Investigating local adaptation in the wood-decay fungus Trichaptum abietinum through common garden experiments and population genomics

Abstract

Rapid climatic changes already affect ecosystems all over the globe. Trichaptum abietinum has a wide geographic distribution covering large climatic gradients, which could indicate adaptation to local environments in different populations or high phenotypic plasticity within the species. How well populations are able to adapt to the local environment could predict how the species distribution will react to an altered climate. In this study, the process of local adaptation has been investigated in the fungal wood decay species Trichaptum abietinum. Population genomic analyses coupled with common garden experiments have been used to investigate if different populations of T. abietinum have gone through adaptation to local climatic conditions, and to detect possible environmental drivers and genetic mechanisms that cause adaptation. Clear population structure and divergence were detected between eastern and western populations, albeit little divergence was found within these two groups of T. abietinum. A Redundancy Analysis proposed adaptation towards a wet and stable, coastal climate in western specimens, and possibly towards high temperatures in a southern population. Common garden experiments, measuring decay and hyphal extension rate, indicated static trends between populations at different temperatures. The observed divergence between eastern and western populations could be due to different immigration routes of T. abietinum, connected to two separate postglacial immigration histories of Picea abies. Another possibility is adaptation to the distinct conditions in eastern and western Norway. However, due to a clear population structure the results from the Redundancy Analysis performed could be misleading. Several genes, with known and unknown gene functions, was detected in areas of SNPs possibly under selection for high levels of precipitation and isothermality. Further studies, including additional sampling sites, larger sample sizes and more extensive genomic analysis, should be conducted to confirm the suggested patterns found in this study.