Interference Lines Research Articles

Histone demethylase JMJ713 interaction with JMJ708 modulating H3K36me2, enhances rice heat tolerance through promoting hydrogen peroxide scavenging

The Earth is currently undergoing rapid warming cause of the accumulation in greenhouse gas emissions into the atmosphere and the consequent rise in global temperatures. High temperatures can bring the effects on rice development and growth (Oryza sativa) and thereby decrease rice yield. In this study, we have identified that both JMJ713 and JMJ708 possess distinct histone demethylase activities. Specifically, JMJ713 modulates the levels of H3K36me2 while JMJ708 alters H3K9me3. Additionally, we have observed an interaction between JMJ713 and JMJ708, which collectively modify the level of H3K36me2. Furthermore, our findings demonstrate that JMJ713 plays an essential role to heat stress responses in rice. The overexpression of JMJ713 enhances heat tolerance in rice, whereas JMJ713 RNA interference rice lines exhibit increased sensitivity to heat. Further investigations revealed that overexpression of JMJ713 activated catalase (CAT) and peroxidase (POD) activities by mitigating excessive accumulation of reactive oxygen species (ROS) caused by heat stress. Interestingly, the setting rates of JMJ713 RNA interference lines decreased in comparing to wild-type, indicating that JMJ713 might play a crucial role in the rice seed development stage as well. Collectively, Overall, this study not only highlights JMJ713 is involved in heat stress responses but also provides insights into the conserved Fe(Ⅱ) and α-ketoglutarate (KG) binding residues are crucial for the demethylase activity of JMJ713, as well as JMJ713 interacts with JMJ708 to jointly regulate the levels of H3K36me2.

A Fuzzy-Logic-Based Approach for Eliminating Interference Lines in Micro Rain Radar (MRR-2)

This research presents a novel fuzzy-logic-based algorithm aimed at detecting and removing interference lines from Micro Rain Radar (MRR-2) data. Interference lines, which are non-meteorological echoes with unknown origins, can severely obscure meteorological signals. Leveraging an understanding of interference line characteristics, such as temporal continuity, we identified and utilized eight key variables to distinguish interference lines from meteorological signals. These variables include radar moments, Doppler spectrum peaks, and the spatial/temporal continuity of Doppler velocity. The algorithm was developed and validated using data from MRR installations at three sites (Seoul, Suwon, and Incheon) in South Korea, from June to September 2021–2023. While there is a slight tendency to eliminate some weak precipitation, results indicate that the algorithm effectively removes interference lines while preserving the majority of genuine precipitation signals, even in complex scenarios where both interference and precipitation signals are present. The developed software, written in Python 3 and available as open-source, outputs in NetCDF4 format, with customizable parameters for user flexibility. This tool offers a significant contribution to the field, facilitating the accurate interpretation of MRR-2 data contaminated by interference.

Analysis of rosmarinic acid synthase (RAS) gene family and functional study of SmRAS1/2/4 in Salvia miltiorrhiza

Rosmarinic acid synthase is an essential enzyme involved in the biosynthesis of rosmarinic acid (RA), which facilitates the coupling of phenylpropanoid and tyrosine-derived pathway products. Our study identified six SmRAS genes in Salvia miltiorrhiza, with SmRAS1 being the only one functionally characterized to date. Real-time quantitative PCR was employed to analyze the expression profiles of the SmRAS gene family, revealing that SmRAS1/2/4 are predominantly expressed in the roots, which are the medicinal components of S. miltiorrhiza. SmRAS2 and SmRAS4 exhibited significant responses to abscisic acid (ABA), gibberellin (GA3), and methyl jasmonate (MeJA) stimuli, while SmRAS1 had notable responses to GA3 and MeJA. β-glucuronidase (GUS) staining in transgenic Arabidopsis thaliana confirmed a spatiotemporal expression pattern of SmRAS1/2/4 that was consistent with the qRT-PCR results. SmRAS1/2/4 are primarily localized to the cytoplasm and plasma membrane. Our findings suggested that the overexpressions of SmRAS1 or SmRAS4 led to increased levels of salvianolic acid B (SalB) and RA, with a concomitant decrease in the Danshensu (DSS) content, which served as a substrate. In contrast, RNA interference lines exhibited a downward trend in the content of these substances. Interestingly, no significant changes were detected in the SalB, RA, or DSS contents due to the overexpression of SmRAS2 or RNA interference lines. Collectively, our study demonstrated that SmRAS1 and SmRAS4 are key regulators of RA and SalB biosynthesis in S. miltiorrhiza, while SmRAS2′s role appears less impactful, suggesting a complex regulatory network that influences the medicinal properties of this plant.

