Diagnosing Smith–Magenis Syndrome and Duplication 17p11.2 Syndrome byRAI1Gene Copy Number Variation Using Quantitative Real-Time PCR

2008 ◽  
Vol 12 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Hoa T. Truong ◽  
Sara Solaymani-Kohal ◽  
Kevin R. Baker ◽  
Santhosh Girirajan ◽  
Stephen R. Williams ◽  
...  
2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Tamaya Castro Ribeiro ◽  
Alexander Augusto Jorge ◽  
Madson Q. Almeida ◽  
Beatriz Marinho de Paula Mariani ◽  
Mirian Yumi Nishi ◽  
...  

Context.IGF1Roverexpression appears to be a prognostic biomarker of metastatic pediatric adrenocortical tumors. However, the molecular mechanisms that are implicated in its upregulation remain unknown.Aim. To investigate the potential mechanisms involved inIGF1Roverexpression.Patients and Methods. We studied 64 adrenocortical tumors.IGF1Rcopy number variation was determined in all patients using MLPA and confirmed using real time PCR. In a subgroup of 32 patients, automatic sequencing was used to identifyIGF1Rallelic variants and the expression of microRNAs involved inIGF1Rregulation by real time PCR.Results.IGF1Ramplification was detected in an adrenocortical carcinoma that was diagnosed in a 46-year-old woman with Cushing’s syndrome and virilization.IGF1Roverexpression was demonstrated in this case. In addition, gene amplification of otherlociwas identified in this adrenocortical malignant tumor, but noIGF1Rcopy number variation was evidenced in the remaining cases. Automatic sequencing revealed three known polymorphisms but they did not correlate with its expression. Expression of miR-100, miR-145, miR-375, and miR-126 did not correlate withIGF1Rexpression.Conclusion. We demonstrated amplification and overexpression ofIGF1Rgene in only one adrenocortical carcinoma, suggesting that these combined events are uncommon. In addition,IGF1Rpolymorphisms and abnormal microRNA expression did not correlate withIGF1Rupregulation in adrenocortical tumors.


2009 ◽  
Vol 55 (9) ◽  
pp. 1680-1685 ◽  
Author(s):  
Matthew J Rose-Zerilli ◽  
Sheila J Barton ◽  
A John Henderson ◽  
Seif O Shaheen ◽  
John W Holloway

Abstract Background: Structural variation in the human genome is increasingly recognized as being highly prevalent and having relevance to common human diseases. Array-based comparative genome-hybridization technology can be used to determine copy-number variation (CNV) across entire genomes, and quantitative PCR (qPCR) can be used to validate de novo variation or assays of common CNV in disease-association studies. Analysis of large qPCR data sets can be complicated and time-consuming, however. Methods: We describe qPCR assays for GSTM1 (glutathione S-transferase mu 1) and GSTT1 (glutathione S-transferase theta 1) gene deletions that can genotype up to 192 samples in duplicate 5-μL reaction volumes in <2 h on the ABI Prism 7900HT Sequence Detection System. To streamline data handling and analysis of these CNVs by qPCR, we developed a novel interactive, macro-driven Microsoft Excel® spreadsheet. As proof of principle, we used our software to analyze CNV data for 1478 DNA samples from a family-based cohort. Results: With only 8 ng of DNA template, we assigned CNV genotypes (i.e., 2, 1, or 0 copies) to either 96% (GSTM1) or 91% (GSTT1) of all DNA samples in a single round of PCR amplification. Genotyping accuracy, as ascertained by familial inheritance, was >99.5%, and independent genotype assignments with replicate real-time PCR runs were 100% concordant. Conclusions: The genotyping assay for GSTM1 and GSTT1 gene deletion is suitable for large genetic epidemiologic studies and is a highly effective analysis system that is readily adaptable to analysis of other CNVs. .


2008 ◽  
Vol 375 (1) ◽  
pp. 150-152 ◽  
Author(s):  
Cheng Xin Yi ◽  
Jun Zhang ◽  
Ka Man Chan ◽  
Xiao Kun Liu ◽  
Yan Hong

2006 ◽  
Vol 65 (3) ◽  
pp. 476-487 ◽  
Author(s):  
Miguel A. Providenti ◽  
Jason M. O'Brien ◽  
Robyn J. Ewing ◽  
E. Suzanne Paterson ◽  
Myron L. Smith

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Runa M Grimholt ◽  
Petter Urdal ◽  
Olav Klingenberg ◽  
Armin P Piehler

Abstract Background Alpha-thalassemia is the most common human genetic disease worldwide. Copy number variations in the form of deletions of α-globin genes lead to α-thalassemia while duplications of α-globin genes can cause a severe phenotype in β-thalassemia carriers due to accentuation of globin chain imbalance. It is important to have simple and reliable methods to identify unknown or rare deletions and duplications in cases in which thalassemia is suspected but cannot be confirmed by multiplex gap-PCR. Here we describe a copy number variation assay to detect deletions and duplications in the α-globin gene cluster (HBA-CNV). Results Quantitative real-time PCR was performed using four TaqMan® assays which specifically amplify target sequences representing both the α-globin genes, the –α3.7 deletion and the HS-40 region. The copy number for each target was determined by the 2-ΔΔCq method. To validate our method, we compared the HBA-CNV method with traditional gap-PCR in 108 samples from patients referred to our laboratory for hemoglobinopathy evaluation. To determine the robustness of the four assays, we analyzed samples with and without deletions diluted to obtain different DNA concentrations. The HBA-CNV method identified the correct copy numbers in all 108 samples. All four assays showed the correct copy number within a wide range of DNA concentrations (3.2-100 ng/μL), showing that it is a robust and reliable method. By using the method in routine diagnostics of hemoglobinopathies we have also identified several deletions and duplications that are not detected with conventional gap-PCR. Conclusions HBA-CNV is able to detect all known large deletions and duplications affecting the α-globin genes, providing a flexible and simple workflow with rapid and reliable results.


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