Evaluating inbreeding and assessing the risk of outbreeding depression in genetic rescue using whole-genome sequence data
Abstract
Restoring genetic diversity through assisted migration is increasingly recognized as a crucial strategy to counteract inbreeding depression and boost genetic variation in small and fragmented populations yet concerns about outbreeding depression often hinder its application. We propose a genomics-informed update to an existing framework enabling a more precise assessment of outbreeding depression risk and genetic rescue feasibility. We apply this approach to a butterfly species—the marsh fritillary ( Euphydryas aurinia )—which has faced severe range contractions and near-extinction in Denmark. We identify substantial inbreeding in the investigated populations (F ROH approaching 40%), historical gene flow, recent divergence times between populations, and low likelihood of local adaptation. Together, these results provide an example where genetic rescue could be undertaken successfully by transplanting individuals across populations with minimal outbreeding depression risks. Despite working with a scaffold-level assembly and moderate sample sizes, our analyses provide robust insights into population dynamics, demography, and local adaptation, demonstrating that even imperfect genomic data can inform conservation strategies. By refining an existing framework, we illustrate how genomics can enhance genetic rescue efforts and guide decision-making for threatened species. Our approach provides a scalable model for integrating genomic data into conservation management, advancing the use of evolutionary and conservation genetics principles in mitigating biodiversity loss.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (4)
Aja Noersgaard Buur Tengstedt
Department of Biology, Aarhus University
Toke Thomas Høye
Torsten Nygaard Kristensen
Department of Chemistry and Bioscience, Aalborg University
Michael M. Hansen
Department of Biology, Aarhus University