Mesas Redondas

"Genetics is undergoing a profound transformation driven by advances in sequencing technologies, the massive generation of biological data, and artificial intelligence. The ability to analyze genomes at population scale, integrate genetic information with clinical and environmental data, and identify previously inaccessible patterns is expanding our understanding of the mechanisms underlying health, disease, and biological diversity. Artificial intelligence is accelerating multiple stages of genetic research, from identifying and interpreting genetic variants to understanding gene regulation, protein structure and function, and interactions among genes, cells, and the environment. Increasingly sophisticated computational models can generate hypotheses, establish genotype–phenotype relationships, and prioritize targets for experimental validation. In this context, AI does not replace experimental research; rather, it expands our capacity to explore complex biological systems and is changing the way scientific questions are formulated and tested. These developments are also shortening the path from scientific discovery to practical applications. In healthcare, they are creating opportunities for more accurate diagnosis, risk stratification, precision medicine, drug discovery, and gene and cell therapies. In agriculture and animal production, AI-assisted genetics can accelerate breeding programs, improve disease resistance, and support the development of production systems better adapted to climate change. In biodiversity conservation, integrating genomics and AI provides new tools to characterize populations, monitor species, and guide conservation strategies. At the same time, this new frontier raises important scientific, ethical, and societal challenges. Data quality and representativeness, algorithmic bias, protection of genetic information, privacy, consent, intellectual property, and equitable access to the benefits of these technologies are becoming central issues. For countries with extensive genetic and biological diversity, such as Brazil, developing representative genomic databases, computational infrastructure, scientific expertise, and locally developed AI models will be particularly important. Genetics in the age of AI therefore represents more than adopting a new technological tool. It is transforming how knowledge is generated and translated into innovation. The challenge ahead is to integrate genetics, biology, data science, and artificial intelligence with experimental and clinical research, while training a new generation of scientists who can work across disciplines and establish governance frameworks that ensure responsible, secure, and socially relevant use of the knowledge generated."