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.