Kawecki, T. J. & Ebert, D. Conceptual issues in local adaptation. Ecol. Lett.7, 1225–1241 (2004).
Cushman, S. A. et al. Editorial: the least cost path from landscape genetics to landscape genomics: challenges and opportunities to explore NGS data in a spatially explicit context. Front. Genet.9, 215 (2018).
Pereira, A. Plant abiotic stress challenges from the changing environment. Front. Plant Sci.7, 1123 (2016).
Rellstab, C. et al. A practical guide to environmental association analysis in landscape genomics. Mol. Ecol.24, 4348–4370 (2015).
Zhu, J. K. Abiotic stress signaling and responses in plants. Cell167, 313–324 (2016).
Allendorf, F. W., Hohenlohe, P. A. & Luikart, G. Genomics and the future of conservation genetics. Nat. Rev. Genet.11, 697–709 (2010).
Radwan, J. & Babik, W. The genomics of adaptation. Proc. Biol. Sci.279, 5024–5028 (2012).
Li, Y. et al. Ten years of landscape genomics: challenges and opportunities. Front. Plant Sci.8, 2136 (2017).
Cushman, S. A. Grand challenges in evolutionary and population genetics: the importance of integrating epigenetics, genomics, modeling, and experimentation. Front. Genet.5, 197 (2014).
Guggisberg, A. et al. The genomic basis of adaptation to calcareous and siliceous soils in Arabidopsis lyrata. Mol. Ecol.27, 5088–5103 (2018).
Brennan, R. S. et al. Integrative population and physiological genomics reveals mechanisms of adaptation in killifish. Mol. Biol. Evol.35, 2639–2653 (2018).
Chen, C. et al. Population genomics provide insights into the evolution and adaptation of the eastern honey bee (Apis cerana). Mol. Biol. Evol.35, 2260–2271 (2018).
Dittberner, H. et al. Natural variation in stomata size contributes to the local adaptation of water-use efficiency in Arabidopsis thaliana. Mol. Ecol.27, 4052–4065 (2018).
Pfeifer, S. P. et al. The evolutionary history of Nebraska deer mice: local adaptation in the face of strong gene flow. Mol. Biol. Evol.35, 792–806 (2018).
Ahrens, C. W., Byrne, M. & Rymer, P. D. Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species. Mol. Ecol.28, 2502–2516 (2019).
Wright, S. Evolution in Mendelian populations. Genetics16, 97–159 (1931).
Miao, C. Y. et al. Landscape genomics reveal that ecological character determines adaptation: a case study in smoke tree (Cotinus coggygria Scop.). BMC Evol. Biol.17, 202 (2017).
Li, J. X. et al. Adaptive genetic differentiation in Pterocarya stenoptera (Juglandaceae) driven by multiple environmental variables were revealed by landscape genomics. BMC Plant Biol.18, 306 (2018).
Arciero, E. et al. Demographic history and genetic adaptation in the Himalayan region inferred from genome-wide SNP genotypes of 49 populations. Mol. Biol. Evol.35, 1916–1933 (2018).
Friis, G. et al. Genome-wide signals of drift and local adaptation during rapid lineage divergence in a songbird. Mol. Ecol.27, 746–760 (2018).
Fitzpatrick, M. C. & Keller, S. R. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecol. Lett.18, 1–16 (2015).
Guerrero, J. et al. Soil environment is a key driver of adaptation in Medicago truncatula: new insights from landscape genomics. N. Phytol.219, 378–390 (2018).
Keller, S. R. et al. Local adaptation in the flowering-time gene network of balsam poplar, Populus balsamifera L. Mol. Biol. Evol.29, 3143–3152 (2012).
Manel, S. et al. Genome assemblies, genomic resources and their influence on the detection of the signal of positive selection in genome scans. Mol. Ecol.25, 170–184 (2016).
Fu, Z. Z. et al. Molecular data and ecological niche modeling reveal population dynamics of widespread shrub Forsythia suspensa (Oleaceae) in China’s warm-temperate zone in response to climate change during the Pleistocene. BMC Evol. Biol.14, 114 (2014).
Hamrick, J. L. & Godt, M. J. Plant Population Genetics, Breeding, and Genetic Resources (Sinauer, Sunderland, 1990).
Hewitt, G. M. Genetic consequences of climatic oscillations in the quaternary. Philos. Trans. R. Soc. Lond. B Biol. Sci.359, 183–195 (2004).
Manel, S. & Holderegger, R. Ten years of landscape genetics. Trends Ecol. Evol.28, 614–621 (2013).
Balkenhol, N. et al. Current status, future opportunities, and remaining challenges in landscape genetics. In (eds Balkenhol, N. C., et al.). Landscape Genetics: Concepts, Methods, Applications (Wiley, Hoboken, 2015).
Yang, J. et al. Landscape population genomics of forsythia (Forsythia suspensa) reveal that ecological habitats determine the adaptive evolution of species. Front. Plant Sci.8, 481 (2017).
Sun, X. et al. SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS ONE8, e58700 (2013).
Sollars, E. S. A. et al. Genome sequence and genetic diversity of European ash trees. Nature541, 212–216 (2017).
Unver, T. et al. Genome of wild olive and the evolution of oil biosynthesis. Proc. Natl Acad. Sci. USA114, E9413–E9422 (2017).
Yang, X. et al. The chromosome-level quality genome provides insights into the evolution of the biosynthesis genes for aroma compounds of Osmanthus fragrans. Hortic. Res.5, 72 (2018).
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res.19, 1655–1664 (2009).
Wallander, E. & Albert, V. A. Phylogeny and classification of Oleaceae based on rps16 and trnL-F sequence data. Am. J. Bot.87, 1827–1841 (2000).
