Unraveling the early molecular and physiological mechanisms involved in response to phenanthrene exposure.

BACKGROUND: Higher plants have to cope with increasing concentrations of pollutants of both natural and anthropogenic origin. Given their capacity to concentrate and metabolize various compounds including pollutants, plants can be used to treat environmental problems - a process called phytoremediation. However, the molecular mechanisms underlying the stabilization, the extraction, the accumulation and partial or complete degradation of pollutants by plants remain poorly understood. RESULTS: Here, we determined the molecular events involved in the early plant response to phenanthrene, used as a model of polycyclic aromatic hydrocarbons. A transcriptomic and a metabolic analysis strongly suggest that energy availability is the crucial limiting factor leading to high and rapid transcriptional reprogramming that can ultimately lead to death. We show that the accumulation of phenanthrene in leaves inhibits electron transfer and photosynthesis within a few minutes, probably disrupting energy transformation. CONCLUSION: This kinetic analysis improved the resolution of the transcriptome in the initial plant response to phenanthrene, identifying genes that are involved in primary processes set up to sense and detoxify this pollutant but also in molecular mechanisms used by the plant to cope with such harmful stress. The identification of first events involved in plant response to phenanthrene is a key step in the selection of candidates for further functional characterization, with the prospect of engineering efficient ecological detoxification systems for polycyclic aromatic hydrocarbons.

Genetics and epigenetics of Pinus nigra populations with differential exposure to air pollution.

Forest species in the course of their evolution have experienced several environmental challenges, which since historic times include anthropogenic pollution. The effects of pollution on the genetic and epigenetic diversity in black pine (Pinus nigra) forests were investigated in the Amyntaio - Ptolemais - Kozani Basin, which has been for decades the largest lignite mining and burning center of Greece, with a total installed generating capacity of about 4.5 GW, operating for more than 70 years and resulting in large amounts of primary air pollutant emissions, mainly SO2, NOx and PM10. P. nigra, a biomarker for air pollution and a keystone species of affected natural ecosystems, was examined in terms of phenology (cone and seed parameters), genetics (283 AFLP loci) and epigenetics (606 MSAP epiloci), using two populations (exposed to pollution and control) of the current (mature trees) and future (embryos) stand. It was found that cone, seed, as well as genetic diversity parameters, did not show statistically significant differences between the exposed population and the control. Nevertheless, statistically significant differences were detected at the population epigenetic level. Moreover, there was a further differentiation regarding the intergenerational comparison: while the epigenetic diversity does not substantially change in the two generations assessed in the control population, epigenetic diversity is significantly higher in the embryo population compared to the parental stand in the exposed population. This study sheds a light to genome dynamics in a forest tree population exposed to long term atmospheric pollution burden and stresses the importance of assessing both genetics and epigenetics in biomonitoring applications.

The GenTree Platform: growth traits and tree-level environmental data in 12 European forest tree species.

BACKGROUND: Progress in the field of evolutionary forest ecology has been hampered by the huge challenge of phenotyping trees across their ranges in their natural environments, and the limitation in high-resolution environmental information. FINDINGS: The GenTree Platform contains phenotypic and environmental data from 4,959 trees from 12 ecologically and economically important European forest tree species: Abies alba Mill. (silver fir), Betula pendula Roth. (silver birch), Fagus sylvatica L. (European beech), Picea abies (L.) H. Karst (Norway spruce), Pinus cembra L. (Swiss stone pine), Pinus halepensis Mill. (Aleppo pine), Pinus nigra Arnold (European black pine), Pinus pinaster Aiton (maritime pine), Pinus sylvestris L. (Scots pine), Populus nigra L. (European black poplar), Taxus baccata L. (English yew), and Quercus petraea (Matt.) Liebl. (sessile oak). Phenotypic (height, diameter at breast height, crown size, bark thickness, biomass, straightness, forking, branch angle, fructification), regeneration, environmental in situ measurements (soil depth, vegetation cover, competition indices), and environmental modeling data extracted by using bilinear interpolation accounting for surrounding conditions of each tree (precipitation, temperature, insolation, drought indices) were obtained from trees in 194 sites covering the species' geographic ranges and reflecting local environmental gradients. CONCLUSION: The GenTree Platform is a new resource for investigating ecological and evolutionary processes in forest trees. The coherent phenotyping and environmental characterization across 12 species in their European ranges allow for a wide range of analyses from forest ecologists, conservationists, and macro-ecologists. Also, the data here presented can be linked to the GenTree Dendroecological collection, the GenTree Leaf Trait collection, and the GenTree Genomic collection presented elsewhere, which together build the largest evolutionary forest ecology data collection available.

Author Correction: The GenTree Dendroecological Collection, tree-ring and wood density data from seven tree species across Europe.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The GenTree Dendroecological Collection, tree-ring and wood density data from seven tree species across Europe.

The dataset presented here was collected by the GenTree project (EU-Horizon 2020), which aims to improve the use of forest genetic resources across Europe by better understanding how trees adapt to their local environment. This dataset of individual tree-core characteristics including ring-width series and whole-core wood density was collected for seven ecologically and economically important European tree species: silver birch (Betula pendula), European beech (Fagus sylvatica), Norway spruce (Picea abies), European black poplar (Populus nigra), maritime pine (Pinus pinaster), Scots pine (Pinus sylvestris), and sessile oak (Quercus petraea). Tree-ring width measurements were obtained from 3600 trees in 142 populations and whole-core wood density was measured for 3098 trees in 125 populations. This dataset covers most of the geographical and climatic range occupied by the selected species. The potential use of it will be highly valuable for assessing ecological and evolutionary responses to environmental conditions as well as for model development and parameterization, to predict adaptability under climate change scenarios.