Multiple peaks in the derivative melting curve of chromatin from animals of varying age

1974 ◽  
Vol 3 ◽  
pp. 37-49 ◽  
Author(s):  
D.I. Kurtz ◽  
A.P. Russell ◽  
F.M. Sinex
Keyword(s):  
Melting Curve ◽  
Multiple Peaks

scholarly journals Human Platelet Antigen Genotyping and Expression of CD109 (Human Platelet Antigen 15) mRNA in Various Human Cell Types

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Sang Mee Hwang ◽  
Mi Jung Kim ◽  
Ho Eun Chang ◽  
Yun Ji Hong ◽  
Taek Soo Kim ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Human Platelet ◽  
Human Fibroblasts ◽  
Leukemia Cell ◽  
Embryonic Stem ◽  
Melting Curve ◽  
Leukemia Cell Line ◽  
Melting Curve Analysis ◽  
Platelet Antigen ◽  
Human Platelet Antigen

CD109 gene encodes a glycosylphosphatidylinositol-linked glycoprotein found in a subset of platelets and endothelial cell, and human platelet antigen (HPA) 15 is found on CD109. We evaluated the HPA genotype and/or the CD109 mRNA expression on two peripheral blood stem cells (PBSC), two peripheral bloods (PB), 12 granulocyte products, natural killer (NK)-92, B-lymphocyte (CO88BV59-1), K-562 leukemia cell line, human embryonic stem cell (hESC), and human fibroblasts (HF). HPA genotyping was performed by SNaPshot assay and CD109 mRNA expression was evaluated by real-time PCR with SYBR green and melting curve analysis. Genotype HPA-15a/-15a was found in PBSC#1 and two granulocyte products, and HPA-15a/-15b was found in PBSC#2, eight granulocyte products, NK-92, K-562, hESC, and HF, and HPA-15b/-15b was found in two granulocyte products. CD109 mRNA expression was highly increased in HF and increased in CD34+ and CD34− PBSCs and some granulocyte products, compared to the PB. However, the increase of expression level varied among the PBSC and granulocyte products. The CD109 mRNA expression of NK-92, K-562, hESC, and CO 88BV59-1 was not detected. HPA genotype was evaluated in various cells and the expression of CD109, which contains HPA 15, was different among cell lines and high in HF and PBSCs.

scholarly journals Rapid genotypic detection ofBacillus anthracisand theBacillus cereusgroup by multiplex real-time PCR melting curve analysis

2005 ◽  
Vol 43 (2) ◽  
pp. 301-310 ◽  
Author(s):  
Kijeong Kim ◽  
Juwon Seo ◽  
Katherine Wheeler ◽  
Chulmin Park ◽  
Daewhan Kim ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Melting Curve ◽  
Curve Analysis ◽  
Melting Curve Analysis

scholarly journals On multiple peaks and moderate deviations for the supremum of a Gaussian field

2015 ◽  
Vol 43 (6) ◽  
pp. 3468-3493 ◽  
Author(s):  
Jian Ding ◽  
Ronen Eldan ◽  
Alex Zhai
Keyword(s):  
Moderate Deviations ◽  
Gaussian Field ◽  
Multiple Peaks

scholarly journals Genotyping of a tri-allelic polymorphism by a novel melting curve assay in MTHFD1L: an association study of nonsyndromic Cleft in Ireland

2012 ◽  
Vol 13 (1) ◽  
Author(s):  
Stefano Minguzzi ◽  
Anne M Molloy ◽  
Kirke Peadar ◽  
James Mills ◽  
John M Scott ◽  
...  
Keyword(s):  
Association Study ◽  
Melting Curve ◽  
Allelic Polymorphism

scholarly journals Diagnosis of α-1-Antitrypsin Deficiency: An Algorithm of Quantification, Genotyping, and Phenotyping

2006 ◽  
Vol 52 (12) ◽  
pp. 2236-2242 ◽  
Author(s):  
Melissa R Snyder ◽  
Jerry A Katzmann ◽  
Malinda L Butz ◽  
Ping Yang ◽  
D Brian Dawson ◽  
...  
Keyword(s):  
Laboratory Testing ◽  
Null Allele ◽  
Melting Curve ◽  
Curve Analysis ◽  
Laboratory Evaluation ◽  
Melting Curve Analysis ◽  
Genotype Assay ◽  
Antitrypsin Deficiency ◽  
Phenotype Analysis ◽  
A1at Deficiency

Abstract Background: Laboratory testing in suspected α-1-antitrypsin (A1AT) deficiency involves analysis of A1AT concentrations and identification of specific alleles by genotyping or phenotyping. The purpose of this study was to define and evaluate a strategy that provides reliable laboratory evaluation of A1AT deficiency. Methods: Samples from 512 individuals referred for A1AT phenotype analysis were analyzed by quantification, phenotype, and genotype. A1AT concentrations were measured by nephelometry. Phenotype analysis was performed by isoelectric focusing electrophoresis. The genotype assay detected the S and Z deficiency alleles by a melting curve analysis. Results: Of the 512 samples analyzed, 2% of the phenotype and genotype results were discordant. Among these 10 discordant results, 7 were attributed to phenotyping errors. On the basis of these data we formulated an algorithm, according to which we analyzed samples by genotyping and quantification assays, with a reflex to phenotyping when the genotype and quantification results were not concordant. Retrospective analyses demonstrated that 4% of samples submitted for genotype and quantitative analysis were reflexed to phenotyping. Of the reflexed samples, phenotyping confirmed the genotype result in 85% of cases. In the remaining 15%, phenotyping provided further information, including identifying rare deficiency alleles and suggesting the presence of a null allele, and allowed for a more definitive interpretation of the genotype result. Conclusions: The combination of genotyping and quantification, with a reflex to phenotyping, is the optimal strategy for the laboratory evaluation of A1AT deficiency.

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