Cryptic genetic variation and adaptation to waterlogging in Caledonian Scots pine, Pinus sylvestris L

Does the definition of a novel environment affect the ability to detect cryptic genetic variation?

Anthropogenic change exposes populations to environments that have been rare or entirely absent from their evolutionary past. Such novel environments are hypothesized to release cryptic genetic variation, a hidden store of variance that can fuel evolution. However, support for this hypothesis is mixed. One possible reason is a lack of clarity in what is meant by 'novel environment', an umbrella term encompassing conditions with potentially contrasting effects on the exposure or concealment of cryptic variation. Here, we use a meta-analysis approach to investigate changes in the total genetic variance of multivariate traits in ancestral versus novel environments. To determine whether the definition of a novel environment could explain the mixed support for a release of cryptic genetic variation, we compared absolute novel environments, those not represented in a population's evolutionary past, to extreme novel environments, those involving frequency or magnitude changes to environments present in a population's ancestry. Despite sufficient statistical power, we detected no broad-scale pattern of increased genetic variance in novel environments, and finding the type of novel environment did not explain any significant variation in effect sizes. When effect sizes were partitioned by experimental design, we found increased genetic variation in studies based on broad-sense measures of variance, and decreased variation in narrow-sense studies, in support of previous research. Therefore, the source of genetic variance, not the definition of a novel environment, was key to understanding environment-dependant genetic variation, highlighting non-additive genetic variance as an important component of cryptic genetic variation and avenue for future research.

Heritable genetic variation but no local adaptation in a pine-ectomycorrhizal interaction

Local adaptation of plants to mycorrhizal fungi helps determine the outcome of mycorrhizal interactions. However, there is comparatively little work exploring the potential for evolution in interactions with ectomycorrhizal fungi, and fewer studies have explored the heritability of mycorrhizal responsiveness, which is required for local adaptation to occur. We set up a reciprocal inoculation experiment using seedlings and soil from four populations of Scots pine (Pinus sylvestris) from Scotland, measuring seedling response to mycorrhizal inoculation after 4 months. We estimated heritability for the response traits and tested for genotype × environment interactions. While we found that ectomycorrhizal responsiveness was highly heritable, we found no evidence that pine populations were locally adapted to fungal communities. Instead, we found a complex suite of interactions between pine population and soil inoculum. Our results suggest that, while Scots pine has the potential to evolve in response to mycorrhizal fungi, evolution in Scotland has not resulted in local adaptation. Long generation times and potential for rapid shifts in fungal communities in response to environmental change may preclude the opportunity for such adaptation in this species, and selection for other factors such as resistance to fungal pathogens may explain the pattern of interactions found.

275 years of forestry meets genomics in Pinus sylvestris

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA-seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long-term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.