Objective
This talk aims to clarify foundational concepts in genetics and epistasis for a broad audience, and further introducing Next-Gen GWAS (NGG) (1) as a novel approach for exploring complex genetic interactions. I will focus on how NGG could enhance cannabis traits and support studies on human responses to active cannabis compounds.

Methods
I will begin by explaining the basics of genetics and epistatic interactions, emphasizing NGG’s ability to uncover previously hidden gene interactions. In the second part, I will demonstrate how we use generative AI to design peptides that modulate plant growth and how these peptides can be tailored to interact with specific proteins.

Summary
From a genetic perspective, we can now dissect >100 billions of epistatic interactions in plants and humans, significantly improving phenotype prediction (1). Additionally, we have developed AI generated peptides that have a profound impact on plant development.

Learning Objectives:

• Learn the basics of genetics for gene-to-trait analysis in plants and animals, with new insights into our technique, NGG, which opens new avenues in plant and human studies
  
  
•  Discover how generative AI can be used to design regulatory molecules (peptides) that control plant traits and beyond