scholarly journals Assessment of gene expression profiles in primary and secondary zoospores of Plasmodiophora brassicae by dot blot and real-time PCR

2013 ◽  
Vol 168 (8) ◽  
pp. 518-524 ◽  
Author(s):  
Jie Feng ◽  
Sheau-Fang Hwang ◽  
Stephen E. Strelkov
Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 911-911 ◽  
Author(s):  
Martin Neumann ◽  
Sandra Heesch ◽  
Stefan Schwartz ◽  
Nicola Gökbuget ◽  
Dieter Hoelzer ◽  
...  

Abstract Abstract 911 Introduction: Recently, a small subgroup of pediatric acute T-lymphoblastic leukemia (T-ALL) was described, which is closely associated with the gene expression profile of early T-cell precursors (ETPs). This subtype, termed ETP-ALL, showed a highly unfavorable outcome compared to non-ETP(='typical')-ALL. Based on the results of Coustan-Smith et al. (Lancet Oncology, 2009), the Italian national study Associazione Italiana Ematologia Oncologia Pediatrica (AIEOP) and St-Jude Children's hospital modified their treatment in children with ETP-ALL to a more intensive regime including stem cell transplantation. ETP-ALL is characterized by a specific immunophenotype (CD1a-, CD8-, CD5weak with expression of stem cell or myeloid markers). Here we explored the existence of ETP-ALL in adults and further studied the molecular characteristics of this specific T-ALL subtype. Patients and methods: We examined the gene expression profiles of 86 adult T-ALL patients obtained from the Microarray Innovations in LEukemia (MILE) multicenter study (HG-U133 Plus 2.0, Affymetrix, Haferlach et al., JCO in press). In addition, bone marrow of 296 patients from the German Acute Lymphoblastic Leukemia Multicenter Study Group (GMALL) were analyzed by flow cytometry and expression levels of BAALC, IGFBP7, MN1, and WT1 were determined by real-time-PCR. Results: Using the published list of differentially expressed genes in ETPs (Coustan-Smith et al. 2009) we performed unsupervised clustering analyses of the 86 T-ALL samples. A cluster of 17 samples (19.8%) displayed an ETP-associated gene expression profile and were defined as ETP-ALL. Comparing the gene expression profiles of ETP-ALL and typical T-ALL, 2065 probe sets were differentially expressed in ETP-ALL (FDR 0.05). In addition to genes used for classification, we also identified genes known to be involved in the pathogenesis of T-ALL (e.g. PROM1, BCL2, LMO2, LYL1). In particular, stem cell associated genes such as, BAALC (2.52-fold, p=0.003), IGFBP7 (2.76-fold, p=0.002) or MN1 (3.41-fold, p<0.001) were upregulated in ETP-ALL, whereas HOX11 (45-fold, p=0.004), a marker for thymic T-ALL, was downregulated. An independent cohort of 297 patient samples from the GMALL study group was examined by flow cytometry and real-time PCR. 19 (6.4%) samples revealed the ETP-ALL immunophenotype. As expected, all patient samples were found in the group of early T-ALL, representing 23.5% of all early T-ALLs. There was a significant correlation between a lower leukocyte count at first diagnosis and the classification of ETP-ALL (p=0.001). Gene expression measured by real-time-PCR was performed for genes associated with poor outcome in T-ALL: BAALC (2.11-fold, p<0.001) and IGFBP7 (3.59-fold, p=0.003) were significantly upregulated in the group of ETP-ALL. Similarly, the genes MN1 (4.52-fold, p<0.001) and WT1 (2.76-fold, p=0.036), described as poor prognostic markers in cytogenetically normal AML, were also upregulated in ETP-ALL. Conclusion: In adult T-ALL, a subset of patients shares the gene expression profil and immunophenotype of ETP-ALL, which is in line with recent findings in pediatric patients. The gene expression profile of this subset is significantly correlated to stem cell associated markers predictive for inferior outcome in T-ALL. Interestingly, adverse factors in CN-AML are also aberrantly expressed in ETP-ALL suggesting a myeloid origin of ETPs and indicating a closer relationship between ETP-ALL and AML. The prognostic impact and the determination of the most appropiate set of markers needs to be further investigated. These results support the GMALL strategy to regard early T-ALL patients as high risk with assignment to stem cell transplantation. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Equity Ownership.


Author(s):  
Zuobing Yan ◽  
Yongli Li ◽  
Zhou Zhou ◽  
Yongan Zhang ◽  
Liangjian Qu

Carposina sasakii is one of the most important pests on the quality of stone and pome fruits. Investigation of a gene expression level in the species is hampered because of the gap of validated reference genes. The expression variation in the transcription levels of eight candidate reference genes, Actin (ACT), Tubulinbeta-1 (TUB), Ribosomal protein 49 (RP49), Elongation factor1-alpha (EF-1a), Elongation factor1-b (EF-1b), Elongation factor1-d (EF-1d), Ribosomal proteinL13 (RPL13) and Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), were analyzed by quantitative real-time PCR (qPCR). The stability and ranking of these gene expression profiles in three organ types (head, thorax and abdomen), three developmental stages (larva, pupa and moth), and five diapause states (non-diapause, pre-diapause, diapause 0 d, diapause 20 d and diapause 60 d) were assessed using two algorithm-based methods, geNorm and NormFinder. EF-1a, ACT and GAPDH were evaluated to be the three stable reference genes based on the important observations and comprehensive analysis, whereas TUB and EF-1b showed low expression stability. Best gene combinations for different qPCR analysis in C. sasakii could be chosen from the three stable reference genes, the using of two reference genes is sufficient to effectively normalize qPCR data in C. sasakii. The study laid the foundation for gene expression analysis in C. sasakii and provided new information for the selection of reference genes.


