Literature DB >> 26892340

Scanning for α-Hemoglobin Variants by High-Resolution Melting Analysis.

Walaiporn Yimniam1, Sumalee Jindadamrongwech2.   

Abstract

BACKGROUND: Definitive detection of hemoglobin (Hb) variants requires DNA sequencing. High-resolution melting (HRM) analysis of polymerase chain reaction (PCR) amplicons was applied to detect and discriminate among uncommon α-Hb variants found in Thailand.
METHODS: Uncommon suspected α-Hb variants observed in Hb typing were identified by sequencing of DNA from whole blood samples. Three pairs of PCR primers covering the mutation regions in the three α-globin exons then were used for PCR coupled with difference in HRM analysis to subtract out the concomitant melting profile of the normal allele in the heterozygous state.
RESULTS: DNA sequencing identified six heterozygous α-Hb variants, namely, Hb G-Waimanalo (HBA2: exon 2, codon 64 G>A), Hb J-Buda (HBA1: exon 2, codon 61 G>T), Hb Kurosaki (HBA2: exon 1; codon 7 A>G), Hb O-Indonesia (HBA1: exon 3 codon 116 G>A), Hb Q-India (HBA1:exon 2, codon 64 G>C), and Hb Q-Thailand (HBA1: exon 2 codon 74 G>C). Difference HRM analysis showed one temperature melting profile using exon 1 primer pair, four different profiles with exon 2 primer pair, and one profile with exon 3 primer pair.
CONCLUSIONS: PCR-HRM analysis was effective in detecting and discriminating among single point mutations causing six uncommon α-Hb variants in heterozygous individuals. The method can be applied for routine screening due to its simplicity and relatively low cost.
© 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  DNA sequencing; hemoglobin typing; hemoglobin variant; high-resolution melting (HRM) analysis; quantitative PCR

Mesh:

Substances:

Year:  2016        PMID: 26892340      PMCID: PMC6807199          DOI: 10.1002/jcla.21914

Source DB:  PubMed          Journal:  J Clin Lab Anal        ISSN: 0887-8013            Impact factor:   2.352


  32 in total

1.  Identification of Hb J-Buda [alpha61(E10)Lys-->Asn] in a Thai female.

Authors:  D Itchayanan; J Svasti; C Srisomsap; P Winichagoon; S Fucharoen
Journal:  Hemoglobin       Date:  1999-05       Impact factor: 0.849

Review 2.  Current and emerging techniques for diagnostic mutation detection: an overview of methods for mutation detection.

Authors:  Claire F Taylor; Graham R Taylor
Journal:  Methods Mol Med       Date:  2004

3.  High-resolution melting analysis of the three common nondeletional α-thalassemia mutations in the Chinese population: Hbs Constant Spring, Quong Sze and Westmead.

Authors:  Ru Li; Can Liao; Dongzhi Li; Jian Li
Journal:  Hemoglobin       Date:  2010       Impact factor: 0.849

4.  Hb Q India: is it always benign?

Authors:  I Panigrahi; J Bajaj; T Chatterjee; R Saxena; M Mahapatra; H P Pati
Journal:  Am J Hematol       Date:  2005-03       Impact factor: 10.047

5.  Rapid identification of HBB gene mutations by high-resolution melting analysis.

Authors:  Hung-Chang Shih; Tze-Kiong Er; Tien-Jye Chang; Ya-Sian Chang; Ta-Chih Liu; Jan-Gowth Chang
Journal:  Clin Biochem       Date:  2009-07-23       Impact factor: 3.281

6.  Simple non-radioactive method for detecting haemoglobin Constant Spring gene.

Authors:  S Fucharoen; G Fucharoen; Y Fukumaki
Journal:  Lancet       Date:  1990-06-23       Impact factor: 79.321

7.  Hb Kurosaki [alpha 7(A5)Lys-->Glu]: a new alpha chain variant found in a Japanese woman.

Authors:  T Harano; K Harano; K Imai; T Murakami; H Matsubara
Journal:  Hemoglobin       Date:  1995 May-Jul       Impact factor: 0.849

Review 8.  Haemoglobinopathies in southeast Asia.

Authors:  Suthat Fucharoen; Pranee Winichagoon
Journal:  Indian J Med Res       Date:  2011-10       Impact factor: 2.375

9.  Is high resolution melting analysis (HRMA) accurate for detection of human disease-associated mutations? A meta analysis.

Authors:  Bing-Sheng Li; Xin-Ying Wang; Feng-Li Ma; Bo Jiang; Xiao-Xiao Song; An-Gao Xu
Journal:  PLoS One       Date:  2011-12-14       Impact factor: 3.240

10.  Hemoglobinopathy: molecular epidemiological characteristics and health effects on Hakka people in the Meizhou region, southern China.

Authors:  Min Lin; Ying-Fang Wen; Jiao-Ren Wu; Qian Wang; Lei Zheng; Gui-Rong Liu; Yue Huang; Hui Yang; Fen Lin; Xiao-Fen Zhan; Chun-Ping Lin; Hui-Tian Yang; Qiu-Qing Weng; Fen-Ting Huang; Yuan Wang; Mei-Qiong Yao; Hui-Zhou Chen; Di-Hong Wu; Jing-Bo Zeng; Ri-Xin Zeng; Hua Yang; Gui-Cai Li; Min Lu; Juan-Juan Zhu; Long-Xu Xie; Jun-Li Wang; Li-Ye Yang
Journal:  PLoS One       Date:  2013-02-01       Impact factor: 3.240

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