Wang, T. Q. et al. TCM treatment of anemopyretic cold rule analysis. J. Tianjin Univ. Tradit. Chin. Med.37, 113–117 (2018).
Fritsche, L. G. et al. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat. Genet.48, 134–143 (2016).
Najafi, S., Sorkheh, K. & Nasernakhaei, F. Characterization of the APETALA2/Ethylene-responsive factor (AP2/ERF) transcription factor family in sunflower. Sci. Rep.8, 11576 (2018).
Xie, Z. et al. AP2/ERF transcription factor regulatory networks in hormone and abiotic stress responses in Arabidopsis. Front. Plant Sci.10, 228 (2019).
Chakraborty, U. & Pradhan, B. Drought stress-induced oxidative stress and antioxidative responses in four wheat (Triticum aestivum L.) varieties. Arch. Agron. Soil Sci.58, 617–630 (2012).
Noureddine, Y. Changes of peroxidase activities under cold stress in annuals populations of medicago. Mol. Plant Breed.6, 5 (2015).
Gong, L. et al. Transcriptome profiling of the potato (Solanum tuberosum L.) plant under drought stress and water-stimulus conditions. PLoS ONE10, e0128041 (2015).
Wang, M. et al. Comparative transcriptome analysis to elucidate the enhanced thermotolerance of tea plants (Camellia sinensis) treated with exogenous calcium. Planta249, 775–786 (2019).
Schöttler, M. A. et al. Photosynthetic complex stoichiometry dynamics in higher plants: biogenesis, function, and turnover of ATP synthase and the cytochrome b6f complex. J. Exp. Bot.66, 2373–2400 (2015).
Collakova, E. & DellaPenna, D. The role of homogentisate phytyltransferase and other tocopherol pathway enzymes in the regulation of tocopherol synthesis during abiotic stress. Plant Physiol.133, 930–940 (2003).
Gavalas, N. A. & Clark, H. E. On the role of manganese in photosynthesis: kinetics of photoinhibition in manganese-deficent and 3-(4-chlorophenyl)-1, 1-dimethylurea-inhibited Euglena gracilis. Plant Physiol.47, 139–143 (1971).
Chen, C. Y. et al. Structural basis of jasmonate-amido synthetase FIN219 in complex with glutathione S-transferase FIP1 during the JA signal regulation. Proc. Natl Acad. Sci. USA114, E1815–E1824 (2017).
Nisar, N. et al. Carotenoid metabolism in plant. Mol. Plant8, 68–82 (2015).
Landguth, E. L. et al. Modeling multilocus selection in an individual-based, spatially-explicit landscape genetics framework. Mol. Ecol. Resour.20, 605–615 (2020).
Ram, S. Role of alcohol dehydrogenase, malate dehydrogenase and malic enzyme in flooding tolerance in Brachiaria Species. J. Plant Biochem. Biot.9, 45–47 (2000).
Butsayawarapat, P. et al. Comparative transcriptome analysis of waterlogging-sensitive and tolerant zombi pea (Vigna vexillata) reveals energy conservation and root plasticity controlling waterlogging tolerance. Plants8, 264 (2019).
Ohsawa, T. & Ide, Y. Global patterns of genetic variation in plant species along vertical and horizontal gradients on mountains. Glob. Ecol. Biogeogr.17, 152–163 (2008).
Yang, J. et al. Landscape genomics analysis of Achyranthes bidentata reveal adaptive genetic variations are driven by environmental variations relating to ecological habit. Popul. Ecol.59, 355–362 (2017).
Fu, Z. Z. et al. Population genetics of the widespread shrub Forsythia suspensa (Oleaceae) in warm-temperate China using microsatellite loci: implication for conservation. Plant Syst. Evol.302, 1–9 (2016).
Marcais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics27, 764–770 (2011).
Jain, M. et al. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat. Biotechnol.36, 338–345 (2018).
Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive κ-mer weighting and repeat separation. Genome Res.27, 722–736 (2017).
Chakraborty, M. et al. Contiguous and accurate de novo assembly of metazoan genomes with modest long read coverage. Nucleic Acids Res.44, e147 (2016).
Vaser, R. et al. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res.27, 737–746 (2017).
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE9, e112963 (2014).
Simão, F. A. et al. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics31, 3210 (2015).
Parra, G., Bradnam, K. & Korf, I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics23, 1061–1067 (2007).
Zhang, J. et al. High-density genetic map construction and identification of a locus controlling weeping trait in an ornamental woody plant (Prunus mume Sieb. et Zucc). DNA Res.22, 1–9 (2015).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics25, 1754–1760 (2009).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res.20, 1297–1303 (2010).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics25, 2078–2079 (2009).
Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet.38, 904–909 (2006).
Kumar, S. et al. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol. Biol. Evol.35, 1547–1549 (2018).
Excoffier, L. & Lischer, H. E. L. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour.10, 564–567 (2010).
Pickrell, J. K. & Pritchard, J. K. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet.8, e1002967 (2012).
Foll, M. & Gaggiotti, O. E. A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics180, 977–993 (2008).
Hijmans, R. J. et al. Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant Genet. Resour. Newsl.127, 15–19 (2001).
Frichot, E. et al. Testing for associations between loci and environmental gradients using latent factor mixed models. Mol. Biol. Evol.30, 1687–1699 (2013).
Joost, S. et al. A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation. Mol. Ecol.16, 3955–3969 (2007).
Stucki, S. et al. High performance computation of landscape genomic models including local indicators of spatial association. Mol. Ecol. Resour.17, 1072–1089 (2017).
Oksanen, J. et al. Vegan: Community Ecology Package. R. Package Version 2.4-5 (2017).
Altschul, S. F. et al. Basic local alignment search tool. J. Mol. Biol.215, 403–410 (1990).
Source: Ecology - nature.com