Introduction
Low linkage disequilibrium (LD) is characteristic of conifer genomes and the independence of genes contributes to the adaptation patterns seen in conifers (Prunier et al., 2016). Angiosperms may undergo allopatric speciation by adaptation leading to reproductive isolation, however, conifers are less likely to do this due to low LD and large genome size (Ahuja & Neale, 2005; Pavy et al., 2012). For this reason, local adaptation to host environments is quite common in conifers with many alleles with small effects driving the adaptation (De La Torre et al., 2019; Hornoy et al., 2015). In Picea sitchensis (Bong.) Carr. (Sitka spruce) this has been demonstrated using phenotype data where bud set timing was adaptive to local climate types (Mimura & Aitken, 2010). In Loblolly pine, Pinus taeda L., climate adaptation at a local level is due to these subtle changes in the frequency of alleles of moderate/small effect (De La Torre et al., 2019) and in Lodgepole pine,Pinus contortus Douglas, climactic adaptations have been shown to be characterised by a slow rate of recombination (Lotterhos et al., 2018). Conifer is generally slow and characterised by low changes in frequency of many alleles, which is likely to affect the diversity of local adaptations found in these types of conifer studies. The long lifecycle of conifers results in low recombination cycles, contributing to slow adaptation.
Evergreen conifers have multiple mechanisms to survive colder harsh winter environments (Chang et al., 2021; Senser & Beck, 1984). Low temperatures can reduce the rate of enzymatic activity, disrupt metabolic processes and inhibit protein repair systems (Chang et al., 2021). To overcome this, some conifers have developed cold hardiness, which can stabilise and change membrane lipid composition which function to reduce the build-up of ice crystals in extracellular spaces (Chang et al., 2021; Senser & Beck, 1984). Cold hardiness is reported in some white spruce populations, a close relative of Sitka spruce (Sebastian-Azcona et al., 2018). Growth cessation during colder periods is an adaptation linked to shorter diurnal ranges. This is seen in Sitka spruce with delayed bud set due to wintering suggesting growth cessation in buds (Mimura & Aitken, 2010).
Low water stress, heat stress and solar radiation all combine to create drought stress. Thus, drought stress is a complex environmental stressor which requires a suite of differing adaptations (Brodribb et al., 2014). Conifers exhibit two diverging pathways to adapt to low water stress, one involves raised levels of abscisic acid (ABA) to close stomata and another method involves leaf desiccation (Teskey et al., 2015). Transpiration cooling is important for heat stress however, but stomatal closure can increase the severity of heat stress (Teskey et al., 2015). It is known that reductions in total seasonal solar radiation correlate to a reduction in tree height, so generally it is not considered a stressor on its own unless it exacerbates drought stress through evapotranspiration (Strand et al., 2006).
Sitka spruce occupies a large number of geographic and climatic niches along the Pacific Northwest of North America. This large gradient in environments requires specific local adaptations across the population (Gapare et al., 2005). The IUFRO (International Union of Forest Research Organisations) population was established in 1968 and 1970 by Matthews and Fletcher, representing the natural range of Sitka, collected at intervals of 50km and representing >80 provenances. (Sype, 1990). The collection includes samples over 3000 km in extent from Alaska to California. Elevation ranges from sea level to 671m, and an maximum distance from coast of 164m. Annual precipitation ranges from 4015 mm to 621 mm (Fick & Hijmans, 2017). Mean annual temperature ranges from -7.3°C to 17.4°C (Fick & Hijmans, 2017). Mean diurnal range is 10.8hrs to 4.43hrs per day (Fick & Hijmans, 2017). This highlights the range of environments present in this data set making it key for the study of local adaptation in conifers. This diverse and large range of environments likely leads to adaptations at the local level driven by shifts in allele frequencies, a common pattern in conifers (De La Torre et al., 2019). To discover the genetic bases of these adaptations, a number of methods have been developed. Genome wide association studies take trait data and genotype data and associated molecular markers with a trait (Casola, 2019; Chen et al., 2021; Hiraoka et al., 2018). This is useful for the discovery of the molecular function of traits or for the identification of molecular markers for the deployment in selection programs as has been done in Picea abies (L.) H. Karst. (Chen et al., 2021). Similar techniques can be used to associate genes with an environment using genotype-environment association. In conifers, trait association has been completed in Lodgepole pine and Loblolly pine by associating climactic variables with loci, elucidating mechanisms of adaptation (De La Torre et al., 2019; Lotterhos et al., 2018). The ability to associate genotype, phenotype and environment is important in these studies, as it indicates a pathway towards adaptation. While not previously undertaken in conifers, Canonical correlation analysis (CANCOR) has allowed for the discovery of loci that correlate with phenotypic growth due to environmental conditions in the forage grassLolium perenne (Blanco-Pastor et al., 2021) (also outbreeding and wind pollinated). This analysis merges data to discover loci responsible for improved phenotypes for the environment, which is key for breeders.
In this chapter we utilised data from a diverse collection of Sitka spruce, available in an arboretum collection in Ireland, representing the entire natural range of the species. This collection consists of 80 provenances with roughly 15 trees per provenance. In total 1177 genotypes were available for the study. Here we have utilised GEA, GWAS and CANCOR to discover loci responsible for specific traits and adaptations. We implemented CANCOR analysis to see the phenotypic effects of environments on genotypes. These loci can then be traced through populations, elucidating the driving forces of adaptation in Sitka spruce.