2010 ◽  
Vol 14 (6) ◽  
pp. 321-336 ◽  
Author(s):  
VINCENT A. FUNARI ◽  
KONSTANTIN VOEVODSKI ◽  
DIMITRY LEYFER ◽  
LAURA YERKES ◽  
DONALD CRAMER ◽  
...  

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 5064-5064
Author(s):  
L. Ozbun ◽  
T. Bonome ◽  
M. E. Johnson ◽  
M. Radonovich ◽  
C. Pise-Masison ◽  
...  

5064 Background: The purpose of this study was to identify a predictive gene signature for chemoresponse in patients with advanced stage papillary serous ovarian cancer. Methods: Expression profiling was performed on 50 chemonaive, microdissected advanced stage papillary serous ovarian cancers using Affymetrix Human Genome U133 Plus 2.0 microarrays. Chemoresistance was defined as disease progression while the patients remained on primary chemotherapy. Nine normal human ovarian surface epithelial (HOSE) brushings were also assessed to quantify normal gene expression levels. Validation was performed by quantitative real time PCR using the HOSE isolates and microdissected ovarian tumor samples. Results: A supervised learning algorithm applied to genes differentially expressed between chemosensitive/resistance tumors (p < 0.001) using leave-one-out cross-validation (LOOCV), identified over 2000 genes associated with tumor chemosensitivity. The chemoresponsive gene list was further refined to 576 genes by including only genes used for all LOOCV iterations. An independent gene list was generated comparing expression profiles of chemoresistant tumors to HOSE. The two lists were compared to identify common genes, generating final classifier list of 75 genes that included genes involved in apoptosis, RNA processing, protein ubiquitination, transcription regulation, and other novel genes. We hypothesized genes identified in both data sets would be predictive and biologically relevant. Of these 75 genes, 20 were validated by real-time PCR. Validated genes were ranked by a univariate t-stat value to further resolve the predictor. 4 multivariate predictor algorithms demonstrated the 10 top ranked validated genes maximixed prediction accuracy (compound covariate, 91%; diagonal linear discriminant analysis, 91%; 3-nearest neighbor, 86%; nearest centroid, 95%). The predictive value of these genes will be evaluated on an independent sample set. Conclusions: Gene expression profiling can distinguish between chemosensitive and chemoresistant ovarian cancers. This signature can predict response to therapy and has identified novel biologically and clinically relevant targets. No significant financial relationships to disclose.


2006 ◽  
Vol 18 (2) ◽  
pp. 160
Author(s):  
S. Mamo ◽  
Sz. Bodo ◽  
Z. Polgar ◽  
A. Dinnyes

Very little is known about the effect of vitrification on gene functions after warming. The goals of our study were to examine the transcript variations and identify genes most affected by the treatment. For this, 8-cell-stage embryos were collected from female ICR mice mated with ICR males. The embryos were washed with CZB-HEPES base medium and suspended briefly in equilibrium medium consisting of 4% ethylene glycol (EG) in base medium at room temperature. Following equilibration, the embryos were vitrified in a 35% EG, 0.4 M trehalose, 5% polyvinylpyrrolidone (PVP) solution by means of a solid-surface vitrification (SSV) technique as described earlier (Dinnyes 2000 Biol. Reprod. 63, 513-518). Then 40 embryos each from the control and the vitrified/warmed groups were cultured in CZB medium for 3 h. Total RNAs were extracted from cultured embryos in each group using TRIzol (Invitrogen, Bio-Science, Ltd., Budapest, Hungary), following the manufacturer's instructions. Two rounds of amplification were employed to produce labeled RNA, using low input RNA amplification kit (Agilent Technologies, Kromat, Ltd., Budapest, Hungary) procedures with modifications. Three micrograms of contrasting RNA samples were hybridized on the Agilent Mouse 22K oligonucleotide slides with subsequent analysis of the results. Moreover, as an independent analysis tool, real time PCR was used with eight designed primers. All of the vitrified embryos were recovered after warming with no morphological signs of cryodamage and used for analysis. The two rounds of amplification yielded 15-16 �g of cRNA. The analysis of repeated hybridizations by Rosetta luminator software (Agilent) showed 20 183 genes and expressed sequence tags (ESTs) that passed the selection criteria and were identified as common signatures in all of the slides. Unsupervised analysis of the gene expression data identified a total of 631 differentially expressed (P < 0.01) genes. However, to support the reliability of the results, only those variations above 1.5 fold differences were considered as significant in the final analysis. Therefore, with this stringent criterion 183 genes were differentially expressed (P < 0.01), of which 109 were up-regulated and the remainder down-regulated. Although genes have multiple and overlapping functions, most of the differentially expressed genes were functionally classified into various physiological categories. These include stress response (8), apoptosis related (6), metabolism (51), temperature response (4), and transcription regulation (15). Moreover, the independent analysis with real time PCR and unamplified samples verified the results of microarray. Thus, based on confirmation of the results by an independent analysis and support by the previous studies for some of the genes, it is possible to conclude that the expression patterns reflect the true biological image of embryos after vitrification, with most effects on stress- and cell metabolism-related genes. This work was supported by EU FP6 (MEXT-CT-2003-59582), Wellcome Trust Foundation (Grant No. 070246), and National Office of Research and Technology (NKTH) (#BIO-00017/2002, #BIO-00086/2002).


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