MsMIOX2, encoding a MsbZIP53-activated myo-inositol oxygenase, enhances saline-alkali stress tolerance by regulating cell wall pectin and hemicellulose biosynthesis in alfalfa.

Alfalfa is one of the most widely cultivated forage crops worldwide. However, soil salinization restricts alfalfa growth and development and affects global productivity. The plant cell wall is the first barrier against various stresses. Therefore, elucidating the alterations in cell wall architecture is crucial for stress adaptation. This study aimed to clarify the impact of myo-inositol oxygenase 2 (MsMIOX2) on cell wall pectin and hemicellulose biosynthesis under saline-alkali stress and identify the upstream transcription factors that govern MsMIOX2. MsMIOX2 activation induced cell wall pectin and hemicellulose accumulation under saline-alkali stress. The effects of MsMIOX2 in saline-alkali tolerance were investigated by characterizing its overexpression and RNA interference lines. MsMIOX2 overexpression positively regulated the antioxidant system and photosynthesis in alfalfa under saline-alkali stress. MsMIOX2 exhibited myo-inositol oxygenase activity, which increased polysaccharide contents, facilitated pectin and hemicellulose biosynthesis, and extended the cell wall thickness. However, MsMIOX2 RNA interference decreased cell wall thickness and alleviated alfalfa saline-alkali stress tolerance. In addition, MsbZIP53 was identified as an upstream transcriptional MsMIOX2 regulator by yeast one-hybrid, electrophoretic mobility shift assay, dual-luciferase, and beta-glucuronidase assays. MsbZIP53 overexpression increased MsMIOX2 expression, elevated MIOX activity, reinforced the antioxidant system and photosynthesis, and increased saline-alkali stress tolerance in alfalfa. In conclusion, this study presents a novel perspective for elucidating the molecular mechanisms of saline-alkali stress tolerance in alfalfa and emphasizes the potential use of MsMIOX2 in alfalfa breeding.

Real-time identification of noise type contaminated in surface electromyogram signals using efficient statistical features

Different types of noise contaminating the surface electromyogram (EMG) signal may degrade the recognition performance. For noise removal, the type of noise has to first be identified. In this paper, we propose a real-time efficient system for identifying a clean EMG signal and noisy EMG signals contaminated with any one of the following three types of noise: electrocardiogram interference, spike noise, and power line interference. Two statistical descriptors, kurtosis and skewness, are used as input features for the cascading quadratic discriminant analysis classifier. An efficient simplification of kurtosis and skewness calculations that can reduce computation time and memory storage is proposed. The experimental results from the real-time system based on an ATmega 2560 microcontroller demonstrate that the kurtosis and skewness values show root mean square errors between the traditional and proposed efficient techniques of 0.08 and 0.09, respectively. The identification accuracy with five-fold cross-validation resulting from the quadratic discriminant analysis classifier is 96.00%.

Enhanced detection limit in an exceptional surface-based fiber resonator by manipulating Fano interference.

An exceptional surface (ES) has advantages in improving sensing robustness and enhancing frequency splitting. Typically, the eigenvalue splitting must exceed the mode linewidth in order to be clearly visible in the spectrum, which limits the precision of the ES-based sensing structure. In this paper, a strategy for manipulating spectral line shape in an ES-based structure is experimentally realized. In addition, the limit of the minimum detectable displacement can be further reduced by monitoring the peak intensity of the Fano interference line shape. The demonstration of Fano interference in an ES-based system opens the way for a new class of ultrasensitive optical sensors.

