BioTechniques (Jul 2014)
A workflow to increase verification rate of chromosomal structural rearrangements using high-throughput next-generation sequencing
- Kelly Quek,
- Katia Nones,
- Ann-Marie Patch,
- J. Lynn Fink,
- Felicity Newell,
- Nicole Cloonan,
- David Miller,
- Muhammad Z. H. Fadlullah,
- Karin Kassahn,
- Angelika N. Christ,
- Timothy J. C. Bruxner,
- Suzanne Manning,
- Ivon Harliwong,
- Senel Idrisoglu,
- Craig Nourse,
- Ehsan Nourbakhsh,
- Shivangi Wani,
- Anita Steptoe,
- Matthew Anderson,
- Oliver Holmes,
- Conrad Leonard,
- Darrin Taylor,
- Scott Wood,
- Qinying Xu,
- Peter Wilson,
- Andrew V. Biankin,
- John V. Pearson,
- Nic Waddell,
- Sean M. Grimmond
Affiliations
- Kelly Quek
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Katia Nones
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Ann-Marie Patch
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- J. Lynn Fink
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Felicity Newell
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Nicole Cloonan
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- David Miller
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Muhammad Z. H. Fadlullah
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Karin Kassahn
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Angelika N. Christ
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Timothy J. C. Bruxner
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Suzanne Manning
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Ivon Harliwong
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Senel Idrisoglu
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Craig Nourse
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Ehsan Nourbakhsh
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Shivangi Wani
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Anita Steptoe
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Matthew Anderson
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Oliver Holmes
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Conrad Leonard
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Darrin Taylor
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Scott Wood
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Qinying Xu
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Peter Wilson
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Andrew V. Biankin
- 3The Kinghorn Cancer Centre, Cancer Research Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
- John V. Pearson
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Nic Waddell
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- Sean M. Grimmond
- 1Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, University of Queensland, St Lucia, Brisbane, QLD, Australia
- DOI
- https://doi.org/10.2144/000114189
- Journal volume & issue
-
Vol. 57,
no. 1
pp. 31 – 38
Abstract
Somatic rearrangements, which are commonly found in human cancer genomes, contribute to the progression and maintenance of cancers. Conventionally, the verification of somatic rearrangements comprises many manual steps and Sanger sequencing. This is labor intensive when verifying a large number of rearrangements in a large cohort. To increase the verification throughput, we devised a high-throughput workflow that utilizes benchtop next-generation sequencing and in-house bioinformatics tools to link the laboratory processes. In the proposed workflow, primers are automatically designed. PCR and an optional gel electrophoresis step to confirm the somatic nature of the rearrangements are performed. PCR products of somatic events are pooled for Ion Torrent PGM and/or Illumina MiSeq sequencing, the resulting sequence reads are assembled into consensus contigs by a consensus assembler, and an automated BLAT is used to resolve the breakpoints to base level. We compared sequences and breakpoints of verified somatic rearrangements between the conventional and high-throughput workflow. The results showed that next-generation sequencing methods are comparable to conventional Sanger sequencing. The identified breakpoints obtained from next-generation sequencing methods were highly accurate and reproducible. Furthermore, the proposed workflow allows hundreds of events to be processed in a shorter time frame compared with the conventional workflow.
Keywords
- next-generation sequencing
- cancer
- chromosome breakpoints
- structural variation
- verification
- high-throughput