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Abstract Bark beetles and root weevils can impact forests through tree death on landscape scales. Recently, subterranean termites have been linked to these beetles via the presence of bluestain fungi (Ascomycota: Ophiostomataceae), which are vectored to trees by beetles. However, only a small subset of bluestain species have been examined. Here, we tested whether termite-bluestain association patterns in the field reflect termite feeding preference in laboratory choice trials. We documented the presence of four bluestain fungi (Leptographium procerum (W.B. Kendr.), L. terebrantis (Barras & Perry), Grosmannia huntii (Rob.-Jeffr.), and G. alacris (T.A. Duong, Z.W. de Beer & M.J. Wingf.) in the roots of 2,350 loblolly pine trees in the southeastern United States and whether termites were present or absent on these roots and paired this with laboratory choice feeding trials. Termites were found 2.5-fold on tree roots with at least one bluestain fungus present than tree roots without bluestain fungi. Although termites in this study and others were associated with L. procerum, L. terebrantis, and marginally G. huntii, termites only showed preferential feeding on wood inoculated with G. huntii in laboratory trials. This suggests that increased termite presence on wood with bluestain fungi may be driven by factors other than increased wood palatability. Termites could thus disproportionately affect wood turnover rates for specific pools (e.g., bark beetle and root weevil attacked trees) and in some cases (e.g., G. huntii) accelerate wood decomposition. This study supports the growing evidence that the association between subterranean termites and bluestain fungi is spatially and taxonomically widespread. 

In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 h to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. PAST has been implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately half an hour to one hour by processing data in parallel and produced the same results as the previously developed method. PAST has many user-specified options for maximum customization. Thus, to promote a powerful new pathway analysis methodology that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible, efficient, and user-friendly tool. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes.