Next-Generation Sequencing in the Clinical Laboratory

Abstract Next-generation (or massively parallel) sequencing has rapidly supplanted traditional Sanger sequencing as the preferred methodology for acquiring clinical sequence data. Massively parallel sequencing offers numerous advantages including high sensitivity and specificity for genetic variants, the ability to consolidate numerous molecular tests to a single platform, and unprecedented sequencing throughput. However, reaping the full benefit of this new technology is a complicated, collaborative undertaking, and relies upon the interdependency of three disciplines: chemistry, computer science, and clinical medicine. Specialized sequencing instruments can simultaneously sequence a host of genetic targets in numerous patient samples, generating millions of sequence reads per reaction. Thus, informatics tools are necessary for searching these data and structuring information in a format that can be understood by a molecular pathologist. Finally, clinical understanding of the impact of genetic variants on disease diagnosis, treatment, and prognosis is used to generate a relevant clinical report.

[1]  W. Grody,et al.  ACMG recommendations for standards for interpretation and reporting of sequence variations: Revisions 2007 , 2008, Genetics in Medicine.

[2]  Michael R. Speicher,et al.  A survey of tools for variant analysis of next-generation genome sequencing data , 2013, Briefings Bioinform..

[3]  Marc S. Williams,et al.  ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing , 2013, Genetics in Medicine.

[4]  M. Dolled-Filhart,et al.  Computational and Bioinformatics Frameworks for Next-Generation Whole Exome and Genome Sequencing , 2013, TheScientificWorldJournal.

[5]  Paul Flicek,et al.  Sense from sequence reads: methods for alignment and assembly , 2009, Nature Methods.

[6]  Mauricio O. Carneiro,et al.  Pacific biosciences sequencing technology for genotyping and variation discovery in human data , 2012, BMC Genomics.

[7]  Philip Hugenholtz,et al.  Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data , 2013, PLoS Comput. Biol..

[8]  S. Whittaker,et al.  BRAF mutation testing algorithm for vemurafenib treatment in melanoma: recommendations from an expert panel , 2013, The British journal of dermatology.

[9]  S. Turner,et al.  Zero-Mode Waveguides for Single-Molecule Analysis at High Concentrations , 2003, Science.

[10]  Szymon Grabowski,et al.  Compression of DNA sequence reads in FASTQ format , 2011, Bioinform..

[11]  Cheng-Yao Chen.  DNA polymerases drive DNA sequencing-by-synthesis technologies: both past and present , 2014, Front. Microbiol..

[12]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[13]  M. Fiorentino,et al.  454 next generation-sequencing outperforms allele-specific PCR, Sanger sequencing, and pyrosequencing for routine KRAS mutation analysis of formalin-fixed, paraffin-embedded samples , 2013, OncoTargets and therapy.

[14]  W. Kibbe,et al.  Review of Current Methods, Applications, and Data Management for the Bioinformatics Analysis of Whole Exome Sequencing , 2014, Cancer informatics.

[15]  M. Fedurco,et al.  BTA, a novel reagent for DNA attachment on glass and efficient generation of solid-phase amplified DNA colonies , 2006, Nucleic acids research.

[16]  Christophe Dessimoz,et al.  Base-calling for next-generation sequencing platforms , 2011, Briefings Bioinform..

[17]  Bernard P. Puc,et al.  An integrated semiconductor device enabling non-optical genome sequencing , 2011, Nature.

[18]  Elaine R. Mardis,et al.  A decade’s perspective on DNA sequencing technology , 2011, Nature.

[19]  François Ducray,et al.  Predictive biomarkers in adult gliomas: the present and the future , 2013, Current opinion in oncology.

[20]  Larry N. Singh,et al.  Secondary variants in individuals undergoing exome sequencing: screening of 572 individuals identifies high-penetrance mutations in cancer-susceptibility genes. , 2012, American journal of human genetics.

[21]  Robert Brian Jenkins,et al.  Molecular Testing Guideline for Selection of Lung Cancer Patients for EGFR and ALK Tyrosine Kinase Inhibitors: Guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology , 2013, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[22]  C. Hutchison.  DNA sequencing: bench to bedside and beyond , 2007, Nucleic acids research.

[23]  Joel Gelernter,et al.  Variant Callers for Next-Generation Sequencing Data: A Comparison Study , 2013, PloS one.

[24]  H. Swerdlow,et al.  A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers , 2012, BMC Genomics.

[25]  Heng Li,et al.  A survey of sequence alignment algorithms for next-generation sequencing , 2010, Briefings Bioinform..

[26]  Joshua L. Deignan,et al.  ACMG clinical laboratory standards for next-generation sequencing , 2013, Genetics in Medicine.

[27]  P Green,et al.  Base-calling of automated sequencer traces using phred. II. Error probabilities. , 1998, Genome research.

[28]  T. Dallman,et al.  Performance comparison of benchtop high-throughput sequencing platforms , 2012, Nature Biotechnology.

[29]  S. Turner,et al.  Real-Time DNA Sequencing from Single Polymerase Molecules , 2009, Science.

[30]  Tina Hambuch,et al.  Opportunities and challenges associated with clinical diagnostic genome sequencing: a report of the Association for Molecular Pathology. , 2012, The Journal of molecular diagnostics : JMD.