The Molecular Cloning and Expression Analysis of a CYP71 Gene in Ginkgo biloba L.

Cytochrome P450 monooxygenases (CYPs) are a group of redox proteins that catalyze various oxidative reactions in plant secondary metabolism. To explore the function of the CYP71 gene in Ginkgo biloba under biotic and abiotic stresses, a full-length CYP gene, designated GbCYP71, was first isolated and characterized from leaves of G. biloba. It contained a 1512-bp open reading frame (ORF) encoding 503 amino-acid-deduced polypeptide whose theoretical molecular weight was 56.9 kDa. The genomic DNA sequence of GbCYP71 contained two exons and one intron. The cDNA of GbCYP71 was subcloned in a pET-32a vector and then transformed into E. coli strain BL21 (DE3). A protein with a molecular weight of 76.4 kDa was subsequently identified and found to be consistent with the above theoretical value. Transient expression analysis revealed that the GbCYP71 protein may be located in the G. biloba cell cytoplasm. GbCYP71 was expressed in almost all ginkgo tissues, including leaves, stamens, gynoecia, stems and, preferentially, roots. Expression-profiling analyses revealed that GbCYP71 can be induced by salinity stress and phytohormone signals, including salicylic acid, abscisic acid, methyl jasmonate and ethephon, but is repressed by heat and cold stresses. These results indicate that GbCYP71 mainly functions in responding to biotic and abiotic stresses

Crop rotation and native microbiome inoculation restore soil capacity to suppress a root disease

14 páginas.- 5 figuras.- 58 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-023-43926-4.It is widely known that some soils have strong levels of disease suppression and prevent the establishment of pathogens in the rhizosphere of plants. However, what soils are better suppressing disease, and how management can help us to boost disease suppression remain unclear. Here, we used field, greenhouse and laboratory experiments to investigate the effect of management (monocropping and rotation) on the capacity of rhizosphere microbiomes in suppressing peanut root rot disease. Compared with crop rotations, monocropping resulted in microbial assemblies that were less effective in suppressing root rot diseases. Further, the depletion of key rhizosphere taxa in monocropping, which were at a disadvantage in the competition for limited exudates resources, reduced capacity to protect plants against pathogen invasion. However, the supplementation of depleted strains restored rhizosphere resistance to pathogen. Taken together, our findings highlight the role of native soil microbes in fighting disease and supporting plant health, and indicate the potential of using microbial inocula to regenerate the natural capacity of soil to fight disease. © 2023, The Author(s).This research was supported by the National Key Research and Development Program of China 2022YFD2201900 (Xi.L.), the National Natural Science Foundation of China 32122056, 42011045 (Xi.L.), and the earmarked fund for CARS-13 (X.W.). M.D-B. acknowledges support from TED2021-130908B-C41/AEI/10.13039/501100011033/Unión Europea NextGenerationEU/PRTR and from the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033.Peer reviewe

Identification, characterization, and gene expression analysis of nucleotide binding site (NB)-type resistance gene homologues in switchgrass

Abstract Background Switchgrass (Panicum virgatum L.) is a warm-season perennial grass that can be used as a second generation bioenergy crop. However, foliar fungal pathogens, like switchgrass rust, have the potential to significantly reduce switchgrass biomass yield. Despite its importance as a prominent bioenergy crop, a genome-wide comprehensive analysis of NB-LRR disease resistance genes has yet to be performed in switchgrass. Results In this study, we used a homology-based computational approach to identify 1011 potential NB-LRR resistance gene homologs (RGHs) in the switchgrass genome (v 1.1). In addition, we identified 40 RGHs that potentially contain unique domains including major sperm protein domain, jacalin-like binding domain, calmodulin-like binding, and thioredoxin. RNA-sequencing analysis of leaf tissue from ‘Alamo’, a rust-resistant switchgrass cultivar, and ‘Dacotah’, a rust-susceptible switchgrass cultivar, identified 2634 high quality variants in the RGHs between the two cultivars. RNA-sequencing data from field-grown cultivar ‘Summer’ plants indicated that the expression of some of these RGHs was developmentally regulated. Conclusions Our results provide useful insight into the molecular structure, distribution, and expression patterns of members of the NB-LRR gene family in switchgrass. These results also provide a foundation for future work aimed at elucidating the molecular mechanisms underlying disease resistance in this important bioenergy crop

