A new guide to using landscape genomics analysis to enhance conservation and use of plant genetic resources
Climate change and environmental disturbances due to human activities are posing significant threats to biodiversity, which in turn, affects food security and social stability. Many species are undergoing range shifts and fitness declines, while others have developed adaptive traits to avoid extinction. When genetically controlled, these traits undergo natural selection, leading to the development of locally adapted populations, where specific alleles become prevalent due to their fitness advantage in specific environments. This has led to a growing research interest in landscape genomics, which combines landscape ecology and genomics to detect signatures of local adaptation.
Landscape genomics is particularly valuable for identifying the loci responsible for adaptive genetic variation across landscapes. The approach, though relatively new, has shown its feasibility in crop and animal species, revealing adaptive traits in species like wheat, maize, barley, sorghum, eggplant, goats, and chicken. Modeling genomic and environmental data has allowed researchers to predict crop fitness in future climates, benefiting conservation efforts and crop improvement programs. For example, studies have identified populations at risk of extinction, guiding ex-situ conservation and assisted gene flow strategies. Using landscape genomics to predict species’ genetic responses to climate gradients is helping shape conservation strategies to maintain biodiversity.
While landscape genomics holds promise, there are significant challenges, particularly the issue of false positives when identifying loci linked to local adaptation. False positives may arise when genetic drift or demographic effects mimic local adaptation patterns. Fortunately, continuous improvement of methods in environmental association analyses is helping to control for false positives. Moreover, distinguishing between correlated environmental factors remains challenging in landscape genomics studies, as some correlations may be due to covarying factors not included in the analysis. Despite these challenges, its potential to mine adaptive genes for crop improvement and to inform conservation strategies is vast.
This comprehensive manual provides valuable insights into the fundamental steps and critical considerations needed for undertaking successful landscape genomics studies. It includes a few commonly applied methods, but it is important to note that various techniques are available depending on capacity and proficiency. Study scenarios can vary widely, and the complexity of each can differ significantly depending on the studied organism and diverse landscapes involved. Links to additional detailed resources have also been provided to broaden users’ perspective.
In summary, landscape genomics is rapidly advancing with the ability to generate genomic datasets, even for non-model species. Enhanced environmental data, improved analysis methods, cost reduction, and ease of generating genomic data are expected to boost landscape genomic studies. These advancements will deepen our understanding of how specific genotypes adapt to their environments, both now and under future predicted conditions.
Omondi E, Lin Y-P, van Zonneveld M. 2024. A guide to using landscape genomics analysis to enhance conservation and use of plant genetic resources. Publication No. 25-1094. World Vegetable Center, Shanhua, Taiwan. 77pp.
Thanks to the Taiwan Ministry of Foreign Affairs for support through the Taiwan-Asia Vegetable Initiative (TAsVI) that made this manual possible. This project is implemented by the World Vegetable Center, in partnership with the Taiwan Agricultural Research Institute (TARI); Malaysia Agriculture Research and Development Institute (MARDI) Horticulture Research Centre; University of the Philippines Los Baños (UPLB) Institute of Plant Breeding, and Bureau of Plant Industries (BPI), the Philippines; Kasetsart University, Tropical Vegetable Research Center (TVRC), and Department of Agriculture Horticulture Research Institute , Thailand; and Vietnam Academy of Agricultural Sciences (VAAS) Plant Resource Center (PRC), and Fruit and Vegetable Research Institute (FAVRI), Vietnam.
The genomic data used in this manual has been developed under the G2P-SOL project: Linking genetic resources, genomes, and phenotypes of Solanaceous crops. This work has been funded by the European Union under the grant agreements n. 677379 (Linking genetic resources, genomes, and phenotypes of Solanaceous crops (G2P-SOL)) and n. 101094738 (Promoting a Plant Genetic Resource Community for Europe, PRO-GRACE). We would like to acknowledge the G2P-SOL collaborators that contributed to the generation of this data. We thank the authors and instructors of different online resources and courses listed in the link to other useful resources below. The insights received from these resources have made the demonstration and interpretation of the results easy in some of the steps through this manual.
