Researchers at the University of California, Berkeley, have created a new artificial intelligence model called GPN-Star that helps analyze genetic data more efficiently. This model is designed to identify important genetic variations that influence inherited traits, including those linked to diseases. Published in the journal Nature, the model is notable for its ability to perform these tasks with less computational power than larger AI models, making it more accessible for researchers. GPN-Star was trained using whole-genome alignments (WGAs), which are comparisons of entire genomes across multiple species. This approach is different from traditional methods that use individual, unaligned genomes. By using WGAs, the model reduces the time and computing resources needed for training. According to Yun Song, a professor of computer science and statistics at Berkeley and senior author of the study, the model can detect patterns in DNA sequences and distinguish between parts of the genome that have functional roles and those that do not. The research team has made their genome-wide predictions publicly available, highlighting genetic variants that are likely to have a significant impact on inherited traits. These predictions were generated using data from three different human-anchored WGAs, as well as WGAs from various other species, including mice, fruit flies, chickens, roundworms, and a type of plant called Arabidopsis thaliana. Each of the human-anchored WGAs was built using genomes from different combinations of species, reflecting different points in evolutionary history. The study found that models trained on different evolutionary timescales were better suited to interpreting different types of genetic variants. This insight could help scientists better understand how genetic changes have shaped life across species. The researchers hope that their model will be easy for other teams to use, modify, and build upon, potentially speeding up discoveries in genetics and improving our understanding of how genes influence health and development in humans and other organisms.