Copy-Number Variation Contributes to the Mutational Load of Bardet-Biedl Syndrome.

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作者:Lindstrand Anna, Frangakis Stephan, Carvalho Claudia M B, Richardson Ellen B, McFadden Kelsey A, Willer Jason R, Pehlivan Davut, Liu Pengfei, Pediaditakis Igor L, Sabo Aniko, Lewis Richard Alan, Banin Eyal, Lupski James R, Davis Erica E, Katsanis Nicholas
Bardet-Biedl syndrome (BBS) is a defining ciliopathy, notable for extensive allelic and genetic heterogeneity, almost all of which has been identified through sequencing. Recent data have suggested that copy-number variants (CNVs) also contribute to BBS. We used a custom oligonucleotide array comparative genomic hybridization (aCGH) covering 20 genes that encode intraflagellar transport (IFT) components and 74 ciliopathy loci to screen 92 unrelated individuals with BBS, irrespective of their known mutational burden. We identified 17 individuals with exon-disruptive CNVs (18.5%), including 13 different deletions in eight BBS genes (BBS1, BBS2, ARL6/BBS3, BBS4, BBS5, BBS7, BBS9, and NPHP1) and a deletion and a duplication in other ciliopathy-associated genes (ALMS1 and NPHP4, respectively). By contrast, we found a single heterozygous exon-disruptive event in a BBS-associated gene (BBS9) in 229 control subjects. Superimposing these data with resequencing revealed CNVs to (1) be sufficient to cause disease, (2) Mendelize heterozygous deleterious alleles, and (3) contribute oligogenic alleles by combining point mutations and exonic CNVs in multiple genes. Finally, we report a deletion and a splice site mutation in IFT74, inherited under a recessive paradigm, defining a candidate BBS locus. Our data suggest that CNVs contribute pathogenic alleles to a substantial fraction of BBS-affected individuals and highlight how either deletions or point mutations in discrete splice isoforms can induce hypomorphic mutations in genes otherwise intolerant to deleterious variation. Our data also suggest that CNV analyses and resequencing studies unbiased for previous mutational burden is necessary to delineate the complexity of disease architecture.

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