References
Ahuja, M. R., & Neale, D. B. (2005). Evolution of Genome Size in
Conifers. Silvae Genetica , 54 (1-6), 126-137.
https://doi.org/doi:10.1515/sg-2005-0020
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J.
(1990). Basic local alignment search tool. J Molecular Biology ,215 (3), 403-410.
https://doi.org/10.1016/s0022-2836(05)80360-2
Blanco-Pastor, J. L., Barre, P., Keep, T., Ledauphin, T.,
Escobar-Gutierrez, A., Roschanski, A. M., Willner, E., Dehmer, K. J.,
Hegarty, M., Muylle, H., Veeckman, E., Vandepoele, K., Ruttink, T.,
Roldan-Ruiz, I., Manel, S., & Sampoux, J. P. (2021). Canonical
correlations reveal adaptive loci and phenotypic responses to climate in
perennial ryegrass. Molecular Ecology Resourses , 21 (3),
849-870. https://doi.org/10.1111/1755-0998.13289
Brodribb, T. J., McAdam, S. A. M., Jordan, G. J., & Martins, S. C. V.
(2014). Conifer species adapt to low-rainfall climates by following one
of two divergent pathways. Proceedings of the National Academy of
Sciences , 111 (40), 14489-14493.
https://doi.org/doi:10.1073/pnas.1407930111
Byrne, T., Farrelly, N., Kelleher, C., Hodkinson, T., Byrne, S., &
Barth, S. (2022). Genetic Diversity and Structure of a Diverse
Population of Picea sitchensis Using Genotyping-by-Sequencing.Forests , 13 (9), 1511.
https://www.mdpi.com/1999-4907/13/9/1511
Casola, C. (2019). Resequencing of massive pine genomes helps to unlock
the genetic underpinning of quantitative traits in conifer trees.New Phytologist , 221 (4), 1669-1671.
https://doi.org/10.1111/nph.15655
Chang, C. Y., Brautigam, K., Huner, N. P. A., & Ensminger, I. (2021).
Champions of winter survival: cold acclimation and molecular regulation
of cold hardiness in evergreen conifers. New Phytologist ,229 (2), 675-691. https://doi.org/10.1111/nph.16904
Chen, Z.-Q., Zan, Y., Milesi, P., Zhou, L., Chen, J., Li, L., Cui, B.,
Niu, S., Westin, J., Karlsson, B., García-Gil, M. R., Lascoux, M., &
Wu, H. X. (2021). Leveraging breeding programs and genomic data in
Norway spruce (Picea abies L. Karst) for GWAS analysis. Genome
Biology , 22 (1), 179.
https://doi.org/10.1186/s13059-021-02392-1
Christoforou, A., Dondrup, M., Mattingsdal, M., Mattheisen, M.,
Giddaluru, S., Nöthen, M. M., Rietschel, M., Cichon, S., Djurovic, S.,
Andreassen, O. A., Jonassen, I., Steen, V. M., Puntervoll, P., & Le
Hellard, S. (2012). Linkage-disequilibrium-based binning affects the
interpretation of GWASs. Am J Hum Genet , 90 (4), 727-733.
https://doi.org/10.1016/j.ajhg.2012.02.025
Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V.,
Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M.,
& Li, H. (2021). Twelve years of SAMtools and BCFtools.Gigascience , 10 (2).
https://doi.org/10.1093/gigascience/giab008
De La Torre, A. R., Wilhite, B., & Neale, D. B. (2019). Environmental
Genome-Wide Association Reveals Climate Adaptation Is Shaped by Subtle
to Moderate Allele Frequency Shifts in Loblolly Pine. Genome
Biology Evolution , 11 (10), 2976-2989.
