The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation
Jong Yoon Jeon, Yucheol Shin, Andrew J. Mularo, Xiao Feng, J. Andrew DeWoody
Abstract
Abstract Background Ecological and genomic attributes of populations can provide two orthologous perspectives on the biological profiles associated with local adaptation. The ability of organisms to track suitable habitats (ecological adaptability) and of populations to shift allele frequencies (adaptive potential) are prerequisite for population sustainability. Aims Many contemporary populations are threatened by habitat loss (ecological vulnerability) and a lack of adaptive potential (evolutionary vulnerability). Technical advances provide new opportunities to address these challenges in biological conservation: Future habitat shifts can be predicted by ecological niche modelling and adaptive genetic diversity can be discerned using genome sequence data. Together, these two approaches illuminate the local adaptation profile and help identify the environmental and genomic conditions that should maximize evolutionary fitness. Materials and Methods Here, we reviewed the primary literature to identify key studies that utilize both whole‐genome resequencing (WGR) and ecological niche modelling (ENM) in an effort to envisage future research directions that may benefit conservation efforts. Results We identified ways to integrate different approaches, such as ENM‐informed adaptive genomics and adaptive genomics‐informed ENMs, that can be used to delineate and conserve local adaptation profiles. Discussion Integrative approaches can identify adaptive characteristics, vulnerable populations subject to environmental changes, and the patterns of local adaptation from geographic and genomic analyses. We discuss future research directions, limitations and their potential solutions with suggestions for collaborative workflows. Conclusion The integration of WGR and ENM is promising with their continuous advancement. An integrative approach can be used to evaluate eco‐evolutionary attributes, at both organismal and molecular levels, that can be used to help conserve local adaptation profiles.