Steffensenbuhl4338

Salt stress is one of the most devastating environmental factors threatening soybean growth and yield. However, the molecular link between salt stress and epigenetics has not been well-elucidated in soybean. In this study, from the wild soybean cDNA library, we isolated a GsSnRK1 kinase interacting protein (GsMSTY1) which is phylogenetically homologous with histone acetyltransferase MYST family with unknown function. GsMSTY1 gene is dominantly expressed in wild soybean roots and is highly responsive to abiotic stresses. GsMYST1 was able to be phosphorylated at the Ser44 site by GsSnRK1 and demonstrated in vivo acetyltransferase activity in transgenic soybean roots revealed by an anti-H4ace antibody. A transcription factor protein GsNAC83 was identified to interact with both GsMYST1 and GsSnRK1, and GsNAC83 could recruit the GsMYST1-GsSnRK1 module to COR15B gene promoter determined by ChIP-qPCR assay. To dissect the molecular functions of this ternary complex, we treated the transgenic soybean roots with salt stress and found that the stress could activate GsSnRK1, and the activated GsSnRK1 subsequently phosphorylated GsMYST1 to enhance its acetyltransferase activity which may epigenetically promote the target gene expression. To explore the physiological functions, we coexpressed GsSnRK1 and GsMYST1 genes in soybean hairy roots and found that only GsSnRK1(wt)/GsMYST1(wt) but not the mutant genes could promote soybean resistance to salt stress, implicating that phosphorylation of GsMYST1 is required for it to acetylate histone H4 on the target genes to upregulate expression of the stress-related genes. Our data shed new light on the functions of the GsSnRK1-GsMYST1-GsNAC83 module and its regulatory mechanism on plant tolerance to abiotic stresses.Long non-coding RNAs (lncRNAs) are an increasingly studied group of non-protein coding transcripts with a wide variety of molecular functions gaining attention for their roles in numerous biological processes. Nearly 6,000 lncRNAs have been identified in Arabidopsis thaliana but many have yet to be studied. Here, we examine a class of previously uncharacterized lncRNAs termed CONSERVED IN BRASSICA RAPA (lncCOBRA) transcripts that were previously identified for their high level of sequence conservation in the related crop species Brassica rapa, their nuclear-localization and protein-bound nature. In particular, we focus on lncCOBRA1 and demonstrate that its abundance is highly tissue and developmental specific, with particularly high levels early in germination. lncCOBRA1 contains two snoRNAs domains within it, making it the first sno-lincRNA example in a non-mammalian system. However, we find that it is processed differently than its mammalian counterparts. We further show that plants lacking lncCOBRA1 display patterns of delayed germination and are overall smaller than wild-type plants. Lastly, we identify the proteins that interact with lncCOBRA1 and propose a novel mechanism of lincRNA action in which it may act as a scaffold with the RACK1A protein to regulate germination and development, possibly through a role in ribosome biogenesis.The generation of oxygen and organic matter in plants mainly depends on photosynthesis, which directly affects plant growth and development. The chloroplast is the main organelle in which photosynthesis occurs. https://www.selleckchem.com/products/mk-8617.html In this study, a Glycine max pale green leaf 3-1 (Gmpgl3-1) mutant was isolated from the soybean mutagenized population. The Gmpgl3-1 mutant presented with decreased chlorophyll contents, reduced chloroplast stroma thylakoids, reduced yields, and decreased numbers of pods per plant. Bulked segregant analysis (BSA) together with map-based cloning revealed a single-nucleotide non-synonymous mutation at the 341st nucleotide of the first exon of the chloroplast development-related GmTic110a gene. The phenotype of the knockout plants was the same as that of the mutant. The GmTic110a gene was highly expressed in the leaves at various developmental stages, and its protein was localized to the inner chloroplast membrane. Split luciferase complementation assays and coimmunoprecipitation (co-IP) experiments revealed that GmTic110a interacted with GmTic20, GmTic40a, and GmTic40b in tobacco leaves. These results indicated that the GmTic110a gene plays an important role in chloroplast development.Postharvest deterioration can result in qualitative and quantitative changes in the marketability of horticultural commodities, as well as considerable economic loss to the industry. Low temperature and controlled atmosphere conditions (low O2 and elevated CO2) are extensively employed to prolong the postharvest life of these commodities. Nevertheless, they may suffer from chilling injury and other physiological disorders, as well as excessive water loss and bacterial/fungal decay. Research on the postharvest physiological, biochemical, and molecular responses of horticultural commodities indicates that low temperature/controlled atmosphere storage is associated with the promotion of γ-aminobutyrate (GABA) pathway activity, with or without the accumulation of GABA, delaying senescence, preserving quality and ameliorating chilling injury. Regardless of whether apple fruits are stored under low temperature/controlled atmosphere conditions or room temperature, elevated endogenous GABA or exogenous GABA maintains. The occurrence of the aluminum-activated malate transporter and the glutamate/aspartate/GABA exchanger in the tonoplast, respectively, offers prospects for reducing transpirational water in cut flowers and immature green fruit, and for altering the development, flavor and biotic resistance of apple fruits.Ubiquitination, a widespread mechanism of regulating cellular responses in plants, is one of the most important post-translational modifications of proteins in many biological processes and is involved in the regulation of plant disease resistance