https://doi.org/10.1093/gbe/evz220
Du, H., Ran, J.-H., Feng, Y.-Y., & Wang, X.-Q. (2020). The flattened
and needlelike leaves of the pine family (Pinaceae) share a conserved
genetic network for adaxial-abaxial polarity but have diverged for
photosynthetic adaptation. BMC Evolutionary Biology ,20 (1), 131. https://doi.org/10.1186/s12862-020-01694-5
Elshire, R. J., Glaubitz, J. C., Sun, Q., Poland, J. A., Kawamoto, K.,
Buckler, E. S., & Mitchell, S. E. (2011). A robust, simple
genotyping-by-sequencing (GBS) approach for high diversity species.PLoS One , 6 (5), e19379.
https://doi.org/10.1371/journal.pone.0019379
Farjon, A. (2010). A Handbook of the World’s Conifers . Brill.
https://doi.org/https://doi.org/10.1163/9789047430629
Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: new 1-km spatial
resolution climate surfaces for global land areas. International
Journal of Climatology , 37 (12), 4302-4315.
https://doi.org/https://doi.org/10.1002/joc.5086
Gagalova, K. K., Warren, R. L., Coombe, L., Wong, J., Nip, K. M., Yuen,
M. M. S., Whitehill, J. G. A., Celedon, J. M., Ritland, C., Taylor, G.
A., Cheng, D., Plettner, P., Hammond, S. A., Mohamadi, H., Zhao, Y.,
Moore, R. A., Mungall, A. J., Boyle, B., Laroche, J., . . . Birol, I.
(2022). Spruce giga-genomes: structurally similar yet distinctive with
differentially expanding gene families and rapidly evolving genes.Plant J , 111 (5), 1469-1485.
https://doi.org/10.1111/tpj.15889
Gapare, W. J., Aitken, S. N., & Ritland, C. E. (2005). Genetic
diversity of core and peripheral Sitka spruce (Picea sitchensis (Bong.)
Carr) populations: implications for conservation of widespread species.Biological Conservation , 123 (1), 113-123.
https://doi.org/10.1016/j.biocon.2004.11.002
GFDRR. (2022). WF-GLOBAL-CSIRO-30 .
https://www.geonode-gfdrrlab.org/layers/hazard:csiro_wf_max_fwi_rp30#more
Gu, Z., Eils, R., & Schlesner, M. (2016). Complex heatmaps reveal
patterns and correlations in multidimensional genomic data.Bioinformatics , 32 (18), 2847-2849.
https://doi.org/10.1093/bioinformatics/btw313
Günther, T., & Coop, G. (2013). Robust identification of local
adaptation from allele frequencies. Genetics , 195 (1),
205-220. https://doi.org/10.1534/genetics.113.152462
Hall, D. K., Riggs, G. A., & Salomonson, V. V. (2006).MODIS/Terra Snow Cover 5-Min L2 Swath 500m. Version 5).
https://doi.org/http://dx.doi.org/10.5067/ACYTYZB9BEOS.
Hiraoka, Y., Fukatsu, E., Mishima, K., Hirao, T., Teshima, K. M.,
Tamura, M., Tsubomura, M., Iki, T., Kurita, M., Takahashi, M., &
Watanabe, A. (2018). Potential of Genome-Wide Studies in Unrelated Plus
Trees of a Coniferous Species, Cryptomeria japonica (Japanese Cedar).Frontiers Plant Science , 9 , 1322.
https://doi.org/10.3389/fpls.2018.01322
Hornoy, B., Pavy, N., Gerardi, S., Beaulieu, J., & Bousquet, J. (2015).
Genetic Adaptation to Climate in White Spruce Involves Small to Moderate
Allele Frequency Shifts in Functionally Diverse Genes. Genome
Biology Evolution , 7 (12), 3269-3285.
https://doi.org/10.1093/gbe/evv218
Jurgiel, B. (2020). Point sampling tool . Retrieved 07/09/2022
from https://github.com/borysiasty/pointsamplingtool
Li, H., & Durbin, R. (2009). Fast and accurate short read alignment
with Burrows-Wheeler transform. Bioinformatics , 25 (14),
1754-1760. https://doi.org/10.1093/bioinformatics/btp324
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N.,
Marth, G., Abecasis, G., Durbin, R., & Genome Project Data Processing,
S. (2009). The Sequence Alignment/Map format and SAMtools.Bioinformatics , 25 (16), 2078-2079.
https://doi.org/10.1093/bioinformatics/btp352
Liu, S., Y. Wei, W.M. Post, R.B. Cook, K. Schaefer, & Thornton., M. M.