A tonoplast-localized TPK-type K+ transporter (TPKa) regulates potassium accumulation in tobacco

Potassium ion (K+) is one of the most essential nutrients for the growth and development of tobacco (Nicotiana tabacum L.), however, the molecular regulation of K+ concentration in tobacco remains unclear. In this study, a two-pore K (TPK) channel gene NtTPKa was cloned from tobacco, and NtTPKa protein contains the unique K+ selection motif GYGD and its transmembrane region primarily locates in the tonoplast membrane. The expression of NtTPKa gene was significantly increased under low-potassium stress conditions. The concentrations of K+ in tobacco were significantly increased in the NtTPKa RNA interference lines and CRISPR/Cas9 knockout mutants. In addition, the transport of K+ by NtTPKa was validated using patch clamp technique, and the results showed that NtTPKa channel protein exclusively transported K+ in a concentration-dependent manner. Together, our results strongly suggested that NtTPKa is a key gene in maintaining K+ homeostasis in tobacco, and it could provide a new genetic resource for increasing the concentration of K+ in tobacco.

Automated detection and removal of artifacts from sEMG signals based on fuzzy inference system and signal decomposition methods

Surface electromyography (sEMG) signal quality decreases when it is contaminated by different types of artifacts. Detection and removal of the contaminants from sEMG signals were a major and interesting task for several research works in recent years. In this paper, a novel automatic approach was designed for the detection and removal of artifacts from sEMG signals. The proposed method consists of a combined model that based on a fuzzy inference system (FIS), a signal decomposition method, and a denoising technique. Based on three spectral statistical features, which are calculated in frequency domain using power spectral density: composite multiscale entropy (CMSE), kurtosis (K), and skewness (S), FIS detects the artifactual epochs of the sEMG signal. Thereafter, those epochs are decomposed into their components by a signal decomposition. In this work, we have tested the performance of two decomposition methods namely stationary wavelet transform (SWT) and variational mode decomposition (VMD). A second FIS is used to select the contaminated components. Depending on the type of artifact, two procedures are considered, the first aims to denoise motion artifact (MOA), electrocardiography interference (ECG) and power line interference (PLI), whereas the second procedure aims to eliminate the additive white gaussian noise (AWGN). Finally, the denoised signal is reconstructed. The evaluation performance of the proposed method is compared with the performance of some existing methods using the following metrics: SNR improvement (ΔSNR), the reduction in artifact (λ(%)), improvement in signal to noise and distortion ratio (ΔSNDR) and improvement in the root mean square error (ΔRMSE). The results emphazed the superiority of our method over others in terms of all the used metrics and computational time.

Electromagnetic telemetry signal denoising: An interference elimination via parameter estimation

Electromagnetic telemetry has emerged as a promising technique for the real-time acquisition of downhole data. However, the transmission of electromagnetic waves through the formation encounters attenuation, leading to a weakened received signal at the surface, typically registering at the microvolt level. The growing presence of surface electrical equipment in well-site environments has engendered heightened electromagnetic interference, thus deteriorating the signal-to-noise ratio (SNR) of received signals. The conventional linear filtering method can effectively eliminate the electromagnetic interference at the wellsite, but it has no effect on the low frequency interference close to the carrier frequency, especially the common low-frequency pulse interference (LPI) and power line interference (PLI). To mitigate the adverse effects of surface noise, we propose a nonlinear processing method based on parameter estimation algorithms. Generally, the proposed method entails reconstructing the interference by accurate parameter estimation and subtracting it from the received signal, aiming to enhance the SNR of the received signal. Simulation data and real noise data collected in the field are processed to verify the effectiveness of the proposed method. The results demonstrate the superiority of this approach over traditional filtering techniques in effectively eradicating surface interference.

Deoxyxylulose 5-Phosphate Synthase Does Not Play a Major Role in Regulating the Methylerythritol 4-Phosphate Pathway in Poplar.

