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Targeted Capture and Massively Parallel Sequencing of Twelve Human Exomes
- Source :
- Nature
- Publication Year :
- 2009
-
Abstract
- Genome-wide association studies suggest that common genetic variants explain only a small fraction of heritable risk for common diseases, raising the question of whether rare variants account for a significant fraction of unexplained heritability1,2. While DNA sequencing costs have fallen dramatically3, they remain far from what is necessary for rare and novel variants to be routinely identified at a genome-wide scale in large cohorts. We have therefore sought to develop second-generation methods for targeted sequencing of all protein-coding regions (`exomes'), to reduce costs while enriching for discovery of highly penetrant variants. Here we report on the targeted capture and massively parallel sequencing of the exomes of twelve humans. These include eight HapMap individuals representing three populations4, and four unrelated individuals with a rare dominantly inherited disorder, Freeman-Sheldon syndrome (FSS)5. We demonstrate the sensitive and specific identification of rare and common variants in over 300 megabases (Mb) of coding sequence. Using FSS as a proof-of-concept, we show that candidate genes for monogenic disorders can be identified by exome sequencing of a small number of unrelated, affected individuals. This strategy may be extendable to diseases with more complex genetics through larger sample sizes and appropriate weighting of nonsynonymous variants by predicted functional impact.
- Subjects :
- Genome, Human
Genetic Variation
Exons
Sequence Analysis, DNA
Syndrome
Polymorphism, Single Nucleotide
Sensitivity and Specificity
Article
Gene Frequency
Haplotypes
INDEL Mutation
Sample Size
Humans
Genetic Predisposition to Disease
Genetic Testing
RNA Splice Sites
Gene Library
Genes, Dominant
Oligonucleotide Array Sequence Analysis
Subjects
Details
- Language :
- English
- ISSN :
- 14764687 and 00280836
- Volume :
- 461
- Issue :
- 7261
- Database :
- OpenAIRE
- Journal :
- Nature
- Accession number :
- edsair.pmid..........4aa0ceebeb88eac8622064d932ba29d2