cellular pathway dependent on ghrelin via growth hormone secretagogue receptor (GHSR). Our results suggest that this pathway may be essential for mammary cancer cells to have a metastatic potential.
Heterozygous missense mutations in IHH result in Brachydactyly type A1 (BDA1; OMIM 112500), a condition characterized by the shortening of digits due to hypoplasia/aplasia of the middle phalanx. Indian Hedgehog signaling regulates the proliferation and differentiation of chondrocytes and is essential for endochondral bone formation. Analyses of activated IHH signaling in C3H10T1/2 cells showed that three BDA1-associated mutations (p.E95K, p.D100E and p.E131K) severely impaired the induction of targets such as Ptch1 and Gli1. However, this was not a complete loss of function, suggesting that these mutations may affect the interaction with the receptor PTCH1 or its partners, with an impact on the induction potency. From comparative microarray expression analyses and quantitative real-time PCR, we identified three additional targets, Sostdc1, Penk1 and Igfbp5, which were also severely affected. Penk1 and Igfbp5 were confirmed to be regulated by GLI1, while the induction of Sostdc1 by IHH is independent of GLI1. SOSTDC1 is a BMP antagonist, and altered BMP signaling is known to affect digit formation. The role of Penk1 and Igfbp5 in skeletogenesis is not known. However, we have shown that both Penk1 and Igfbp5 are expressed in the interzone region of the developing joint of mouse digits, providing another link for a role for IHH signaling in the formation of the distal digits.
The main aims of this study were to determine the effects of GH gene abuse/misuse in normal animals and to discover genes that could be used as candidate biomarkers for the detection of GH gene therapy abuse/misuse in humans. We determined the global gene expression profile of peripheral whole blood from normal adult male rats after long-term GH gene therapy using CapitalBio 27 K Rat Genome Oligo Arrays. Sixty one genes were found to be differentially expressed in GH gene-treated rats 24 weeks after receiving GH gene therapy, at a two-fold higher or lower level compared to the empty vector group (p < 0.05). These genes were mainly associated with angiogenesis, oncogenesis, apoptosis, immune networks, signaling pathways, general metabolism, type I diabetes mellitus, carbon fixation, cell adhesion molecules, and cytokine-cytokine receptor interaction. The results imply that exogenous GH gene expression in normal subjects is likely to induce cellular changes in the metabolism, signal pathways and immunity. A real-time qRT-PCR analysis of a selection of the genes confirmed the microarray data. Eight differently expressed genes were selected as candidate biomarkers from among these 61 genes. These 8 showed five-fold higher or lower expression levels after the GH gene transduction (p < 0.05). They were then validated in real-time PCR experiments using 15 single-treated blood samples and 10 control blood samples. In summary, we detected the gene expression profiles of rat peripheral whole blood after long-term GH gene therapy and screened eight genes as candidate biomarkers based on the microarray data. This will contribute to an increased mechanistic understanding of the effects of chronic GH gene therapy abuse/misuse in normal subjects.
 Microarray methods have become a basic tool in studies of global gene expression and changes in transcript levels. Affymetrix microarrays from the HGU133 series contain multiple probe-sets complementary to the same gene (4742 genes are represented by more than one probe-set in a microarray HGU133A). Individual probe-sets annotated to the same gene often show different hybridization signals and even opposite trends, which may result from some of them matching transcripts of more than one gene and from the existence of different splice-variant transcripts. Existing methods that redefine probe-sets and develop custom probe-set definitions use mathematical tools such as Matlab or the R statistical environment with the Bioconductor package (Gentleman et al., 2004, Genome Biol. 5: 280) and thus are directed to researchers with a good knowledge of bioinformatics. We propose here a new approach based on the principle that a probe-set which hybridizes to more than one transcript can be recognized because it produces a signal significantly different from others assigned to the particular gene, allowing it to be detected as an outlier in the group and eliminated from subsequent analyses. A simple freeware application has been developed (available at http://www.bioinformatics.aei.polsl.pl) that detects and removes outlying probe-sets and calculates average signal values for individual genes using the latest annotation database provided by Affymetrix. We illustrate this procedure using microarray data from our experiments aiming to study changes of transcription profile induced by ionizing radiation in human cells.
High-density microarrays were recently used to identify the genomic profiles of vascular cells during atherogenesis. This strategy succeeded in identifying both biomarkers and underlying biological processes of the pathological development. However, data documenting the early stages of disease are sparse. To identify the mechanisms involved in atherogenesis, we examined differential gene expression in the aorta of C57BL/6J mice fed a high-fat diet (HFD) or a low-fat diet (LFD), for a short period of time of three weeks. The cDNA microarray analysis revealed that the expression of 448 genes was significantly different between the two groups. As expected, key genes involved in lipid synthesis or catabolism were down- and upregulated, respectively, representing a normal gene expression response to increased cellular lipid levels. Overrepresented biological processes were identified by Gene Ontology (GO) analysis, which revealed that aortic cells differentiate into a new phenotype in mice fed the HFD. This phenotype was represented by changes in the expression of 81 genes associated with extracellular matrix and cytoskeletal modifications. Some of these genes were previously shown to be involved in the cardiovascular diseases process. In conclusion, short-term HFD consumption results in metabolic disturbances leading to a broad induction of genes involved in vessel architecture remodelling.
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Transcriptomic index of skeletal muscle of beef breeds bulls

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In the present study cDNA microarray (18263 probes) were used for analysis of bovine skeletal muscle (m.semitendinosus) transcriptome in 12-month-old bulls of four cattle breeds: Holstein-Friesian (HF), Limousine (LIM), Hereford (HER) and Polish Red (PR), aiming to identify the genes, which expression is common for beef breed bulls. The number of transcripts significantly different from HF bulls muscle amounted to 393, 462 and 638 for LIM, HER and PR, respectively. As a result of this study the transcriptomic index was proposed, being the set of 48 genes expressed similarly in beef breed bulls in comparison to HF bulls. Classification of genes according to molecular function of their protein products has shown the highest number of genes encoding proteins involved in nucleic acid binding (10), regulatory proteins (6), kinases (4) and signaling molecules (3). Classification according to biological processes revealed the highest number of genes involved in protein metabolism i modification (14), signal transduction (5), cell cycle (4), intracellular protein traffic (4), nucleoside, nucleotide and nucleic acid metabolism (4), apoptosis (3), cell structure and motility (3), and cellular transport (3). Since the role of the most genes included to the transcriptomic index has not been described yet in bovine skeletal muscle, obtained results may be very useful in revealing new candidate genes to search a new criteria of animal selection in beef production.
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