The plastidic 2-C-methylerythritol 4-phosphate (MEP) pathway supplies the precursors of a large variety of essential plant isoprenoids, but its regulation is still not well understood. Using metabolic control analysis (MCA), we examined the first enzyme of this pathway, 1-deoxyxylulose 5-phosphate synthase (DXS), in multiple grey poplar (Populus × canescens) lines modified in their DXS activity. Single leaves were dynamically labeled with 13CO2 in an illuminated, climate-controlled gas exchange cuvette coupled to a proton transfer reaction mass spectrometer, and the carbon flux through the MEP pathway was calculated. Carbon was rapidly assimilated into MEP pathway intermediates and labeled both the isoprene released and the IDP+DMADP pool by up to 90%. DXS activity was increased by 25% in lines overexpressing the DXS gene and reduced by 50% in RNA interference lines, while the carbon flux in the MEP pathway was 25-35% greater in overexpressing lines and unchanged in RNA interference lines. Isoprene emission was also not altered in these different genetic backgrounds. By correlating absolute flux to DXS activity under different conditions of light and temperature, the flux control coefficient was found to be low. Among isoprenoid end products, isoprene itself was unchanged in DXS transgenic lines, but the levels of the chlorophylls and most carotenoids measured were 20-30% less in RNA interference lines than in overexpression lines. Our data thus demonstrate that DXS in the isoprene-emitting grey poplar plays only a minor part in controlling flux through the MEP pathway.

ANALYTICAL APPROACH FOR PREDICTING THE STATE OF STRENGTH PARAMETERS OF ASSYMETRIC GEARS

During the process of high-speed gear hobbing of asymmetrical cylindrical gear gears, the surface layer undergoes repeated plastic deformation and leads, in turn, to a change in the physical and mechanical properties and structure of the metal. In order to increase the importance of teeth in machine drives of important machinery, the use of gears with an asymmetrical shape of the teeth is demonstrated, which reflects the functional difference of gears according to GOST 1643-81 and an asymmetrical profile. In accordance with the changes, occurring in the surface layer, the depth of the hardened layer is determined by the change in microhardness across the cross section of the part and by changing the nature of interference lines on x-ray diffraction patterns during layer-by-layer etching of the surface under study depending on the cutting speed. The cutting speed acts as a factor that determines the rate of plastic deformation of the surface layer. With increasing strain rate, the tensile strength and yield strength of structural materials increase. Increasing the yield strength reduces the plasticity of the processed material and acts in the direction of reducing the degree of hardening. With increasing temperature and degree of deformation, the rate of the softening process, which occurs due to recrystallization, increases. An increase in cutting temperature increases the intensity of the softening process and reduces the degree of hardening.

Cucumber malate decarboxylase, CsNADP-ME2, functions in the balance of carbon and amino acid metabolism in fruit

Abstract Central metabolism produces carbohydrates and amino acids that are tightly correlated to plant growth and thereby crop productivity. Malate is reported to link mitochondrial respiratory metabolism with cytosolic biosynthetic pathways. Although the function of malate metabolism-related enzymes in providing carbon has been characterized in some plants, evidence for this role in the fleshy fruit of cucumber is lacking. Here, radiolabeled bicarbonate fed into the xylem stream from the cucumber roots was incorporated into amino acids, soluble sugars, and organic acids in the exocarp and vasculature of fruits. The activities of decarboxylases, especially decarboxylation from NADP-dependent malic enzyme (NADP-ME), were higher in cucumber fruit than in the leaf lamina. Histochemical localization revealed that CsNADP-ME2 was mainly located in the exocarp and vascular bundle system of fruit. Radiotracer and gas-exchange analysis indicated that overexpression of CsNADP-ME2 could promote carbon flux into soluble sugars and starch in fruits. Further studies combined with metabolic profiling revealed that the downregulation of CsNADP-ME2 in RNA interference (RNAi) lines caused the accumulation of its substrate, malate, in the exocarp. In addition to inhibition of glycolysis-related gene expression and reduction of the activities of the corresponding enzymes, increased amino acid synthesis and decreased sugar abundance were also observed in these lines. The opposite effect was found in CsNADP-ME2-overexpressing lines, suggesting that there may be a continuous bottom-up feedback regulation of glycolysis in cucumber fruits. Overall, our studies indicate that CsNADP-ME2 may play potential roles in both central carbon reactions and amino acid metabolism in cucumber fruits.

