Literature DB >> 21594782

Quantification of CFTR transcripts.

Anabela S Ramalho1, Luka A Clarke, Margarida D Amaral.   

Abstract

Quantification and analysis of CFTR transcripts is of crucial importance not only for cystic fibrosis (CF) diagnosis and prognosis, but also in evaluating the efficiency of various therapeutic approaches to CF, including gene therapy. Reverse transcription (RT) followed by quantitative polymerase chain reaction (qPCR) is at present the most sensitive method for transcript abundance measurement. Classical RNA-based methods require significant expression levels in target samples for appropriate analysis, thus PCR-based methods have evolved towards reliable quantification. In this chapter we describe and discuss several protocols for the quantitative analysis of CFTR transcripts, including those variants that result from alternative splicing.

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Year:  2011        PMID: 21594782     DOI: 10.1007/978-1-61779-117-8_9

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Assessing the residual CFTR gene expression in human nasal epithelium cells bearing CFTR splicing mutations causing cystic fibrosis.

Authors:  Laia Masvidal; Susana Igreja; Maria D Ramos; Antoni Alvarez; Javier de Gracia; Anabela Ramalho; Margarida D Amaral; Sara Larriba; Teresa Casals
Journal:  Eur J Hum Genet       Date:  2013-10-16       Impact factor: 4.246

2.  Quantitative analysis of copy number variants based on real-time LightCycler PCR.

Authors:  Lijiang Ma; Wendy K Chung
Journal:  Curr Protoc Hum Genet       Date:  2014-01-21

3.  Defining the disease liability of variants in the cystic fibrosis transmembrane conductance regulator gene.

Authors:  Patrick R Sosnay; Karen R Siklosi; Fredrick Van Goor; Kyle Kaniecki; Haihui Yu; Neeraj Sharma; Anabela S Ramalho; Margarida D Amaral; Ruslan Dorfman; Julian Zielenski; David L Masica; Rachel Karchin; Linda Millen; Philip J Thomas; George P Patrinos; Mary Corey; Michelle H Lewis; Johanna M Rommens; Carlo Castellani; Christopher M Penland; Garry R Cutting
Journal:  Nat Genet       Date:  2013-08-25       Impact factor: 38.330

  3 in total

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