2016
DOI: 10.1111/mec.13525
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Exploring natural variation ofPinus pinasterAiton using metabolomics: Is it possible to identify the region of origin of a pine from its metabolites?

Abstract: Natural variation of the metabolome of Pinus pinaster was studied to improve understanding of its role in the adaptation process and phenotypic diversity. The metabolomes of needles and the apical and basal section of buds were analysed in ten provenances of P. pinaster, selected from France, Spain and Morocco, grown in a common garden for 5 years. The employment of complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) together with bioinformatics tools allowed the reliable quantification of 24… Show more

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Cited by 59 publications
(61 citation statements)
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“…pinaster provenances. These provenances were distinguishable essentially through secondary metabolism and defined two major groups: Atlantic and Mediterranean . A similar study correlated the variability in EO composition of P .…”
Section: Resultsmentioning
confidence: 64%
See 1 more Smart Citation
“…pinaster provenances. These provenances were distinguishable essentially through secondary metabolism and defined two major groups: Atlantic and Mediterranean . A similar study correlated the variability in EO composition of P .…”
Section: Resultsmentioning
confidence: 64%
“…therein), including the one here reported. A more recent study from Meijón et al . addressed the natural variation occurring in P .…”
Section: Resultsmentioning
confidence: 99%
“…In a second example, multigenerational lines inbred from different Drosophila melanogaster populations were found to remain distinguishable in general lipid composition, and approximately one‐fifth of the lipid compounds had clear concentration differences between male and female genotypes (Scheitz, Guo, Early, Harshman, & Clark, 2013). More recent studies of environmental and bud–leaf metabolome analyses of Pinus pinaster (ten European provenances in common garden) revealed two groups of individuals corresponding to spatially distinct regions (Meijón et al., 2016). All these studies used distance measures based on a reduced dimensionality of abundance differences for targeted compounds instead of explicitly calculating and comparing diversity indices (Appendix S1), which account for both chemical compounds’ presence–absence and relative abundances within each sample.…”
Section: Introductionmentioning
confidence: 99%
“…In forest tree research, LC-MS instruments have also been used for untargeted secondary metabolite profiling and phytohormone quantification studies. The focus of these studies was related with abiotic stress responses [19][20][21][22][23][24]67,88,89]; and to a smaller extent to biotic stress responses [90,91] and plant growth and developmental processes [77,92,93].…”
Section: Lc-ms Metabolite Profilingmentioning
confidence: 99%
“…In these cases, the chloroform:methanol:water two-phase solvent system is used, and the polar phase is evaporated to dryness and used for both GC-MS (after derivatization) and LC-MS metabolite profiling (after reconstitution in methanol:water) [21,77,88,89]. To take full advantage of the chloroform:methanol:water two-phase solvent system, the non-polar metabolites (lipophilic fraction) are analyzed by GC-MS after derivatization, for example, with tertmethyl-butyl-ether (MTBE) and trimethylsulfoniumhydroxide (TMSH) [23,92].…”
Section: Lc-ms Metabolite Profilingmentioning
confidence: 99%