AUG 20, 2014 7:30 AM PDT

Panel Discussion: Increasing productivity and reproducibility by automating DNA library preparation for Ion Torrent Sequencing

Speaker
  • Joanna Hamilton, PhD, Co-Director, Dartmouth Medical School and the Norris Cotton Cancer Center Lynne Apone, PhD, Application and Product Development Scientist, NEBNext group, New England Bi
    Biography
      Joanna Hamilton is the Co-Director of the Genomics Shared Resource at Dartmouth Medical School and the Norris Cotton Cancer Center in Lebanon NH.  Dr. Hamilton received her PhD in 2005 in Cancer Biology and completed her post-doc training in Cardiology at Dartmouth.  In 2010, she joined the Genomics Shared Resource and was promoted to Co-Director in 2012.  Dr. Hamilton has been responsible for implementing the deep sequencing services available to researchers and is knowledgeable of both Illumina and Ion Torrent sequencing platforms and microarrays technologies.
      Dr. Lynne Apone is an Application and Product Development Scientist at New England Biolabs, working in the NEBNext group. Dr. Apone received her PhD in Biomedical Sciences from the University of Massachusetts, Worcester. She remained at UMMC as a Post Doctoral fellow and later, an Instructor. Dr. Apone joined Agencourt Personal Genomics in 2005 as a member of the team tasked to develop the SOLiD next generation sequencing platform. In 2010 she joined New England Biolabs where she focuses on the development of products and applications that enable high throughput sequencing on the Ion Torrent and Illumina platforms.
      Zach Smith currently serves as a Senior Applications Scientist at Beckman Coulter, Inc. developing applications for next generation sequencing (NGS) and other life science methods on Beckman's BioMek liquid handing robots. Prior to this, Zach served for over eight years as a Project Scientist at the Center for Genomics and Bioinformatics at Indiana University, Bloomington, where he contributed to several large genome sequencing projects including the cladoceran microcrustacean Daphnia pulex , the jewel wasp  Nasonia vitripennis, the lone-star tick Amblyomma americanum, and others.  Zach completed a Bachelor's of Science in Biology from Indiana University in 2002, followed by a Masters of Environmental Science from Indiana University's School of Public and Environmental Affairs in 2012.

    Abstract

    Next Generation Sequencing has revolutionized genomic variant discovery. The major bottle-neck for sequencing projects is the individual, biological sample, library preparation. This platform specific addition of adaptor sequences to the target DNA of interest is often technically challenging and manually time-consuming. In the Genomics Shared Resource at the Geisel School of Medicine at Dartmouth, we have recently implemented automation of several of our DNA library preparation procedures in collaboration with Beckman Coulter. The NEBNext Fast Fragmentation Library Preparation for Ion Torrent sequencing was automated on the BioMek 4000 liquid handler. This automation allowed us to increase our turnaround times by 2 fold, and also increased the reproducibility of library preparations, and prevents the need for repeated preparations due to technical errors, which were not present in the automated method. Details of the automation methods, library characteristics and sequencing results will be presented. Additional automated methods have been developed for a custom cancer gene panel and whole exome sequencing libraries, the rationale and details for these will be discussed.


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    AUG 20, 2014 7:30 AM PDT

    Panel Discussion: Increasing productivity and reproducibility by automating DNA library preparation for Ion Torrent Sequencing


    Specialty

    Antibodies

    Virology

    Immunology

    Dna Sequencing

    Personalized Medicine

    Clinical Diagnostics

    Immunity

    Cancer Diagnostics

    Immunotherapy

    Bioinformatics

    Flow Cytometry

    Immuno-Oncology

    Gene Expression

    Dna

    Big Data

    Geography

    Europe100%

    Registration Source

    Website Visitors100%

    Job Title

    Student100%

    Organization

    Academic Institution100%


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