SlMYB41 positively regulates tomato thermotolerance by activating the expression of SlHSP90.3

High-temperature stress has become a major abiotic factor that dramatically limits plant growth and crop yield. Plants have evolved complex mechanisms to cope with high-temperature stress, but the factors that regulate plant thermotolerance remain to be discovered. Here, a high temperature-induced MYB transcription factor SlMYB41 was cloned from tomato (Solanum lycopersicum). Two individual SlMYB41-RNA interference (RNAi) lines (MR) and one CRISPR/Cas9 mediated myb41 mutant (MC) were obtained to investigate the function of SlMYB41 in tomato thermotolerance. Under high-temperature stress, we found that the MR and MC lines showed more wilting than the wild type (WT), with more ion leakage, more MDA accumulation, lower contents of osmotic adjustment substances, and more accumulation of reactive oxygen species (ROS) which was resulted from lower antioxidative enzyme activities. In addition, the photosynthetic capacity and complex of MR and MC lines were damaged more seriously than WT plants under high-temperature stress, mainly manifested in lower photosynthetic rate and Fv/Fm. Moreover, heat stress-related genes, such as SlHSP17.6, SlHSP17.7, and SlHSP90.3 were downregulated in MR and MC lines. Importantly, Y1H and LUC analysis indicated that SlMYB41 can directly activate the transcription of SlHSP90.3. Together, our study suggest that SlMYB41 positively regulates tomato thermotolerance by activating the expression of SlHSP90.3.

The commonly used methods for ECG Power-line interference removal

The amplitude of electrocardiogram (ECG) signals is on the millivolt level, and is susceptible to interference from human respiration, muscle tremors, and device circuits during the acquisition process, resulting in baseline drift, electromyographic (EMG) interference, and power line interference. Power line interference is a significant noise source in physiological signal acquisition among these. This article explores several methods to reduce the impact of power frequency interference. By analyzing wavelet transforms, adaptive filtering, and smoothing filters, commonly used methods are evaluated to determine their advantages and limitations. Experimental results show that the smoothed filtering method produces the highest SNR and lowest MSE of the electrocardiogram signal after denoising, resulting in the best denoising effect and thorough filtering. The denoising effect of wavelet transform and adaptive filter is poor. But the different methods for power line interference elimination should be applied according to the data acquisition requirements and equipment performance in response to different situations.

Melatonin-mediated CcARP1 alters F-actin dynamics by phosphorylation of CcADF9 to balance root growth and salt tolerance in pigeon pea.

As a multifunctional hormone-like molecule, melatonin exhibits a pleiotropic role in plant salt stress tolerance. While actin cytoskeleton is essential to plant tolerance to salt stress, it is unclear if and how actin cytoskeleton participates in the melatonin-mediated alleviation of plant salt stress. Here, we report that melatonin alleviates salt stress damage in pigeon pea by activating a kinase-like protein, which interacts with an actin-depolymerizing factor. Cajanus cajan Actin-Depolymerizing Factor 9 (CcADF9) has the function of severing actin filaments and is highly expressed under salt stress. The CcADF9 overexpression lines (CcADF9-OE) showed a reduction of transgenic root length and an increased sensitivity to salt stress. By using CcADF9 as a bait to screen an Y2H library, we identified actin depolymerizing factor-related phosphokinase 1 (ARP1), a novel protein kinase that interacts with CcADF9. CcARP1, induced by melatonin, promotes salt resistance of pigeon pea through phosphorylating CcADF9, inhibiting its severing activity. The CcARP1 overexpression lines (CcARP1-OE) displayed an increased transgenic root length and resistance to salt stress, whereas CcARP1 RNA interference lines (CcARP1-RNAi) presented the opposite phenotype. Altogether, our findings reveal that melatonin-induced CcARP1 maintains F-actin dynamics balance by phosphorylating CcADF9, thereby promoting root growth and enhancing salt tolerance.

