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Intra- and extragenic marker haplotypes of CFTR mutations in cystic fibrosis families
In order to facilitate the screening for the less common mutations in the cystic fibrosis (CF) gene viz., the CF transmembrane conductance regulator gene (CFTR), marker haplotypes were determined for German non-CF (N) and CF chromosomes by polymerase chain reaction analysis of four polymorphisms ups...
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Published in: | Human genetics 1992-02, Vol.88 (4), p.417-425 |
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Main Authors: | , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In order to facilitate the screening for the less common mutations in the cystic fibrosis (CF) gene viz., the CF transmembrane conductance regulator gene (CFTR), marker haplotypes were determined for German non-CF (N) and CF chromosomes by polymerase chain reaction analysis of four polymorphisms upstream of the CF gene (XV-2c, KM.19, MP6-D9, J44) and six intragenic polymorphisms (GATT, TUB9, M470V, T854T, TUB18, TUB20) that span the CFTR gene from exon 6 through exon 21. Novel informative sequence variants of CFTR were detected in front of exons 10 (1525-61 A or G), 19 (3601-65 C or A), and 21 (4006-200 A or G). The CF locus exhibits strong long-range marker-marker linkage disequilibrium with breakpoints of recombination between XV-2c and KM.19, and between exons 10 and 19 of CFTR. Marker alleles of GATT-TUB9 and TUB18-TUB20 were found to be in absolute linkage disequilibrium. Four major haplotypes encompass more than 90% of German N and CF chromosomes. Fifteen CFTR mutations detected on 421 out of 500 CF chromosomes were each identified on one of these four predominant 7-marker haplotypes. Whereas all analysed delta F508 chromosomes carried the same KM.19-D9-J44-GATT-TUB9-M470V-T854T haplotype, another frequent mutation in Germany, R553X, was identified on two different major haplotypes. Hence, a priori haplotyping cannot exclude a particular CF mutation, but in combination with population genetic data, enables mutations to be ranked by decreasing probability. |
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ISSN: | 0340-6717 1432-1203 |
DOI: | 10.1007/BF00215676 |