Roads fragment natural landscapes and often lead to negative consequences for wildlife, especially larger mammals. Mitigating the effects of roads is a common conservation priority for state transportation and wildlife agencies. The state of Vermont is situated in the Northern Appalachian/Acadian Ecoregion and has been identified as an important area that supports broad-scale wildlife connectivity across the northeastern US and southeastern Canada. Efforts to improve connectivity across the ~25,000 km of roads in the state have focused on assessing the connectivity value of existing transportation structures, including bridges, culverts, and overpasses, to prioritize investments in facilitating wildlife movement through them. Other talks in this symposium titled ‘System-Wide Connectivity Advancements: Using Vermont’s Terrestrial Passage Screening Tool’ described the use of omni-directional circuit theory to measure and map connectivity for 8 key species and the value of these outputs for conservation planning and improving connectivity across the road network in the state. Depictions of connectivity for species were based on the notion that animal movement is a function of landcover variables. We extend these analyses by using genetic data to measure and map gene flow across the landscape, which estimates how landcover variables have historically shaped the movement of genes. We used genetic data collected from hair/tissue samples of two high priority species – American marten (Martes americana) and moose (Alces alces) – to model landscape resistance as a function of landcover variables. We then integrated genetic resistance surfaces into an omnidirectional circuit analysis to depict gene flow across the state and in relation to the road network. We explore how the results compare with other movement-based connectivity analyses (presented earlier in the symposium) and can be integrated into efforts to score and rank transportation structures for connectivity.