The SbWRKY54–SbHKT2b transcriptional cascade confers cadmium stress tolerance in sorghum

In plants, high–affinity potassium transporters (HKTs) not only play a significant role in potassium transport but may also be important for the abiotic stress response. However, information regarding the response of HKTs to cadmium (Cd) stress is limited. Here, we focus on SbHKT2b, the expression of which is highly induced by Cd exposure. SbHKT2b overexpression reduced the accumulation of Cd and increased tolerance to Cd exposure, while SbHKT2b–RNA interference (RNAi) lines exhibited the opposite phenotype. In addition, the overexpression of SbHKT2b resulted in reduced reactive oxygen species (ROS) accumulation and enhanced ROS quenching capacity under Cd stress. Further analyses revealed that SbWRKY54 directly binds to the SbHKT2b promoter and upregulates its expression. Overall, the overexpression of SbWRKY54 decreased Cd and ROS accumulation in transgenic sorghum. Taken together, our results showed that SbWRKY54–SbHKT2b is an important Cd stress response pathway in sorghum.

Improved method for positioning crane grab boom corner points using Hough transform and k‐means clustering

AbstractIn the process of automatic grabbing of bridge segment beams, it is crucial to accurately locate and align the corner points of the crane's boom with the beam's lifting holes. This requires the utilization of image processing techniques to precisely detect and locate the corner points of the crane's boom. Existing feature matching methods face challenges such as low detection accuracy and unsuitability for this specific scenario. This article proposes a novel approach for corner point localization by using the intersection points of lines, facilitating the matching of feature points between left and right images. The method consists of three steps: first, a grayscale difference map is constructed by utilizing the R and G channels of the RGB color space. This enhances the bimodal characteristics of the grayscale histograms between the foreground and background, which facilitates the subsequent binarization process. Additionally, opening and closing operations are employed to remove small artifacts from the Canny edge detection results, effectively reducing noise. Second, an adaptive thresholding method based on the mean and variance of Hough transform voting scores is proposed. This method filters out interference lines from the clustering results by selecting appropriate voting scores. Furthermore, an improved centroid calculation method is introduced, which utilizes weighted formulas based on different proportions of voting scores. These weighted formulas replace the original clustering centroids as the basis for line fitting. Finally, the corner coordinates of the crane's boom are computed based on the line fitting results, and the recognition accuracy is compared under different lighting conditions. Experimental results demonstrate that the proposed algorithm exhibits smaller detection errors and higher robustness compared to other corner detection algorithms, particularly when there are numerous interference edge points in the edge detection results. The computed corner coordinates achieve pixel‐level accuracy. The algorithm performs optimally under strong supplementary lighting conditions, with an average detection error percentage of 97.1% within 0–2 pixels and a recognition accuracy of 98.6%. The recognition success rates under different lighting conditions are all above 92.9%. This method is superior to traditional corner detection methods, meets the requirements for automatic grabbing of the boom, and holds practical engineering value. It provides a basis for addressing the accuracy and robustness challenges of crane algorithms influenced by multiple environmental factors.

A Multi-Scale Hybrid Attention Network for Sentence Segmentation Line Detection in Dongba Scripture

Dongba scripture sentence segmentation is an important and basic work in the digitization and machine translation of Dongba scripture. Dongba scripture sentence segmentation line detection (DS-SSLD) as a core technology of Dongba scripture sentence segmentation is a challenging task due to its own distinctiveness, such as high inherent noise interference and nonstandard sentence segmentation lines. Recently, projection-based methods have been adopted. However, these methods are difficult when dealing with the following two problems. The first is the noisy problem, where a large number of noise in the Dongba scripture image interference detection results. The second is the Dongba scripture inherent characteristics, where many vertical lines in Dongba hieroglyphs are easily confused with the vertical sentence segmentation lines. Therefore, this paper aims to propose a module based on the convolutional neural network (CNN) to improve the accuracy of DS-SSLD. To achieve this, we first construct a tagged dataset for training and testing DS-SSLD, including 2504 real images collected from Dongba scripture books and sentence segmentation targets. Then, we propose a multi-scale hybrid attention network (Multi-HAN) based on YOLOv5s, where a multiple hybrid attention unit (MHAU) is used to enhance the distinction between important features and redundant features, and the multi-scale cross-stage partial unit (Multi-CSPU) is used to realize multi-scale and richer feature representation. The experiment is carried out on the Dongba scripture sentence segmentation dataset we built. The experimental results show that the proposed method exhibits excellent detection performance and outperforms several state-of-the-art methods.