Expression of Selected Ginkgo biloba Heat Shock Protein Genes After Cold Treatment Could Be Induced by Other Abiotic Stress

Heat shock proteins (HSPs) play various stress-protective roles in plants. In this study, three HSP genes were isolated from a suppression subtractive hybridization (SSH) cDNA library of Ginkgo biloba leaves treated with cold stress. Based on the molecular weight, the three genes were designated GbHSP16.8, GbHSP17 and GbHSP70. The full length of the three genes were predicted to encode three polypeptide chains containing 149 amino acids (Aa), 152 Aa, and 657 Aa, and their corresponding molecular weights were predicted as follows: 16.67 kDa, 17.39 kDa, and 71.81 kDa respectively. The three genes exhibited distinctive expression patterns in different organs or development stages. GbHSP16.8 and GbHSP70 showed high expression levels in leaves and a low level in gynoecia, GbHSP17 showed a higher transcription in stamens and lower level in fruit. This result indicates that GbHSP16.8 and GbHSP70 may play important roles in Ginkgo leaf development and photosynthesis, and GbHSP17 may play a positive role in pollen maturation. All three GbHSPs were up-regulated under cold stress, whereas extreme heat stress only caused up-regulation of GbHSP70, UV-B treatment resulted in up-regulation of GbHSP16.8 and GbHSP17, wounding treatment resulted in up-regulation of GbHSP16.8 and GbHSP70, and abscisic acid (ABA) treatment caused up-regulation of GbHSP70 primarily

Ecological basis for ginkgo agroforestry systems

Ginkgo (Ginkgo biloba L.) is a multi-value deciduous tree species grown for the production of nuts, timber and foliar medicinal properties. Understanding the ecological and biological basis for Ginkgo agroforestry systems is essential for the design of optimum Ginkgo-food plant combinations. A field and pot trial compared acclimation of Ginkgo to changing light, moisture, and nutrient levels. These resources had interactive effects on Ginkgo, which tolerated partial shading and soil resource depletion. Variation in light was found to be more important for biomass accumulation and flavonoid production than soil nutrients and moisture resource over the ranges of resource availability that were studied. Pot and field trials tested the influence of planting density on growth, biomass, and leaf flavonoid levels. There was strong Ginkgo belowground competition for soil nutrients, especially for nitrogen. Increasing density resulted in a significant reduction in many measures of individual Ginkgo seedling performance, such as net photosynthetic rate (Pn), biomass, and flavonoid concentration, but increased performance per unit area over the one and two growing seasons examined. A greenhouse pot replacement series examined interactions between Ginkgo and wheat (Triticum aestivum L. cv. "Feng Shou No. 2") and Ginkgo and broad bean (Vicia laba L.). Broad bean and wheat were more competitive than Ginkgo, which was less affected by wheat than by broad bean. However, there was a compensatory interaction between Ginkgo and wheat and Ginkgo and broad bean. There was significant belowground competition for soil N between Ginkgo and crop species in the Ginkgo/crop mixtures. The two mixtures outproduced monocultures of the individual species in the mixtures. The Ginkgo: broad bean (or wheat) ratio 5:1 had the best combined biomass production and the highest flavonoid yield. A Field factorial experiment with three Ginkgo/crop mixture treatments was conducted to extend the greenhouse study of the competitive ability of Ginkgo and crop species and of optimum Ginkgo/crop combinations. Components of crop biomass per m2 increased with increased crop density and decreased with increased Ginkgo density. There was evidence of Ginkgo/crop mixture ecological niche differentiation and overyielding advantage. The integration of all the parameters describing the competitive ability of crop species showed that crop species were more competitive than Ginkgo at low Ginkgo density, but less competitive than Ginkgo at high Ginkgo density and that rapeseed was more competitive than the other two crop species. Root competition was more intense than shoot competition in the Ginkgo/rapeseed mixture; shoot competition in Ginkgo/wheat and Ginkgo/broad bean mixtures was more intense than root competition. Ginkgo grown with broad bean had higher economic biomass (Ginkgo leaf biomass and crop seed yield) and flavonoid yield than with wheat and rapeseed (Brassica napus L.). Ginkgo: wheat ratio 24: 200 and Ginkgo: rapeseed (or broad bean) ratio 24:5 exhibited maximum combined economic yield in respective mixture, and Ginkgo: broad bean ratio 24: 5 had the highest combined economic yield and income. A chronosequence combined with remeasurement provided data from Ginkgo plantation ages 1, 3, 6,10, 13, 17, 20, 21 and 22 years on various parameters. Ginkgo density had significant effects on PAR, spatial change in Ginkgo line root biomass (FRB) and wheat root biomass (WRB), and spatial and temporal change in Ginkgo nut and crop seed yield. Before Ginkgo plantation age 21 in the Ginkgo/broad bean mixture and plantation age 22 in the Ginkgo/wheat and Ginkgo/rapeseed mixture, close Ginkgo spacing had higher nut yield per ha than narrow spacing. Starting from plantation age 21 in Ginkgo/broad bean mixture and plantation age 22 in the other two mixtures, low density stands gained a higher nut yield per ha than high density stands. Ginkgo/broad bean mixture had higher individual tree and per-ha-Ginkgo nut yield than did the other two mixtures. Per-ha-seed yields of the three crop species at all three densities were in the order of wheat > rapeseed >broad bean. The results of these studies were integrated to provide a conceptual model of the tradeoffs between Ginkgo and food crop values, and a tabular model of optimum Ginkgo monoculture and agroforestry systems was constructed based on the knowledge of their growth strategies, and competitive and other interactions. Future work should combine these data into a mechanistic, agroforestry model, such as FORECAST or FORCEE, to test a variety of management strategies.Forestry, Faculty ofGraduat

