Literature DB >> 17253931

Rapid and efficient FBN1 mutation detection using automated sample preparation and direct sequencing as the primary strategy.

Lena Tjeldhorn1, Svend Rand-Hendriksen, Kristina Gervin, Kristin Brandal, Elin Inderhaug, Odd Geiran, Benedicte Paus.   

Abstract

Mutations in the fibrillin-1 (FBN1) gene cause Marfan syndrome (MFS) and the other type-1 fibrillinopathies. Finding these mutations is a major challenge considering that the FBN1 gene has a coding region of 8,600 base pairs divided into 65 exons. Most of the more than 600 known mutations have been identified using a mutation scanning method prior to sequencing of fragments with a suspected mutation. However, it is not obvious that these screening methods are ideal, considering cost, efficiency, and sensitivity. We have sequenced the entire FBN1 coding sequence and flanking intronic sequences in samples from 105 patients with suspected MFS, taking advantage of robotic devices, which reduce the cost of supplies and the quantity of manual work. In addition, automation avoids many tedious steps, thus reducing the opportunity for human error. Automated assembling of PCR, purification of PCR products, and assembly of sequencing reactions resulted in completion of the FBN1 sequence in half of the time needed for the manual protocol. Mutations were identified in 69 individuals. The mutation detection rate (76%), types, and genetic distribution of mutations resemble the findings in other MFS populations. We conclude that automated sequencing using the robotic systems is well suited as a primary strategy for diagnostic mutation identification in FBN1.

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Year:  2006        PMID: 17253931     DOI: 10.1089/gte.2006.258-264

Source DB:  PubMed          Journal:  Genet Test        ISSN: 1090-6576


  7 in total

1.  Clinical utility gene card for: Marfan syndrome type 1 and related phenotypes [FBN1].

Authors:  Mine Arslan-Kirchner; Eloisa Arbustini; Catherine Boileau; Anne Child; Gwenaelle Collod-Beroud; Anne De Paepe; Jörg Epplen; Guillaume Jondeau; Bart Loeys; Laurence Faivre
Journal:  Eur J Hum Genet       Date:  2010-04-07       Impact factor: 4.246

2.  Prevalence data on all Ghent features in a cross-sectional study of 87 adults with proven Marfan syndrome.

Authors:  Svend Rand-Hendriksen; Rigmor Lundby; Lena Tjeldhorn; Kai Andersen; Jon Offstad; Svein Ove Semb; Hans-Jørgen Smith; Benedicte Paus; Odd Geiran
Journal:  Eur J Hum Genet       Date:  2009-03-18       Impact factor: 4.246

3.  The importance of genotype-phenotype correlation in the clinical management of Marfan syndrome.

Authors:  Víctor Manuel Becerra-Muñoz; Juan José Gómez-Doblas; Carlos Porras-Martín; Miguel Such-Martínez; María Generosa Crespo-Leiro; Roberto Barriales-Villa; Eduardo de Teresa-Galván; Manuel Jiménez-Navarro; Fernando Cabrera-Bueno
Journal:  Orphanet J Rare Dis       Date:  2018-01-22       Impact factor: 4.123

4.  Assembly assay identifies a critical region of human fibrillin-1 required for 10-12 nm diameter microfibril biogenesis.

Authors:  Sacha A Jensen; Ondine Atwa; Penny A Handford
Journal:  PLoS One       Date:  2021-03-18       Impact factor: 3.240

5.  Case Report: A Novel Homozygous Missense Variant of FBN3 Supporting It Is a New Candidate Gene Causative of a Bardet-Biedl Syndrome-Like Phenotype.

Authors:  Maria Luce Genovesi; Barbara Torres; Marina Goldoni; Eliana Salvo; Claudia Cesario; Massimo Majolo; Tommaso Mazza; Carmelo Piscopo; Laura Bernardini
Journal:  Front Genet       Date:  2022-07-15       Impact factor: 4.772

6.  Automated DNA mutation detection using universal conditions direct sequencing: application to ten muscular dystrophy genes.

Authors:  Richard R Bennett; Hal E Schneider; Elicia Estrella; Stephanie Burgess; Andrew S Cheng; Caitlin Barrett; Va Lip; Poh San Lai; Yiping Shen; Bai-Lin Wu; Basil T Darras; Alan H Beggs; Louis M Kunkel
Journal:  BMC Genet       Date:  2009-10-18       Impact factor: 2.797

7.  New population-based exome data question the pathogenicity of some genetic variants previously associated with Marfan syndrome.

Authors:  Ren-Qiang Yang; Javad Jabbari; Xiao-Shu Cheng; Reza Jabbari; Jonas B Nielsen; Bjarke Risgaard; Xu Chen; Ahmad Sajadieh; Stig Haunsø; Jesper Hastrup Svendsen; Morten S Olesen; Jacob Tfelt-Hansen
Journal:  BMC Genet       Date:  2014-06-18       Impact factor: 2.797

  7 in total

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