(2014). NACP MsTMIP: Unified North American Soil Map .
https://doi.org/https://doi.org/10.3334/ORNLDAAC/1242
Liu, X., Huang, M., Fan, B., Buckler, E. S., & Zhang, Z. (2016).
Iterative Usage of Fixed and Random Effect Models for Powerful and
Efficient Genome-Wide Association Studies. PLoS Genetics ,12 (2), e1005767.
https://doi.org/10.1371/journal.pgen.1005767
Lotterhos, K. E., Yeaman, S., Degner, J., Aitken, S., & Hodgins, K. A.
(2018). Modularity of genes involved in local adaptation to climate
despite physical linkage. Genome Biology , 19 (1), 157.
https://doi.org/10.1186/s13059-018-1545-7
Mimura, M., & Aitken, S. N. (2010). Local adaptation at the range
peripheries of Sitka spruce. J Evolutionary Biology ,23 (2), 249-258.
https://doi.org/10.1111/j.1420-9101.2009.01910.x
Pavy, N., Namroud, M. C., Gagnon, F., Isabel, N., & Bousquet, J.
(2012). The heterogeneous levels of linkage disequilibrium in white
spruce genes and comparative analysis with other conifers.Heredity (Edinb) , 108 (3), 273-284.
https://doi.org/10.1038/hdy.2011.72
Prunier, J., Verta, J. P., & MacKay, J. J. (2016). Conifer genomics and
adaptation: at the crossroads of genetic diversity and genome function.New Phytologist , 209 (1), 44-62.
https://doi.org/10.1111/nph.13565
QGIS.org. (2022). QGIS Geographic Information System . In QGIS
Association. http://www.qgis.org
Sebastian-Azcona, J., Hacke, U. G., & Hamann, A. (2018). Adaptations of
white spruce to climate: strong intraspecific differences in cold
hardiness linked to survival. Ecology Evolution , 8 (3),
1758-1768. https://doi.org/10.1002/ece3.3796
Senser, M., & Beck, E. (1984). Correlation of chloroplast
ultrastructure and membrane lipid composition to the different degrees
of frost resistance achieved in leaves of spinach, ivy, and spruce.J Plant Physiology , 117 (1), 41-55.
https://doi.org/10.1016/S0176-1617(84)80015-2
South, S. (2022). rnaturalearth: World Map Data from Natural
Earth. . https://github.com/ropensci/rnaturalearth.
Strand, M., Löfvenius, M. O., Bergsten, U., Lundmark, T., & Rosvall, O.
(2006). Height growth of planted conifer seedlings in relation to solar
radiation and position in Scots pine shelterwood. Forest Ecology
and Management , 224 (3), 258-265.
https://doi.org/https://doi.org/10.1016/j.foreco.2005.12.038
Sype, H. R.-A., B. (1990). Genetic variability of Sitka spruce of
the IUFRO collection Quebec, Canada.
Teskey, R., Wertin, T., Bauweraerts, I., Ameye, M., McGuire, M. A., &
Steppe, K. (2015). Responses of tree species to heat waves and extreme
heat events. Plant Cell Environ , 38 (9), 1699-1712.
https://doi.org/10.1111/pce.12417
Uddenberg, D., Akhter, S., Ramachandran, P., Sundström, J. F., &
Carlsbecker, A. (2015). Sequenced genomes and rapidly emerging
technologies pave the way for conifer evolutionary developmental
biology. Frontiers Plant Science , 6 , 970.
https://doi.org/10.3389/fpls.2015.00970
Wang, J., & Zhang, Z. (2021). GAPIT Version 3: Boosting Power and
Accuracy for Genomic Association and Prediction. Genomics,
Proteomics & Bioinformatics , 19 (4), 629-640.
https://doi.org/https://doi.org/10.1016/j.gpb.2021.08.005