Extrapolation Assessment for Forest Structural Parameters in Planted Forests of Southern China by UAV-LiDAR Samples and Multispectral Satellite Imagery

Accurate estimation and extrapolation of forest structural parameters in planted forests are essential for monitoring forest resources, investigating their ecosystem services (e.g., forest structure and functions), as well as supporting decisions for precision silviculture. Advances in unmanned aerial vehicle (UAV)-borne Light Detection and Ranging (LiDAR) technology have enhanced our ability to precisely characterize the 3-D structure of the forest canopy with high flexibility, usually within forest plots and stands. For wall-to-wall forest structure mapping in broader landscapes, samples (transects) of UAV-LiDAR datasets are a cost-efficient solution as an intermediate layer for extrapolation from field plots to full-coverage multispectral satellite imageries. In this study, an advanced two-stage extrapolation approach was established to estimate and map large area forest structural parameters (i.e., mean DBH, dominant height, volume, and stem density), in synergy with field plots and UAV-LiDAR and GF-6 satellite imagery, in a typical planted forest of southern China. First, estimation models were built and used to extrapolate field plots to UAV-LiDAR transects; then, the maps of UAV-LiDAR transects were extrapolated to the whole study area using the wall-to-wall grid indices that were calculated from GF-6 satellite imagery. By comparing with direct prediction models that were fitted by field plots and GF-6-derived spectral indices, the results indicated that the two-stage extrapolation models (R2 = 0.64–0.85, rRMSE = 7.49–26.85%) obtained higher accuracy than direct prediction models (R2 = 0.58–0.75, rRMSE = 21.31–38.43%). In addition, the effect of UAV-LiDAR point density and sampling intensity for estimation accuracy was studied by sensitivity analysis as well. The results showed a stable level of accuracy for approximately 10% of point density (34 pts·m−2) and 20% of sampling intensity. To understand the error propagation through the extrapolation procedure, a modified U-statistics uncertainty analysis was proposed to characterize pixel-level estimates of uncertainty and the results demonstrated that the uncertainty was 0.75 cm for mean DBH, 1.23 m for dominant height, 14.77 m3·ha−1 for volume and 102.72 n·ha−1 for stem density, respectively