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bioRxivGenomicsPreprint

Rapid Automated Large Structural Variation Detection in a Diploid Genome by NanoChannel Based Next-Generation Mapping

Alex R. HastieiD, Ernest T. Lam, Andy Wing Chun PangiD, Xinyue ZhangiD, Warren Andrews, Joyce LeeiD, Tiffany Y LiangiD, Jian WangiD, Xiang ZhouiD, Zhanyang ZhuiD, Thomas Anantharaman, Željko Džakula, Sven Bocklandt, Urvashi SurtiiD, Michael Saghbini, Michael D. Austin, Mark Borodkin, R. Erik Holmlin, Han CaoiD

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Abstract

The human genome is diploid with one haploid genome inherited from the maternal and one from the paternal lineage. Within each haploid genome, large structural variants such as deletions, duplications, inversions, and translocations are extensively present and many are known to affect biological functions and cause disease. The ultimate goal is to resolve these large complex structural variants (SVs) and place them in the correct haploid genome with correct location, orientation, and copy number. Current methods such as karyotyping, chromosomal microarray (CMA), PCR-based tests, and next-generation sequencing fail to reach this goal either due to limited resolution, low throughput, or short read length.\n\nBionano Genomics next-generation mapping (NGM) offers a high-throughput, genome-wide method able to detect SVs of one kilobase pairs (kbp) and up. By imaging extremely long genomic molecules of up to megabases in size, the structure and copy number of complex regions of the g ...

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29

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Le Li, Alden King-Yung Leung, Tsz-Piu Kwok+18 more·Genome biology·Dec 1, 2017· 29 citations