Drone-based physiological index reveals long-term acclimation and drought stress responses in trees.

Monitoring early tree physiological responses to drought is key to understanding progressive impacts of drought on forests and identifying resilient species. We combined drone-based multispectral remote sensing with measurements of tree physiology and environmental parameters over two growing seasons in a 100-y-old Pinus sylvestris forest subject to 17-y of precipitation manipulation. Our goal was to determine if drone-based photochemical reflectance index (PRI) captures tree drought stress responses and whether responses are affected by long-term acclimation. PRI detects changes in xanthophyll cycle pigment dynamics, which reflect increases in photoprotective non-photochemical quenching activity resulting from drought-induced photosynthesis downregulation. Here, PRI of never-irrigated trees was up to 10 times lower (higher stress) than PRI of irrigated trees. Long-term acclimation to experimental treatment, however, influenced the seasonal relationship between PRI and soil water availability. PRI also captured diurnal decreases in photochemical efficiency, driven by vapour pressure deficit. Interestingly, 5 years after irrigation was stopped for a subset of the irrigated trees, a positive legacy effect persisted, with lower stress responses (higher PRI) compared with never-irrigated trees. This study demonstrates the ability of remotely sensed PRI to scale tree physiological responses to an entire forest and the importance of long-term acclimation in determining current drought stress responses.

Evidence that tolerance of Eutrema salsugineum to low phosphate conditions is hard-wired by constitutive metabolic and root-associated adaptations.

MAIN CONCLUSION: The extremophyte Eutrema salsugineum (Yukon ecotype) has adapted to an environment low in available phosphate through metabolic and root-associated traits that enables it to efficiently retrieve, use, and recycle phosphorus. Efficient phosphate (Pi) use by plants would increase crop productivity under Pi-limiting conditions and reduce our reliance on Pi applied as fertilizer. An ecotype of Eutrema salsugineum originating from the Yukon, Canada, shows no evidence of decreased relative growth rate or biomass under low Pi conditions and, as such, offers a promising model for identifying mechanisms to improve Pi use by crops. We evaluated traits associated with efficient Pi use by Eutrema (Yukon ecotype) seedlings and 4-week-old plants, including acquisition, remobilization, and the operation of metabolic bypasses. Relative to Arabidopsis, Eutrema was slower to remobilize phosphorus (P) from senescing leaves, primary and lateral roots showed a lower capacity for rhizosphere acidification, and root acid phosphatase activity was more broadly distributed and not Pi responsive. Both species produced long root hairs on low Pi media, whereas Arabidopsis root hairs were well endowed with phosphatase activity. This capacity was largely absent in Eutrema. In contrast to Arabidopsis, maximal in vitro rates of pyrophosphate-dependent phosphofructokinase and phosphoenolpyruvate carboxylase activities were not responsive to low Pi conditions suggesting that Eutrema has a constitutive and likely preferential capacity to use glycolytic bypass enzymes. Rhizosphere acidification, exudation of acid phosphatases, and rapid remobilization of leaf P are unlikely strategies used by Eutrema for coping with low Pi. Rather, equipping an entire root system for Pi acquisition and utilizing a metabolic strategy suited to deficient Pi conditions offer better explanations for how Eutrema has adapted to thrive on alkaline, highly saline soil that is naturally low in available Pi.

Acclimation of the crucifer Eutrema salsugineum to phosphate limitation is associated with constitutively high expression of phosphate-starvation genes.

Eutrema salsugineum, a halophytic relative of Arabidopsis thaliana, was subjected to varying phosphate (Pi) treatments. Arabidopsis seedlings grown on 0.05 mm Pi displayed shortened primary roots, higher lateral root density and reduced shoot biomass allocation relative to those on 0.5 mm Pi, whereas Eutrema seedlings showed no difference in lateral root density and shoot biomass allocation. While a low Fe concentration mitigated the Pi deficiency response for Arabidopsis, Eutrema root architecture was unaltered, but adding NaCl increased Eutrema lateral root density almost 2-fold. Eutrema and Arabidopsis plants grown on soil without added Pi for 4 weeks had low shoot and root Pi content. Pi-deprived, soil-grown Arabidopsis plants were stunted with senescing older leaves, whereas Eutrema plants were visually indistinguishable from 2.5 mm Pi-supplemented plants. Genes associated with Pi starvation were analysed by RT-qPCR. EsIPS2, EsPHT1;4 and EsPAP17 showed up-regulated expression in Pi-deprived Eutrema plants, while EsPHR1, EsWRKY75 and EsRNS1 showed no induction. Absolute quantification of transcripts indicated that PHR1, WRKY75 and RNS1 were expressed at higher levels in Eutrema plants relative to those in Arabidopsis regardless of external Pi. The low phenotypic plasticity Eutrema displays to Pi supply is consistent with adaptation to chronic Pi deprivation in its extreme natural habitat.

A long-read and short-read transcriptomics approach provides the first high-quality reference transcriptome and genome annotation for Pseudotsuga menziesii (Douglas-fir).

Douglas-fir (Pseudotsuga menziesii) is native to western North America. It grows in a wide range of environmental conditions and is an important timber tree. Although there are several studies on the gene expression responses of Douglas-fir to abiotic cues, the absence of high-quality transcriptome and genome data is a barrier to further investigation. Like for most conifers, the available transcriptome and genome reference dataset for Douglas-fir remains fragmented and requires refinement. We aimed to generate a highly accurate, and complete reference transcriptome and genome annotation. We deep-sequenced the transcriptome of Douglas-fir needles from seedlings that were grown under nonstress control conditions or a combination of heat and drought stress conditions using long-read (LR) and short-read (SR) sequencing platforms. We used 2 computational approaches, namely de novo and genome-guided LR transcriptome assembly. Using the LR de novo assembly, we identified 1.3X more high-quality transcripts, 1.85X more "complete" genes, and 2.7X more functionally annotated genes compared to the genome-guided assembly approach. We predicted 666 long noncoding RNAs and 12,778 unique protein-coding transcripts including 2,016 putative transcription factors. We leveraged the LR de novo assembled transcriptome with paired-end SR and a published single-end SR transcriptome to generate an improved genome annotation. This was conducted with BRAKER2 and refined based on functional annotation, repetitive content, and transcriptome alignment. This high-quality genome annotation has 51,419 unique gene models derived from 322,631 initial predictions. Overall, our informatics approach provides a new reference Douglas-fir transcriptome assembly and genome annotation with considerably improved completeness and functional annotation.