responses. Predicting ubiquitination is an important technical method for plant protection. Traditional ubiquitination site determination methods are costly and time-consuming, while computational-based prediction methods can accurately and efficiently predict ubiquitination sites. At present, capsule networks and deep learning are used alone for prediction, and the effect is not obvious. The capsule network reflects the spatial position relationship of the internal features of the neural network, but it cannot identify long-distance dependencies or focus on amino acids in protein sequences or their degree of importance. In this study, we investigated the use of convolutional neural networks and capsule networks in deep learning to design a novel model "Caps-Ubi," first using the one-hot and amino acid continuous type hybrid encoding method to characterize ubiquitination sites. The sequence patterns, the dependencies between the encoded protein sequences and the important amino acids in the captured sequences, were then focused on the importance of amino acids in the sequences through the proposed Caps-Ubi model and used for multispecies ubiquitination site prediction. Through relevant experiments, the proposed Caps-Ubi method is superior to other similar methods in predicting ubiquitination sites.Transmembrane kinases (TMKs) play important roles in plant growth and signaling cascades of phytohormones. However, its function in the regulation of early leaf senescence (ELS) of plants remains unknown. Here, we report the molecular cloning and functional characterization of the WATER-SOAKED SPOT1 gene which encodes a protein belongs to the TMK family and controls chloroplast development and leaf senescence in rice (Oryza sativa L.). The water-soaked spot1 (oswss1) mutant displays water-soaked spots which subsequently developed into necrotic symptoms at the tillering stage. Moreover, oswss1 exhibits slightly rolled leaves with irregular epidermal cells, decreased chlorophyll contents, and defective stomata and chloroplasts as compared with the wild type. Map-based cloning revealed that OsWSS1 encodes transmembrane kinase TMK1. Genetic complementary experiments verified that a Leu396Pro amino acid substitution, residing in the highly conserved region of leucine-rich repeat (LRR) domain, was responsible for the phenotypes of oswss1. OsWSS1 was constitutively expressed in all tissues and its encoded protein is localized to the plasma membrane. Mutation of OsWSS1 led to hyper-accumulation of reactive oxygen species (ROS), more severe DNA fragmentation, and cell death than that of the wild-type control. In addition, we found that the expression of senescence-associated genes (SAGs) was significantly higher, while the expression of genes associated with chloroplast development and photosynthesis was significantly downregulated in oswss1 as compared with the wild type. Taken together, our results demonstrated that OsWSS1, a member of TMKs, plays a vital role in the regulation of ROS homeostasis, chloroplast development, and leaf senescence in rice.The detection of plant disease is of vital importance in practical agricultural production. It scrutinizes the plant's growth and health condition and guarantees the regular operation and harvest of the agricultural planting to proceed successfully. In recent decades, the maturation of computer vision technology has provided more possibilities for implementing plant disease detection. Nonetheless, detecting plant diseases is typically hindered by factors such as variations in the illuminance and weather when capturing images and the number of leaves or organs containing diseases in one image. Meanwhile, traditional deep learning-based algorithms attain multiple deficiencies in the area of this research (1) Training models necessitate a significant investment in hardware and a large amount of data. (2) Due to their slow inference speed, models are tough to acclimate to practical production. (3) Models are unable to generalize well enough. Provided these impediments, this study suggested a Tranvolution detection network with GAN modules for plant disease detection. Foremost, a generative model was added ahead of the backbone, and GAN models were added to the attention extraction module to construct GAN modules. Afterward, the Transformer was modified and incorporated with the CNN, and then we suggested the Tranvolution architecture. Eventually, we validated the performance of different generative models' combinations. Experimental outcomes demonstrated that the proposed method satisfyingly achieved 51.7% (Precision), 48.1% (Recall), and 50.3% (mAP), respectively. Furthermore, the SAGAN model was the best in the attention extraction module, while WGAN performed best in image augmentation. Additionally, we deployed the proposed model on Hbird E203 and devised an intelligent agricultural robot to put the model into practical agricultural use.Paphiopedilum (Orchidaceae) is one of the world's most popular orchids that is found in tropical and subtropical forests and has an enormous ornamental value. SEPALLATA-like (SEP-like) MADS-box genes are responsible for floral organ specification. In this study, three SEP-like MADS-box genes, PhSEP1, PhSEP2, and PhSEP3, were identified in Paphiopedilum henryanum. These genes were 732-916 bp, with conserved SEPI and SEPII motifs. Phylogenetic analysis revealed that PhSEP genes were evolutionarily closer to the core eudicot SEP3 lineage, whereas none of them belonged to core eudicot SEP1/2/4 clades. PhSEP genes displayed non-ubiquitous expression, which was detectable across all floral organs at all developmental stages of the flower buds. Furthermore, subcellular localization experiments revealed the localization of PhSEP proteins in the nucleus. Yeast two-hybrid assays revealed no self-activation of PhSEPs. The protein-protein interactions revealed that PhSEPs possibly interact with B-class DEFICIENS-like and E-class MADS-box proteins.