REXTAL: Regional Extension of Assemblies Using Linked-Reads

  • Tunazzina IslamEmail author
  • Desh Ranjan
  • Eleanor Young
  • Ming Xiao
  • Mohammad Zubair
  • Harold Riethman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10847)


It is currently impossible to get complete de novo assembly of segmentally duplicated genome regions using genome-wide short-read datasets. Here, we devise a new computational method called Regional Extension of Assemblies Using Linked-Reads (REXTAL) for improved region-specific assembly of segmental duplication-containing DNA, leveraging genomic short-read datasets generated from large DNA molecules partitioned and barcoded using the Gel Bead in Emulsion (GEM) microfluidic method [1]. We show that using REXTAL, it is possible to extend assembly of single-copy diploid DNA into adjacent, otherwise inaccessible subtelomere segmental duplication regions and other subtelomeric gap regions. Moreover, REXTAL is computationally more efficient for the directed assembly of such regions from multiple genomes (e.g., for the comparison of structural variation) than genome-wide assembly approaches.


10X sequencing Linked-read sequencing Subtelomere Assembly Segmental duplication Structural variation Genome gaps 



The work in this paper is supported in part by NIH R21CA177395 (HR and MX), and Modeling and Simulation Scholarship (to TI) from Old Dominion University.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Tunazzina Islam
    • 1
    Email author
  • Desh Ranjan
    • 1
  • Eleanor Young
    • 2
  • Ming Xiao
    • 2
    • 3
  • Mohammad Zubair
    • 1
  • Harold Riethman
    • 4
  1. 1.Department of Computer ScienceOld Dominion UniversityNorfolkUSA
  2. 2.School of Biomedical EngineeringDrexel UniversityPhiladelphiaUSA
  3. 3.Institute of Molecular Medicine and Infectious Disease, School of MedicineDrexel UniversityPhiladelphiaUSA
  4. 4.School of Medical Diagnostic and Translational SciencesOld Dominion UniversityNorfolkUSA

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