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Global analysis of disease-related DNA sequence variation in 10 healthy individuals: implications for whole genome-based clinical diagnostics.

http://www.ncbi.nlm.nih.gov/pubmed/21325948

BACKGROUND: Understanding how sequence variants within healthy genomes are distributed with respect to ethnicity and disease-implicated genes is an essential first step toward establishing baselines for personalized genomic medicine. METHODS: In this study, we present an analysis of 10 genomes from healthy individuals of various ethnicities, produced using six different sequencing technologies. In total, these genomes contain more than 34 million single-nucleotide variants. RESULTS: We have analyzed these variants from a clinical perspective, assaying the influence of sequencing technology and ethnicity on prognosis. We have also examined the utility of OMIM and the disease-gene literature for determining the impact of rare, personal variants on an individual's health. CONCLUSIONS: Our analyses demonstrate that clinical prognoses are complicated by sequencing platform-specific errors and ethnicity. We show that disease-causing alleles are globally distributed along ethnic lines, with alleles known to be disease causing in Eurasians being significantly more likely to be homozygous in Africans.

Pubmed ID: 21325948 RIS Download

Mesh terms: Alleles | Computational Biology | Continental Population Groups | Databases, Genetic | Female | Genetics, Medical | Genome | Genome-Wide Association Study | Humans | Individualized Medicine | Male | Molecular Sequence Annotation | Mutation | Polymorphism, Single Nucleotide | Sequence Analysis, DNA

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