To kick-off the ASHG 2024 Annual Meeting, ASHG President, Dr. Bruce Gelb will provide a warm welcome to ASHG’s global audience with his Presidential Address and Welcome.

This session highlights cutting-edge research being conducted across the field of human genetics and genomics. This includes examination of natural selection in mosaic chromosomes, meiotic recombination in in vitro fertilized embryos, uniparental disomy in congenital heart disease, long-read sequencing to identify alternative RNA-splicing, the power of combining biobanks together to discover rare variant associations.

Learning Objectives:

1. Summarize the landscape of mosaic chromosomal alterations (mCA’s) across 66,000 individuals from diverse and understudied populations, including how gene expression can reveal evolutionary dynamics of clonal expansion within individuals.
2. State how the use of preimplantation genetic testing (PGT) data from in vitro fertilized (IVF) embryos can elucidate the process of meiotic recombination and its complex genetic architecture.
3. Summarize how uniparental disomy (UPD) events, some of which include variants of uncertain significance (VUS), have been linked to congenital heart disease (CHD) and the related phenotypes observed in zebrafish experiments.
4. Formulate an experiment using a new method, isoLASER, to leverage long-read RNA-seq data to classify splicing events via cis- or trans-directed mechanisms.
5. Generalize findings from rare variant association testing within a global biobank meta-analysis consortium.

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

Biobank scale genetic data resources for studying complex and rare human diseases are introduced in this session, including 100K Genomes of Europe, UAE Genome Program with 43K individuals, Structural variants from the All of US Research Program, and a complete telomere-to-telomere reference pnael of 6K human haplotypes. Updates about diversity in the NHGRI-EBI GWAS Catalog will be shared. A web resource of Mondo harmonizes the world's rare disease knowledge, which will help rare disease diagnosis.

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

While we know have an increased appreciation for the regulatory roles of the non-coding genome, there are still many regions which remain to be defined. This session will leverage cross-species comparisons, epigenetic approaches and machine learning to interpret the non-coding genome. Moreover, massively parallel reporter assays are an increasingly attractive technology for functionally testing the regulatory potential of non-coding DNA at scale, the use of this technology will also be presented.

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

The challenge of missing heritability is well documented. This session moves beyond standard models of genetic architecture to learn how the complex evolutionary history of a species has shaped different aspects of complex traits.

Learning Objectives:
1. Identify key determinants of gene discovery in Genome Wide Association Studies (GWAS) and Rare Variant Association Studies (RVAS).
2. Examine the influence of admixture in complex diseases.
3. Compare ethnolinguistic, genetic, and geographic data to improve our understanding of genetic variation and ethnolinguistic diversity in eastern and southern African populations and the relationship between them.
4. Identify genetic variants under ongoing natural selection that contribute to disease susceptibilities

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

Since the origins of the field of human genetics nearly 125 years ago, there have been robust conversations about how to characterize genetic traits and disorders across the range from simple to complex. The intellectual framework has great importance in how human genetics is applied, particularly in an era when population genetic screening for so-called single-gene disorders has become increasingly feasible. The 2024 Presidential Symposium will feature three leaders across aspects of this topic: the history of the intellectual debate over simplicity vs. complexity in human genetics; understanding how genetic complexity modifies a paradigmatic simple genetic trait, sickle cell disease; and how randomness (i.e., stochasticity) contributes to phenotypes.

Learning Objectives:
1. Compare simplicity-first (Mendelian) and complexity-first (Weldonian) framings for an elementary genetics curriculum
2. Recognize that sickle cell disease is a monogenic disorder that shows wide variability in clinical outcomes, in part, due to the presence of genetic modifiers
3. Recognize how experiments in gene-edited model organisms can provide insights into the dynamic emergence of developmental defects, focusing on stochastic contributions to partial penetrance

The Trans-Omics in Precision Medicine (TOPMed) project of the National Heart, Lung, and Blood Institute (NHLBI) has supported genomic data generation and harmonization for many U.S. and international-based studies. These include deep whole-genome sequencing (WGS) data and omics datasets. TOPMed is one of the largest resources of WGS and omics (>180,000 WGS, >70,000 funded methylation, RNA-seq, and metabolomics assays, >40,000 proteomics). Importantly, the TOPMed program focuses on data collection from under-studied and under-represented populations such as Hispanic and Latino individuals in the U.S., African, and African American individuals. This session will highlight the 10th anniversary of the TOPMed program and focus on the future use of the TOPMed resource by the broader research community. The session will begin with an “overview of TOPMed” talk by Dr. Gan, the NHLBI program director who oversees TOPMed, describing the vision that motivated TOPMed, highlight major TOPMed milestones, and introduce the vision for the next step of TOPMed. Dr. Gan will also cover the current process for accessing TOPMed data and ideas to improve the process. Four talks will follow highlighting findings enabled by TOPMed: insights into genetic diversity, selection, and population dynamics from large scale sequencing, and findings from integration of omics and genetics. A panel discussion will introduce additional achievements, gaps, and outline to the community how they can use this massive resource.

Learning Objectives:
1. Describe inference and implications of genetic effects at the population levels from ultra-rare genetic variants
2. Identify mechanisms by which trans-eQTLs impact gene expression
3. Examine genetic influences on circulating metabolites with diverse populations via a novel, large multi-ancestry harmonized metabolomics data set
4. State new findings about how proteins causally affect other proteins in human plasma and use of genetic data to infer these relationships

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

This section will focus on applying novel technologies to access gene regulation networks, understand complex disease mechanism, and deep learning approaches for sequencing data analysis and rare variant interpretation.

Learning Objectives:
1. State the advantages of multimodal single cell sequencing in defining CRISPR induced genetic variation.
2. Identify the gene regulatory mechanisms downstream of neuron-astrocyte interactions.
3. Evaluate the relationship between circRNA function and Alzheimer's disease.
4. Construct an in silico module for comprehensive gene regulatory networks analyses.
5. Design novel methods and deep learning approaches for sequencing data analysis.
6. Define a new approach to interpret rare variants when the goal is to identify a sub-population at low risk of disease

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

This session showcases state-of-the-art methods for prioritizing causal risk variants in complex trait genetic studies.

Learning Objectives:
1. Identify genetic variants associated with transcription factor binding in liver.
2. Examine using machine learning to predict and prioritize the effects of non-coding variants on diseases, leveraging functional annotations and GWAS data to identify causal variants and gain biological insights.
3. Manage robustness of summary statistics-based methods under LD mismatch.
4. Evaluate whether current genome language and other deep learning models can help pinpoint causal variants in statistical fine-mapping

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.

This session highlights high scale profiling efforts using different experimental platforms and in different disease settings. This includes heritability analysis in environmental risk and air pollution, methylome and omics (GWAS, TWAS, PWAS) analysis in cancer, global profiling of Cas9 editing sites, and transcriptomics in rare disease.

Learning Objectives:
1. Evaluate several novel strategies for jointly modeling genetic and environmental effects on disease risk using large EHR datasets.
2. Examine how early methylation changes occur and how they interact with other epigenomic shifts.
3. Identify critical pathways in endometriosis pathogenesis using omics approaches.
4. Apply a new sequencing method for targeted pooled and in vivo ribonucleoprotein CRISPR screens in hard-to-transduce cell types and detection of off-target perturbations.
5. Judge a transcriptomics-first method to diagnose rare disease patients by examining transcriptome-wide patterns of minor intron retention events.

Please note: This item is only available as part of the ASHG 2024 Annual Meeting Digital Pass.