Dissecting genotype-environment relationships with functional implications for parental selection in <i>Cannabis</i> breeding

As climate variability continues to impact agricultural systems, identifying genetic factors that contribute to environmental adaptation will be essential for optimizing breeding strategies for the development of climate-resilient varieties. Through human cultivation and naturalization, Cannabis sativa has dispersed globally, adapting to a range of environmental conditions across various climates and latitudes. We combined raw data from multiple public sources to conduct an environmental genomic selection (EGS) analysis on 149 C. sativa samples to assess how different populations of Cannabis relate to their environmental conditions. Exploring genomic estimated adaptive values (GEAVs) across bioclimatic variables can facilitate the selection of parental material adapted for a specific condition. We further explore potential mechanisms of local adaptation by characterizing the individual marker effects that underlie these GEAV scores. To facilitate interpretation, we used previously described genetic groupings (basal, hemp-type, drug-type feral, and drug-type). Distinct patterns emerged across population groups with the drug-type (type I) group showing consistently narrow GEAV ranges, whereas the drug-type feral group showed a broader distribution, often having high GEAVs for precipitation variables. A key climate variable difference was seen in monthly average values, revealing a seasonal response to precipitation in drug-type feral samples. By examining monthly differences in marker effects associated with precipitation, we identify potential genomic mechanisms underlying seasonal environmental responses in drug-type feral samples. As these samples are sourced from geographic regions that have seasonal monsoons, they may have traits conferring flood tolerance (waterlogging) that could be introgressed into other backgrounds. The basal group also exhibited broad GEAV ranges across several bioclimatic traits, indicating they may be a valuable genetic resource for introgression to enhance environmental resilience. These findings underscore the importance of incorporating diverse germplasm into breeding programs to improve Cannabis resilience to changing environmental conditions. EGS provides a fast method to enable climate-conscious parental selection while gaining mechanistic information. Ultimately, we hope that such a strategy could support the development of climate-resilient Cannabis varieties tailored to both current and future environmental challenges.