Haplotyping germline and cancer genomes with high-throughput linked-read sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-03

AUTHORS

Grace X Y Zheng, Billy T Lau, Michael Schnall-Levin, Mirna Jarosz, John M Bell, Christopher M Hindson, Sofia Kyriazopoulou-Panagiotopoulou, Donald A Masquelier, Landon Merrill, Jessica M Terry, Patrice A Mudivarti, Paul W Wyatt, Rajiv Bharadwaj, Anthony J Makarewicz, Yuan Li, Phillip Belgrader, Andrew D Price, Adam J Lowe, Patrick Marks, Gerard M Vurens, Paul Hardenbol, Luz Montesclaros, Melissa Luo, Lawrence Greenfield, Alexander Wong, David E Birch, Steven W Short, Keith P Bjornson, Pranav Patel, Erik S Hopmans, Christina Wood, Sukhvinder Kaur, Glenn K Lockwood, David Stafford, Joshua P Delaney, Indira Wu, Heather S Ordonez, Susan M Grimes, Stephanie Greer, Josephine Y Lee, Kamila Belhocine, Kristina M Giorda, William H Heaton, Geoffrey P McDermott, Zachary W Bent, Francesca Meschi, Nikola O Kondov, Ryan Wilson, Jorge A Bernate, Shawn Gauby, Alex Kindwall, Clara Bermejo, Adrian N Fehr, Adrian Chan, Serge Saxonov, Kevin D Ness, Benjamin J Hindson, Hanlee P Ji

ABSTRACT

Haplotyping of human chromosomes is a prerequisite for cataloguing the full repertoire of genetic variation. We present a microfluidics-based, linked-read sequencing technology that can phase and haplotype germline and cancer genomes using nanograms of input DNA. This high-throughput platform prepares barcoded libraries for short-read sequencing and computationally reconstructs long-range haplotype and structural variant information. We generate haplotype blocks in a nuclear trio that are concordant with expected inheritance patterns and phase a set of structural variants. We also resolve the structure of the EML4-ALK gene fusion in the NCI-H2228 cancer cell line using phased exome sequencing. Finally, we assign genetic aberrations to specific megabase-scale haplotypes generated from whole-genome sequencing of a primary colorectal adenocarcinoma. This approach resolves haplotype information using up to 100 times less genomic DNA than some methods and enables the accurate detection of structural variants. More... »

PAGES

303-311

References to SciGraph publications

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  • Journal

    TITLE

    Nature Biotechnology

    ISSUE

    3

    VOLUME

    34

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nbt.3432

    DOI

    http://dx.doi.org/10.1038/nbt.3432

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1006254156

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26829319


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