The ASHG Genetic Diagnosis & Rare Disease Virtual Symposium will focus on rare genetic diseases, their clinical diagnosis, and the current/emerging technologies to understand them. The presentations will cover the diagnosis of rare diseases, from detecting difficult structural variation (such as intrachromosomal inversions) to approaches for reducing time-to-diagnosis with novel, integrative genomic methods.

All times listed below in Eastern USA.

Schedule

Day 1, December 2

10-11:30 am, Inversions in Rare Disease

Segments of DNA with altered sequenced orientation compared to the reference genome are inversions. These structural rearrangements, which can drive rare disease, can be difficult to detect. In this session, we'll discuss approaches to their detection, their molecular characteristics, features of inversion haplotypes, and their consequences in complex rearrangements.

11:30 - 1pm

Coming Soon!

Day 2, December 3

10-11:30 am, Diagnostic Approaches in the UDN

Individuals with rare, complex genetic diseases may spend years searching for a genetic cause of their condition (diagnostic odyssey). This session will cover approaches to shortening time-to-diagnosis. We'll discuss RNA-Seq diagnosis after failed genomic trio analysis, federated variant matching between patients, CAP/CLIA-certified RNA-Seq as a diagnostic, and profiling the epigenome with long-read sequencing.

11:30 - 1pm, Integrating Different 'Omics Data Sources

Technology has allowed us to assay many different aspects of cellular state, from genome sequence to proteomics to environmental exposure. This session will cover methods for integrating these different data sources into a coherent picture. We'll discuss challenges of integration (such as batch effects), how multi-omics can improve disease surveillance, the importance of community partners in multi-omics studies, and approaches to integrating environmental exposure with multi-omics data. 

Human pangenome assemblies unlock new insights into genetic diversity and previously unresolved genomic regions. This webinar equips participants with practical skills to explore human genomics beyond traditional reference genome. Explore the new Ensembl genome browser (https://beta.ensembl.org/)  with the latest human genomes available, and learn which tools are available to explore these in more detail. 

Overview of Presentation

• Define the Ensembl/GENCODE, MANE and GENCODE Primary annotation processes
• Explore the range of human assemblies and linked data for these available on the new Ensembl Browser
• List the web tools which can be used to query data from human assemblies on the new Ensembl platform

The excitement of discoveries in genetics and their applications to benefit people is accompanied by concerns for widespread and profound harms caused by misuse, even inadvertent, and misunderstanding of genetics. The importance of engaging people of all backgrounds in discussion about genetics and genomics is paramount, and the time for action is now. In this webinar, we will discuss strategies for participants to engage with other genetics professionals, educators, and the broader public to support informed civic engagement on genetics towards an equitable and just future.

Overview of Presentation

• Examine approaches for promoting understanding of and aid dialogue about genetics and surrounding social issues 
• Identify pressing issues surrounding genetics with potential for widespread harm. 
• Evaluate and design opportunities for science engagement at the intersection of genetics and justice 
• Develop a plan to become an advocate and ally for a more just future 

Artificial intelligence (AI) is revolutionizing the field of genomics, unlocking breakthroughs in both research and healthcare that were once unimaginable. By accelerating the analysis of large genomic datasets, AI uncovers critical patterns that illuminate gene networks, highlight risks for common diseases, and help pinpoint the causes of rare conditions. AI also plays a key role in advancing precision medicine by developing novel treatments, customizing therapies to individual genetic profiles, and predicting patient responses to therapies, all of which enhance diagnostic accuracy and treatment outcomes. However, the growing integration of AI in genomics raises important ethical considerations, including concerns about data privacy, informed consent, and the potential for biased algorithms to perpetuate existing inequalities. As AI continues to shape genomics, it is essential to balance innovation with ethical responsibility to ensure equitable access and outcomes for all patients. This session aims to stimulate thoughtful discussion on the transformative potential of AI in genomics while addressing its challenges and ethical implications. Attendees will leave with actionable insights on how to navigate the evolving landscape of AI in genomics research and healthcare and how they can contribute to shaping its future in a responsible and inclusive way.

