Title |
Genome-Wide Structural Variation Detection by Genome Mapping on Nanochannel Arrays
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Published in |
Genetics, October 2015
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DOI | 10.1534/genetics.115.183483 |
Pubmed ID | |
Authors |
Angel C. Y. Mak, Yvonne Y. Y. Lai, Ernest T. Lam, Tsz-Piu Kwok, Alden K. Y. Leung, Annie Poon, Yulia Mostovoy, Alex R. Hastie, William Stedman, Thomas Anantharaman, Warren Andrews, Xiang Zhou, Andy W. C. Pang, Heng Dai, Catherine Chu, Chin Lin, Jacob J. K. Wu, Catherine M. L. Li, Jing-Woei Li, Aldrin K. Y. Yim, Saki Chan, Justin Sibert, Željko Džakula, Han Cao, Siu-Ming Yiu, Ting-Fung Chan, Kevin Y. Yip, Ming Xiao, Pui-Yan Kwok |
Abstract |
Comprehensive whole genome structural variation detection is challenging with current approaches. With diploid cells as DNA source and the presence of numerous repetitive elements, short read DNA sequencing cannot be used to detect structural variation efficiently. In this report, we show that genome mapping with long, fluorescently labeled DNA molecules imaged on nanochannel arrays can be used for whole genome structural variation detection without sequencing. While whole genome haplotyping is not achieved, local phasing (across >150 kb regions) is routine, as molecules from the parental chromosomes are examined separately. In one experiment, we generated genome maps from a trio from the 1000 Genomes Project, compared the maps against that derived from the reference human genome, and identified structural variation that are >5 kb in size. We find that these individuals have many more structural variants than those published, including some with the potential of disrupting gene function or regulation. |
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Geographical breakdown
Country | Count | As % |
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United States | 2 | 18% |
Puerto Rico | 1 | 9% |
Egypt | 1 | 9% |
Australia | 1 | 9% |
Germany | 1 | 9% |
Unknown | 5 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 5 | 45% |
Members of the public | 3 | 27% |
Science communicators (journalists, bloggers, editors) | 2 | 18% |
Unknown | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 2 | <1% |
Netherlands | 1 | <1% |
Norway | 1 | <1% |
United Kingdom | 1 | <1% |
United States | 1 | <1% |
Unknown | 219 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 49 | 22% |
Researcher | 36 | 16% |
Student > Master | 24 | 11% |
Student > Bachelor | 15 | 7% |
Student > Doctoral Student | 10 | 4% |
Other | 38 | 17% |
Unknown | 53 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 72 | 32% |
Biochemistry, Genetics and Molecular Biology | 48 | 21% |
Computer Science | 12 | 5% |
Medicine and Dentistry | 8 | 4% |
Engineering | 8 | 4% |
Other | 21 | 9% |
Unknown | 56 | 25% |