Personalized copy number and segmental duplication maps using next-generation sequencing

• Published in: Nature genetics Vol. 41; no. 10; pp. 1061 - 1067
• Main Authors: Alkan, Can, Kidd, Jeffrey M, Marques-Bonet, Tomas, Aksay, Gozde, Antonacci, Francesca, Hormozdiari, Fereydoun, Kitzman, Jacob O, Baker, Carl, Malig, Maika, Mutlu, Onur, Sahinalp, S Cenk, Gibbs, Richard A, Eichler, Evan E
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.10.2009; Nature Publishing Group
• Subjects: Agriculture; Algorithms; Animal Genetics and Genomics; Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; Cancer Research; Chromosome mapping; Chromosome Mapping - methods; Color blindness; Crohn's disease; Data analysis; DNA - analysis; DNA - genetics; DNA sequencing; Fundamental and applied biological sciences. Psychology; Gene Dosage; Gene Duplication; Gene Function; Genes; Genetic algorithms; Genetic variation; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Genome, Human; Genomic Library; Genomics; Human Genetics; Humans; Life sciences; Methods; Nucleotide sequencing; Phenotypic variations; Polymorphism, Genetic; Sequence Analysis, DNA - methods; Studies; United States; Duplication; Copy number; Sequencing
• ISSN: 1061-4036; 1546-1718; 1546-1718
• DOI: 10.1038/ng.437

Evan Eichler and colleagues have developed an algorithm called mrFAST to map short, next-generation sequence reads across the genome that allows for the accurate prediction of copy-number variation. Despite their importance in gene innovation and phenotypic variation, duplicated regions have remained largely intractable owing to difficulties in accurately resolving their structure, copy number and sequence content. We present an algorithm (mrFAST) to comprehensively map next-generation sequence reads, which allows for the prediction of absolute copy-number variation of duplicated segments and genes. We examine three human genomes and experimentally validate genome-wide copy number differences. We estimate that, on average, 73–87 genes vary in copy number between any two individuals and find that these genic differences overwhelmingly correspond to segmental duplications (odds ratio = 135; P < 2.2 × 10 −16 ). Our method can distinguish between different copies of highly identical genes, providing a more accurate assessment of gene content and insight into functional constraint without the limitations of array-based technology.