Systematic screening of FBN1 gene unclassified missense variants for splice abnormalities

Robinson DO, Lin F, Lyon M, Raponi M, Cross E, White HE, Cox H, Clayton‐Smith J, Baralle D. Systematic screening of FBN1 gene unclassified missense variants for splice abnormalities. Defects at the level of pre‐mRNA splicing are a common source of genetic mutation but such mutations are not always e...

Full description

Saved in:
Bibliographic Details
Published in:Clinical genetics Vol. 82; no. 3; pp. 223 - 231
Main Authors: Robinson, DO, Lin, F, Lyon, M, Raponi, M, Cross, E, White, HE, Cox, H, Clayton-Smith, J, Baralle, D
Format: Journal Article
Language:English
Published: Oxford, UK Blackwell Publishing Ltd 01-09-2012
Wiley-Blackwell
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Robinson DO, Lin F, Lyon M, Raponi M, Cross E, White HE, Cox H, Clayton‐Smith J, Baralle D. Systematic screening of FBN1 gene unclassified missense variants for splice abnormalities. Defects at the level of pre‐mRNA splicing are a common source of genetic mutation but such mutations are not always easy to identify from DNA sequence data alone. Clinical practice has only recently begun to incorporate analysis for this type of abnormality. Some base changes at the DNA level currently viewed as unclassified variants or missense mutations may influence RNA splicing. To address this problem for fibrillin 1 (FBN1) gene missense mutations we have carried out RNA analysis and in silico analysis with splice site prediction programs on 40 cases with 36 different mutations. Direct analysis of RNA from blood was performed by cDNA preparation, PCR amplification of specific FBN1 fragments, gel electrophoresis and sequencing of the PCR products. Of the 36 missense base changes, direct RNA analysis identified 2 which caused an abnormality of splicing. In silico analysis using five splice site prediction programs did not always accurately predict the splicing seen by direct RNA analysis. In conclusion, some apparent missense mutations have an effect on splicing which can be identified by direct RNA analysis, however, in silico analysis of splice sites is not always accurate, should be carried out with more than one prediction program and results should be used with caution.
Bibliography:istex:487BC7D0BE6169F26DCBB5F1287A1D08C8E3A064
ArticleID:CGE1781
ark:/67375/WNG-VDJ1QHZH-M
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:0009-9163
1399-0004
DOI:10.1111/j.1399-0004.2011.01781.x