Agenda

Aquaculture plays a growing role in global food security and sustainable protein production, but challenges related to disease, animal welfare, climate resilience and production efficiency remain. This workshop will explore how advances in genomics, sequencing technologies, artificial intelligence, and data science are transforming aquaculture breeding. Through scientific presentations, cross-sector discussions and an interactive exercise, participants will identify shared priorities and opportunities for collaboration across aquatic and terrestrial species.

This workshop will highlight the development of an open-source sorghum pangenome to advance climate-resilient breeding for smallholder farmers in the Global South. By capturing previously overlooked genetic diversity, the initiative aims to improve genomic prediction and identify new breeding targets. Through partnerships with the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), HudsonAlpha Institute for Biotechnology and the University of Washington, researchers are combining advanced sequencing and epigenomic mapping technologies. Presentations will share findings and explore how these resources can support sorghum breeding and improvement.

This workshop will explore how advances in precision genetics, reproductive biology and epigenetics can improve hybrid maize breeding and seed production. Discussions will highlight the connections between genetic technologies, plant reproduction and epigenetic regulation, examining opportunities to enhance seed quality, breeding efficiency and the development of more reliable and sustainable hybrid maize seed systems.

As climate change, resource constraints and growing food demand challenge global agriculture, accelerating genetic improvement across crops and livestock is increasingly critical. Hosted by the ARC Training Centre in Predictive Breeding, this workshop will explore what predictive breeding could look like in 2050 and the innovations needed to get there. The morning program will bring together researchers, data scientists and industry leaders to identify shared challenges and opportunities for collaboration. Through interactive discussions and scientific presentations, participants will explore advances in multi-omics, genomic prediction, artificial intelligence and genome editing, examining their potential impact, limitations and opportunities to improve breeding outcomes.

Advances in computer vision and artificial intelligence are transforming livestock breeding by enabling scalable, noninvasive collection of digital phenotypes. This workshop will explore how camera-based sensing, deep learning, and AI are advancing livestock phenomics and improving genetic selection for health, efficiency, welfare, resilience, and sustainability. Participants will learn about applications in growth, body composition, behavior, and reproduction, as well as the integration of digital phenotypes into genomic prediction and genetic evaluation. The workshop will also address challenges in large-scale implementation and emerging technologies shaping the future of livestock breeding.

This workshop will explore how advances in crop pangenomics, artificial intelligence, phenomics and quantitative genetics can transform genomic discoveries into more accurate trait prediction and improved breeding decisions. Building on recent progress in long-read sequencing and computational genomics, discussions will focus on translating complex genetic variation into practical tools for predicting hard-to-measure traits and accelerating genetic gain. Bringing together experts in plant genomics, AI, quantitative genetics and crop breeding from academia, nonprofit organizations and industry, the program will examine emerging approaches in pangenome-informed genotyping, structural and haplotype-aware prediction, and genome-to-phenome modeling.

This workshop will explore how synthetic biology and programmable plants could transform agriculture and advance sustainable crop production. Participants will examine how engineered plants can sense and respond to environmental conditions, communicate signals and interact with other organisms and technologies. Discussions will highlight practical applications, emerging opportunities and the technical, biological, social and regulatory challenges of implementing these innovations across agricultural systems.

Insights from human genomics with broader implications for genomic data sharing, interpretation, and discovery across species.

Hear directly from scientific journal editors about publishing trends, what makes research compelling, and strategies for successfully communicating discoveries. Following the moderated panel and audience Q and A, attendees will have an opportunity to connect with editors in small-group discussions. Space is limited.

As models and AI agents play an increasing role in scientific analysis and knowledge management, contextualization and accelerated scientific computing are becoming increasingly important. This applies to both AI-driven and traditional computational approaches, particularly when working with large-scale biological datasets. The workshop will highlight applications in genomic alignment and annotation, single-cell analysis, model tuning and accelerated inference, data federation, accelerated data science, and contextualized embedding with knowledge graphs. It will conclude with a discussion of contextualization, validation, and management of model-generated datasets.