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Identifying Research Priorities to Accelerate Genetic Diagnosis

Event Details

Whole-exome sequencing (WES) and whole-genome sequencing (WGS) are commonly used methods for determining causal variants underlying Mendelian disease. Although WES and WGS have proven to be transformational approaches, much work remains to advance our understanding of the genetic cause of Mendelian conditions and to increase the solve rate for rare disease. The National Human Genome Research Institute (NHGRI) is interested in obtaining feedback from the scientific community to better understand the major challenges, gaps and opportunities for developing solutions to this complex issue.

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Agenda

  • Day 1 - Tuesday, April 16th, 2024

  • 8:30 AM – Arrival and registration
  • 9:00 AM – Welcome and Overview of Workshop Goals
    Lisa Chadwick, NHGRI
  • 9:10 AM – Session 1: Tapping into Emerging Technologies
    Moderator: Heather Colley, NHGRI
  • 9:10 AM – Setting the Stage
    Ali Crawford, Illumina
  • 9:25 AM – Panel Discussion
    Ali Crawford, Illumina
    Adam Kennedy, Metabolon, Inc. 
    Tomi Pastinen, Children’s Mercy Kansas City
    Bekim Sadikovic, London Health Sciences Centre
    Ashleigh Schaffer, Case Western Reserve University
    Andrew Stergachis, University of Washington
  • 10:25 AM – Break
  • 10:45 AM – Session 2: Data Sharing is Caring
    Moderator: Robb Rowley, NHGRI
  • 10:45 AM – Setting the Stage 
    Heidi Rehm, Broad Institute/MGH
  • 11:00 AM – Panel Discussion
    Paul Kruszka, GeneDx
    Heidi Rehm, Broad Institute/MGH
    Tania Simoncelli, Chan Zuckerberg Initiative
    Deanne Taylor, CHOP/University of Pennsylvania
  • 12:00 PM - Lunch
  • 1:00 PM – Session 3: Genetics, it’s Complicated
    Moderator: Jennifer Troyer, NHGRI
  • 1:00 PM – Setting the Stage
    David Adams, NHGRI
  • 1:15 PM – Panel Discussion
    David Adams, NHGRI
    Garry Cutting, Johns Hopkins University
    Glennis Logsdon, University of Pennsylvania
    Sarah Morton, Boston Children’s Hospital
    Melissa Wilson, Arizona State University
  • 2:15 PM - Break
  • 2:35 PM – Session 4: Effectively Linking Variants to Function
    Moderator: Erin Ramos, NHGRI
  • 2:35 PM – Setting the Stage
    Doug Fowler, University of Washington
  • 2:50 PM – Panel Discussion
    Naiara Akizu, CHOP/University of Pennsylvania
    Doug Fowler, University of Washington
    Steve Murray, The Jackson Laboratory
    Saba Parvez, Northwestern University
    Steve Reilley, Yale School of Medicine
  • 3:50 PM - Break
  • 4:10 PM – Session 5: Computational Tools to Enable Genetic Diagnoses
    Moderator: Chris Wellington, NHGRI
  • 4:10 PM – Setting the Stage
    Nara Lygia De Macena Sobreira, Johns Hopkins University
  • 4:25 PM  - Panel Discussion
    Egor Dolzhenko, Pacific Biosciences
    Erik Garrison, The University of Tennessee Health Science Center
    Konrad Karczewski, Broad Institute/MGH
    Anshul Kundaje, Stanford University
    Nara Lygia De Macena Sobreira, Johns Hopkins University
  • 5:25 PM – Wrap up from Day 1 
  • Day 2 - Wednesday, April 17, 2024

  • 9:00 AM – Recap of Day 1: Major Takeaways
    Heather Colley, NHGRI
    Erin Ramos, NHGRI
    Robb Rowley, NHGRI
    Jennifer Troyer, NHGRI
    Chris Wellington, NHGRI
  • 9:30 AM - Session 6: What are we missing? 
    Moderator: Carolyn Hutter, NHGRI
  • 9:30 AM – Open Discussion
    All attendees
  • 10:30 AM -  Break
  • 10:50 AM – Session 7: Recommendations
    Moderator: Lisa Chadwick, NHGRI
  • 10:50 AM – Open Discussion
    All attendees
  • 12:00 PM - Meeting Close

Scientific Planning Committee

Ali Crawford
Illumina

Aaron Quinlan
The University of Utah

Nara Lygia De Macena Sobreira
Johns Hopkins University School of Medicine

Contacts

Lisa Chadwick
Lisa H. Chadwick, Ph.D.
  • Program Director
  • Division of Genome Sciences
Heather Colley
Heather A. Colley, M.S.
  • Program Director
  • Division of Genomic Medicine
Sara Currin
Sara Currin, B.S.
  • Scientific Program Analyst
  • Division of Genome Sciences
Chris Wellington, B.S.
Chris Wellington, B.S.
  • Program Director, Computational Genomics and Data Science
  • Office of Genomic Data Science
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Last updated: April 4, 2024