Learning Objectives

*    Examine modern artificial intelligence compute architectures and how they are being leveraged to impact the practice of medicine
*    Identify the societal, ethical and economic challenges of the tools available for genomic health prediction, and how policymakers can address them
*    Examine the capabilities and limitations of AI in genomic medicine

ASHG's 2025 Annual Meeting was hosted in Boston, Massachusetts from October 14-18.

This package includes the following recordings:

Sessions

• Stronger Together: Advancing Human Genetics Through the Power of Community
• Featured Plenary Abstract Session I
• Integration of Long-Read Sequencing with Multi-Omics Data to Identify Hidden Causal Variants
• Alz in the Details: Piecing Together the Alzheimer's Puzzle
• Single-Cell Multiomic Dissection of Gene Regulation Across Disease States
• Awards Recognition I
• Presidential Symposium: Unraveling the Genetic Foundations of Human Disease: Insights from the Past, Present, and Future
• Update on Recent Changes at NIH and NHGRI: What Researchers Need to Know
• Artificial Intelligence and Machine Learning Tools Reshaping Modern Genomics
• Dissecting the Biology of Neurodegenerative Disorders
• Genetic Insights Fueling Drug Discovery and Precision Health
• Awards Recognition II
• Featured Plenary Abstract Session II
• Deep Learning for Non-coding Variant Interpretation
• Awards Recognition III
• Featured Plenary Abstract Session III
• AI-Powered Genomics: Transforming Data into Insights

This plenary session will explore the complexity and diversity of the human genome through innovative research on haplotypes, structural variation, and population-specific genetic architecture. Speakers will present findings from large-scale studies on chromatin organization, the evolving human pangenome, and ancestry-specific risk factors for diseases such as breast cancer and dyslipidemia. The session will conclude with insights into how rare deleterious mutations influence human lifespan across diverse populations.

Learning Objectives

*    Examine advances in genome representation and structure
*    Recognize how genetic architecture varies across populations and contexts
*    Explain the pangenome and potential downstream applications

ASHG recognizes three of its annual professional award recipients, each of whom will speak on their accomplishments: Anthony Wynshaw-Boris, Advocacy Award recipient; Audrey Hendricks, Education Award recipient; and Mike Talkowski, Scientific Achievement Award recipient. Winners of the ASHG Trainee Research Excellence Awards are also announced. 

Non-coding genetic variants are important drivers of trait variation in humans and other eukaryotic species. As a result, functionally characterizing non-coding variants is a major goal of modern genetics, with important implications for our understanding of the molecular basis of disease and evolution. Deep learning models are a powerful approach for predicting regulatory activity from genomic sequence and interpreting the cis-regulatory code. In this session, four leading scientists will present their work on leveraging such models to interpret the effects of regulatory variation. These talks will highlight recent advances in deep learning for variant effect interpretation, limitations in existing models, and strategies for improvement. Particular advancements that will be discussed will include improvements in model architecture and training, novel interpretation and variant scoring techniques, and emerging strategies to scale model training across populations and tissue types.

Learning Objectives

 *   Highlight challenges of deep learning models for non-coding variant interpretation.
 *   Design deep learning architectures trained on functional human genetic variation.
 *   Construct deep learning models capturing the syntax of cell type-specific gene expression.

This plenary session will highlight the breadth and depth of human genetic research, covering topics related to basic, clinical, and translational research. Specifically, the five talks will highlight i) how cellular models and high-throughput technologies can dissect regulatory mechanisms across biological systems, ii) the associations of complex genomic regions with human traits and diseases, and iii) understand the dynamics related to insurance coverage for germline genetic testing for hereditary cancer.

Learning Objectives

*    Evaluate functional impact of genome regulation at scale
*    Explain insurance coverage for germline genetic testing for hereditary cancer
*    Assess the effect of complex genomic regions on human health and disease

ASHG recognizes two of its annual professional award recipients, each of whom will speak on their accomplishments: Eric Green, Leadership Award recipient and Elizabeth Bhoj, Early Career Award recipient. Winners of the AJHG Award for Outstanding Trainee Publication and HGGA Award for Outstanding Early Career Publication are also recognized.