Literature DB >> 22753364

Validation of a quantitative PCR-high-resolution melting protocol for simultaneous screening of COL1A1 and COL1A2 point mutations and large rearrangements: application for diagnosis of osteogenesis imperfecta.

Filomena Valentina Gentile1, Monia Zuntini, Alessandro Parra, Luca Battistelli, Martina Pandolfi, Gerard Pals, Luca Sangiorgi.   

Abstract

Osteogenesis imperfecta (OI) is a connective tissue disorder mostly characterized by autosomal dominant inheritance. Over 1,100 causal mutations have been identified scattered along all exons of genes encoding type I collagen precursors, COL1A1 and COL1A2. Because of the absence of mutational hotspots, Sanger sequencing is considered the gold standard for molecular analysis even if the workload is very laborious and expensive. To overcome this issue, different prescreening methods have been proposed, including DHPLC and biochemical studies on cultured dermal fibroblasts; however, both approaches present different drawbacks. Moreover, in case of patients who screen negative for point mutations, an additional screening step for complex rearrangements is required; the added causative variants expected from this approach are about 1-2%. The aim of this study was to optimize and validate a new protocol that combines quantitative PCR (qPCR) and high-resolution melting (HRM) curve analysis to reduce time and costs for molecular diagnosis. Results of qPCR-HRM screening on 57 OI patients, validated by DHPLC-direct sequencing and multiplex ligation-dependent probe amplification (MLPA), indicate that all alterations identified with the mentioned methodologies are successfully detected by qPCR-HRM. Moreover, HRM was able to discriminate complex genotypes and homozygous variants. Finally, qPCR-HRM outperformed direct sequencing and DHPLC-MLPA in terms of rapidity and costs.
© 2012 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22753364     DOI: 10.1002/humu.22146

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  6 in total

1.  Genetic analysis of osteogenesis imperfecta in the Palestinian population: molecular screening of 49 affected families.

Authors:  Osama Essawi; Sofie Symoens; Maha Fannana; Mohammad Darwish; Mohammad Farraj; Andy Willaert; Tamer Essawi; Bert Callewaert; Anne De Paepe; Fransiska Malfait; Paul J Coucke
Journal:  Mol Genet Genomic Med       Date:  2017-11-18       Impact factor: 2.183

2.  Mutation spectrum of COL1A1/COL1A2 screening by high-resolution melting analysis of Chinese patients with osteogenesis imperfecta.

Authors:  Mingyan Ju; Xue Bai; Tianke Zhang; Yunshou Lin; Li Yang; Huaiyu Zhou; Xiaoli Chang; Shizhen Guan; Xiuzhi Ren; Keqiu Li; Yi Wang; Guang Li
Journal:  J Bone Miner Metab       Date:  2019-08-14       Impact factor: 2.626

3.  Genotype-phenotype correlation study in 364 osteogenesis imperfecta Italian patients.

Authors:  Margherita Maioli; Maria Gnoli; Manila Boarini; Morena Tremosini; Anna Zambrano; Elena Pedrini; Marina Mordenti; Serena Corsini; Patrizia D'Eufemia; Paolo Versacci; Mauro Celli; Luca Sangiorgi
Journal:  Eur J Hum Genet       Date:  2019-03-18       Impact factor: 4.246

4.  Real-World Data and Budget Impact Analysis (BIA): Evaluation of a Targeted Next-Generation Sequencing Diagnostic Approach in Two Orthopedic Rare Diseases.

Authors:  Elena Pedrini; Antonella Negro; Eugenio Di Brino; Valentina Pecoraro; Camilla Sculco; Elisabetta Abelli; Maria Gnoli; Armando Magrelli; Luca Sangiorgi; Americo Cicchetti
Journal:  Front Pharmacol       Date:  2022-06-06       Impact factor: 5.988

5.  Identification of gene mutation in patients with osteogenesis imperfect using high resolution melting analysis.

Authors:  Jianhai Wang; Xiuzhi Ren; Xue Bai; Tianke Zhang; Yi Wang; Keqiu Li; Guang Li
Journal:  Sci Rep       Date:  2015-08-26       Impact factor: 4.379

6.  Osteogenesis Imperfecta: Search for Mutations in Patients from the Republic of Bashkortostan (Russia).

Authors:  Dina Nadyrshina; Aliya Zaripova; Anton Tyurin; Ildar Minniakhmetov; Ekaterina Zakharova; Rita Khusainova
Journal:  Genes (Basel)       Date:  2022-01-10       Impact factor: 4.096

  6 in total

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