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Human Genome Reference Program Planning Meeting

Event Details

On October 13, 2022, the National Human Genome Research Institute holds the The Human Genome Reference Program (HGRP) Planning Meeting – The Future of HGRP meeting at the Bethesda Marriott Hotel.

All times in EDT.



Session Description


8:30 a.m.


Eric Green

8:40 a.m.

Introduction: purpose, goals, themes, deliverables, logistics

Alexander Arguello
Adam Felsenfeld

8:50 a.m.

Samples and sequencing

Charles Rotimi

Carlos Bustamante (v)Ben Neale, Alice Popejoy, Genevieve Wojcik (v)

9:55 a.m.


10:15 a.m.

Representation and implementation of a pangenome resource

Deanna Church

Erik Garrison, Gabor Marth (v), Pavel Pevzner (v), Adam Phillippy

11:15 a.m.

Dissemination: versioning, user outreach/education, and user tools

Eric Venner

Aravinda Chakravarti (v), Valerie Schneider, Liz Worthey

12:15 p.m.

Lunch on your own

1:15 p.m.

Engaging worldwide partners

Erin Riggs

Heather Lawson, Nicole Soranzo (v), Ambroise Wonkam

2:15 p.m.


2:30 p.m.


Alexander Arguello, Adam Felsenfeld, Deanna Church, Martin Hirst (v), Matt Lebo, Pavel Pevzner (v), Bob Waterston (v).

Key Issues and Questions to Consider

Samples and sequencing

The current program has a goal of ~350 high-quality genomes from diverse populations by late 2024. What should be the goals of a renewed program? Why?

  • What does a "finished" human pangenome look like (i.e., when are we "done”)?
  • Do we need more "pangenome quality" assemblies to achieve this?
  • How do we prioritize sample selection from different perspectives (population genetics, clinical utility,
    diversity and inclusion, others)?
    • At what cost and quality?
  • What consent and population naming standards should be used and how to encourage/integrate them?

Representation and implementation of a pangenome resource

  • Are the current graph and other data structure representations able to usefully represent the number of genome assemblies in the pangenome, now or in the near-to-mid future?
  • How much R&D on graph or other representations is still needed? Or should we concentrate on implementation of available representations?
  • In the next phase of the program, what should be the relative emphasis on R&D for pangenome representations vs aggressive roll-out of the pangenome reference to the community?
  • What is the best way to integrate this element into a larger program — how closely does this activity need to be linked to the other components of HGRP as well as other NIH programs?

Dissemination: versioning, user outreach/education, and user tools

  • What will the user community need/want for the next phase of the program?
  • What tools are needed? How best to encourage their generation and use?
  • How do we minimize version churn or achieve backward compatibility?
  • More generally, what other methods or resources are needed to gain acceptance?
  • In two years, what emphasis will this component need?

Engaging worldwide partners

  • Who are key long-term partners both for the implementation of the pangenome reference as the standard across studies and data types as well as achieving an international resource representing humanity?
    • What is needed to attain this, and what should NHGRI's specific role be?
  • How can NHGRI best help establish this international reference with relatively few resources?
  • Are there particular barriers that NHGRI needs to anticipate (political, cultural, ethical)?
  • Are there things NHGRI should not do, even if it could?


  • Should NHGRI have a coordinated program focused on the human genome reference in ~2024 - 2029?
  • If so, what high-level goals should it have?
  • What major program elements? How should they be related? integrated? How prioritized?
  • How to balance clinical, pop gen, functional genomics, and other user community needs?
  • How to creatively incorporate diversity, equity, and inclusion, in all aspects (participants, investigators, users/communities)
  • Key opportunities, or gaps? What are the main challenges/barriers to anticipate?
  • What strategies can we use to optimize/be efficient?
  • What would success look like? How to measure?

Last updated: April 7, 2023