Daniel Runcie

Daniel Runcie's lab research delves into understanding the intricate interplay between environmental factors and genetic disparities among plant varieties, shaping their performance. Employing gene expression assays across both controlled laboratory settings and real-world field conditions, he and his team unveil the pivotal molecular pathways dictating phenotypic variations among genotypes. They also craft sophisticated statistical methodologies to distill insights from vast datasets. With a core focus on enhancing predictions of crop performance, deciphering the forces molding the evolutionary trajectories of natural plant populations, and pinpointing pivotal systems constraining plant adaptability in the face of climate change, Daniel and his team wield an arsenal of tools, including statistics, quantitative genetics, gene network and ecophysiological models, bioinformatics, and laboratory experiments. The bulk of their projects revolves around gene expression analysis, aimed at unraveling molecular variations within specific gene networks and establishing connections between gene expression traits and variations in plant development or physiology.