Familial adenomatous polyposis: aberrant splicing due to missense or silent mutations in the APC gene
Stefan Aretz1, Siegfried Uhlhaas, Yuli Sun
1Institute of Human Genetics, University Hospital of Bonn, Bonn, Germany. Stefan.Aretz@ukb.uni-bonn.de
Abstract:
Familial adenomatous polyposis (FAP) is caused by germline mutations in the tumor suppressor gene APC. To date, the relevance of rare exonic single-base substitutions at nucleotide positions close to splice sites that are predicted to result in missense or silent (SNP) variants or substitutions in introns at splice-site positions that are not highly conserved has not been systematically examined in FAP patients. In 34 index patients, we identified 26 different heterozygous single-base substitutions at or close to the splice sites. We characterized five exonic mutations in exon 4 (c.423G>T), exon 14 (c.1956C>T, c.1957A>G, and c.1957A>C), and exon 15 (c.1959G>A) by transcript analysis and by splice-prediction programs (BDGP, SpliceSiteFinder, and ESEfinder). The splicing patterns of these variants were compared to those of 16 different substitutions at highly or less-conserved intronic splice-site positions, and to normal controls. In addition, we analyzed cosegregation of the variants with affected family members and examined the genotype-phenotype correlation. We could demonstrate that the four unclear variants in exon 4 and 14 that are predicted to result in missense or silent mutations in fact lead to complete exon skipping due to aberrant splicing; one possible explanation for this observed effect might be the disruption of exonic splicing enhancer (ESE) motifs. In contrast, the substitution at the first position of exon 15 seems to actually be a silent variant. We present the first systematic evaluation of different single-base substitutions in APC at or close to splice sites at transcript level. We show that the consequence of exonic mutations cannot be evaluated only by the predicted change in amino acid sequence but rather by the change at DNA level. The functional analysis of variants with unknown pathogenic effect plays an important role in increasing the mutation detection rate and achieving validation of predictive testing.
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