- Main
Genome-Wide Structural Variation Detection by Genome Mapping on Nanochannel Arrays
- Mak, Angel CY;
- Lai, Yvonne YY;
- Lam, Ernest T;
- Kwok, Tsz-Piu;
- Leung, Alden KY;
- Poon, Annie;
- Mostovoy, Yulia;
- Hastie, Alex R;
- Stedman, William;
- Anantharaman, Thomas;
- Andrews, Warren;
- Zhou, Xiang;
- Pang, Andy WC;
- Dai, Heng;
- Chu, Catherine;
- Lin, Chin;
- Wu, Jacob JK;
- Li, Catherine ML;
- Li, Jing-Woei;
- Yim, Aldrin KY;
- Chan, Saki;
- Sibert, Justin;
- Džakula, Željko;
- Cao, Han;
- Yiu, Siu-Ming;
- Chan, Ting-Fung;
- Yip, Kevin Y;
- Xiao, Ming;
- Kwok, Pui-Yan
- et al.
Published Web Location
https://doi.org/10.1534/genetics.115.183483Abstract
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 variations 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.
Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
Enter the password to open this PDF file:
-
-
-
-
-
-
-
-
-
-
-
-
-
-