Journal of Bone and Mineral Research · 2011 · 62 citations · 31 references
Life SciencesGeneticsMolecular GeneticsGenetic EpidemiologyGenomicsMedical GeneticsRare Disease GenomicsRare Variant Association StudiesVariant AnalysisVariant InterpretationExome SequencingExon-intron BoundariesGenetic Risk VariantsGenome-wide Linkage AnalysisLod Score AnalysisParallel SequencingRare Genetic VariantsReceptor Gene Variants
Massively parallel sequencing of target regions, exomes, and complete genomes has begun to increase the opportunities for identifying genetic variants underlying rare and common diseases dramatically. Here we applied exome resequencing to primary failure of tooth eruption (PFE) to identify the genetic causality of the disease. Two Japanese families having PFE were recruited and examined by genome-wide linkage study and subsequently exome analyses. Linkage analyses of these two families comprising eight affected individuals and two unaffected individuals revealed linkage signals at 10 loci with a maximum LOD score of 1.5. Four affected individuals in one family were pooled and further processed for exome analysis, followed by massive parallel sequencing. After three-step filtering including annotation and functional expectation, three variants were found to be candidates for PFE. Among the three variants, only a novel variant of parathyroid hormone 1 receptor gene (PTH1R), R383Q, was cosegregated in the first PFE family. Accordingly, we screened the gene for variants at all coding exons and the respective intron-exon boundaries in the second family and two sporadic individuals with PFE. We also identified a novel missense variant, P119L, cosegregating in the second family and missense variants P132L and R147C in the sporadic cases. These variants all were in the highly conserved region across zebrafish to chimpanzee and not observed in 192 unrelated controls, supporting the pathogenicity of the variants. The combination of linkage and exome analyses employed in this study provides a powerful strategy for identifying genes responsible for Mendelian disorders.
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