MdMPK3 and MdMPK6 fine-tune MdWRKY17-mediated transcriptional activation of the melatonin biosynthesis gene MdASMT7.

Melatonin (N-acetyl-5-methoxytryptamine) is a potent reactive oxygen species (ROS) scavenger that increases the biotic and abiotic stress tolerance in plants. The signaling and regulation pathways of melatonin in plants remain elusive. Here, we report that transgenic apple (Malus domestica) plants overexpressing the transcription factor gene, MdWRKY17, have higher melatonin contents and lower ROS levels than those of control, while the MdWRKY17 RNA interference (RNAi) lines show the reversed phenotype. The binding of MdWRKY17 to N-acetylserotonin O-methyltransferase7 (MdASMT7) directly promotes the MdASMT7 expression in the in vitro and in vivo. MdASMT7is a melatonin synthase that localizes to the plasma membrane. MdASMT7 overexpression rescued the lower melatonin contents of MdWRKY17-RNAi lines, confirming the role of MdWRKY17-MdASMT7 module in melatonin biosynthesis in apple. Furthermore, melatonin treatment activated the mitogen-activated kinases (MPKs) MdMPK3 and MdMPK6, which phosphorylate MdWRKY17 to promote transcriptional activation of MdASMT7. RNAi-mediated silencing of MdMPK3/6 decreases MdASMT7 expression in transgenic apple plants overexpressing MdWRKY17, which further confirms MdMPK3/6 fine-tunes MdWRKY17-mediated MdASMT7 transcription. This also forms a positive loop that melatonin activates MdMPK3/6 and thus accelerates the biosynthesis of itself via triggering MdMPK3/6-MdWRKY17-MdASMT7 pathway. This novel melatonin regulatory pathway not only have dissected the molecular mechanisms of melatonin biosynthesis but also provided an alternative approach for generating transgenic melatonin-rich apples which may benefits to human health.

CG hypermethylation of the bHLH39 promoter regulates its expression and Fe deficiency responses in tomato roots.

Iron (Fe) is an essential micronutrient for all organisms, including plants, whose limited bioavailability restricts plant growth, yield, and nutritional quality. While the transcriptional regulation of plant responses to Fe deficiency have been extensively studied, the contribution of epigenetic modulations, such as DNA methylation, remains poorly understood. Here, we report that treatment with a DNA methylase inhibitor repressed Fe deficiency-induced responses in tomato (Solanum lycopersicum) roots, suggesting the importance of DNA methylation in regulating Fe deficiency responses. Dynamic changes in the DNA methylome in tomato roots responding to short-term (12hours) and long-term (72hours) Fe deficiency identified many differentially methylated regions (DMRs) and DMR-associated genes. Most DMRs occurred at CHH sites under short-term Fe deficiency, whereas they were predominant at CG sites following long-term Fe deficiency. Furthermore, no correlation was detected between the changes in DNA methylation levels and the changes in transcript levels of the affected genes under either short-term or long-term treatments. Notably, one exception was CG hypermethylation at the bHLH39 promoter, which was positively correlated with its transcriptional induction. In agreement, we detected lower CG methylation at the bHLH39 promoter and lower bHLH39 expression in MET1-RNA interference lines compared with wild-type seedlings. Virus-induced gene silencing of bHLH39 and luciferase reporter assays revealed that bHLH39 is positively involved in the modulation of Fe homeostasis. Altogether, we propose that dynamic epigenetic DNA methylation in the CG context at the bHLH39 promoter is involved in its transcriptional regulation, thus contributing to the Fe deficiency response of tomato.