Bionote
Talissa Floriani is a PhD student passionate about plants and genes. Located at the University of Illinois at Urbana-Champaign, Department of Crop Sciences, with Professor Alex Lipka as the Principal Investigator. Her work is related to genetics and plant breeding, with a focus on statistical genomics and machine learning analysis in sorghum.
Presentation Abstract
The role of ML in genetic association studies: Unraveling the genetic architecture of complex traits in crops demands innovative approaches that transcend the limitations of traditional genome-wide association studies (GWAS). This research challenges the prevailing paradigm by focusing on rare genetic variants—often undetected by conventional methods—yet critical in shaping agronomically important traits. Rare variants, characterized by their low allele frequency, hold untapped potential for improving our understanding of genotype-phenotype relationships, but their identification remains a formidable challenge. To address this gap, we integrate machine learning (ML) methodologies to enhance rare variant discovery and interpretation. Sorghum, a genetically diverse and ecologically resilient staple crop, provides an ideal model for this endeavor. As a species with five distinct genetic races, deciphering its rare variants offers profound implications for breeding strategies, particularly for traits linked to environmental resilience. This study aims to develop and apply a machine learning framework that improves rare variant detection, enhances predictive accuracy for complex traits, and bridges the gap between statistical genetics and computational approaches.
Co-Researcher (Advisor): Alex Lipka