Discovery of common Asian copy number variants using integrated high-resolution array CGH and massively parallel DNA sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-05

AUTHORS

Hansoo Park, Jong-Il Kim, Young Seok Ju, Omer Gokcumen, Ryan E Mills, Sheehyun Kim, Seungbok Lee, Dongwhan Suh, Dongwan Hong, Hyunseok Peter Kang, Yun Joo Yoo, Jong-Yeon Shin, Hyun-Jin Kim, Maryam Yavartanoo, Young Wha Chang, Jung-Sook Ha, Wilson Chong, Ga-Ram Hwang, Katayoon Darvishi, HyeRan Kim, Song Ju Yang, Kap-Seok Yang, Hyungtae Kim, Matthew E Hurles, Stephen W Scherer, Nigel P Carter, Chris Tyler-Smith, Charles Lee, Jeong-Sun Seo

ABSTRACT

Copy number variants (CNVs) account for the majority of human genomic diversity in terms of base coverage. Here, we have developed and applied a new method to combine high-resolution array comparative genomic hybridization (CGH) data with whole-genome DNA sequencing data to obtain a comprehensive catalog of common CNVs in Asian individuals. The genomes of 30 individuals from three Asian populations (Korean, Chinese and Japanese) were interrogated with an ultra-high-resolution array CGH platform containing 24 million probes. Whole-genome sequencing data from a reference genome (NA10851, with 28.3x coverage) and two Asian genomes (AK1, with 27.8x coverage and AK2, with 32.0x coverage) were used to transform the relative copy number information obtained from array CGH experiments into absolute copy number values. We discovered 5,177 CNVs, of which 3,547 were putative Asian-specific CNVs. These common CNVs in Asian populations will be a useful resource for subsequent genetic studies in these populations, and the new method of calling absolute CNVs will be essential for applying CNV data to personalized medicine. More... »

PAGES

400

References to SciGraph publications

Journal

TITLE

Nature Genetics

ISSUE

5

VOLUME

42

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ng.555

    DOI

    http://dx.doi.org/10.1038/ng.555

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1006886726

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20364138


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