As the world is challenged by habitat destruction, species loss, climate change, and dramatically modified community interactions, genetic is critical to help conserve and restore plant species. Yet, our knowledge of green plant genomes lags far behind that of some major clades on the tree of life. Plant genomes are tremendously complex and they have the ability to duplicate themselves or hybridize to rapidly innovate – a handy adaptation when you cannot physically move out of harm’s way. As computational biologists, we develop methods to assemble these genomes, identify the genes within, and understand their evolutionary history. The software we develop has been applied to a wide range of plant species, including several tree species of conservation concern. Our interest in open-source and reproducible software extends beyond single genomes to tools that support population-scale investigations. As such, we will introduce CartograPlant, the first web-based application that integrates genetics and traits data for georeferenced plants with global environmental layers. This field to analysis framework allows us to study how forest tree populations are adapting to a rapidly changing climate.
Jill Wegrzyn is an Associate Professor of Ecology and Evolutionary Biology in the Department at the University of Connecticut where she leads the Plant Computational Genomics Lab. She is also the director of the Computational Biology Core within the Institute of Systems Genomics. Her work focuses on the computational analysis of genomic and transcriptomic sequences from non-model plant species. She develops approaches to examine gene finding, gene expression, transcriptome assembly, and conserved element identification, through machine learning and computational statistics. She uses these novel methods to address questions related to genome biology and population genomics in forest tree species. She also develops web-based applications that integrate data across domains to facilitate the plant geneticist or ecologist’s ability to analyze, share, and visualize their data. Such integration requires the implementation of semantic technologies and ontologies to connect genotype, phenotype, and environmental data.
This is a Virtual Event. Pre-registration is now open!