Veliparib exerts protective effects in intracerebral hemorrhage mice by inhibiting the inflammatory response and accelerating hematoma resolution.

Poly (ADP-ribose) polymerase (PARP) inhibitors have potent anti-inflammatory effects, including the suppression of brain microglial activation. Veliparib, a well-known PARP1/2 inhibitor, exhibits particularly high brain penetration, but its effects on stroke outcome is unknown. Here, the effects of veliparib on the short-term outcome of intracerebral hemorrhage (ICH), the most lethal type of stroke, were investigated. Collagenase-induced mice ICH model was applied, and the T2-weighted magnetic resonance imaging was performed to evaluate lesion volume. Motor function and hematoma volume were also measured. We further performed immunofluorescence, enzyme linked immunosorbent assay, flow cytometry, and blood-brain barrier assessment to explore the potential mechanisms. Our results demonstrated veliparib reduced the ICH lesion volume dose-dependently and at a dosage of 5 mg/kg, veliparib significantly improved mouse motor function and promoted hematoma resolution at days 3 and 7 post-ICH. Veliparib inhibited glial activation and downregulated the production of pro-inflammatory cytokines. Veliparib significantly decreased microglia counts and inhibited peripheral immune cell infiltration into the brain on day 3 after ICH. Veliparib improved blood-brain barrier integrity at day 3 after ICH. These findings demonstrate that veliparib improves ICH outcome by inhibiting inflammatory responses and may represent a promising novel therapy for ICH.

Genetic analysis and QTL mapping of seed hardness trait in a soybean (Glycine max) recombinant inbred line (RIL) population.

Seed hardness is a critical quality trait impacting both the suitability of soybeans for consumption and their processing. The primary objective of this study was to explore the genetic foundations underlying seed hardness in soybeans. A 234 recombinant inbred line (RIL) population was evaluated for seed hardness across three years (2015 in Gansu, 2016, and 2017 in Hainan). Notably, the parent varieties, Zhonghuang35 and Jindou21, displayed significant differences in seed hardness. Also, the RIL population exhibited a wide range of genetic variation in seed hardness, with coefficients of variation between 70.53 % and 94.94 %. The frequency distribution of this trait conformed to a relatively normal distribution, making it suitable for QTL analysis. Six QTLs associated with seed hardness were identified with three located on chromosome 2 and three on chromosome 16. The major QTL, qHS-2-1, consistently exhibited the highest percentage of PVE and LOD in Gansu 2015, Hainan 2016, and Hainan 2017, suggesting its central role in determining seed hardness. Further investigation revealed four genes within the qHS-2-1 interval potentially related to seed hardness. GO enrichment analysis provided insights into their functions, including factors such as Glyma.02G307000, a pectin lyase-like superfamily protein, which could influence seed hardness through its role in pectin lyase enzyme activity. Expression analysis of these candidate genes demonstrated significant differences between the two parent varieties, further highlighting their potential role in seed coat hardness. This study offers valuable insights into the genetic mechanisms governing soybean seed coat hardness, providing a foundation for future research and crop improvement efforts.

Analysis of pollutant dispersion patterns in rivers under different rainfall based on an integrated water-land model.

In the context of rapid urban expansion, the interaction between humanity and nature has become more prominent. Urban land and rivers often exist as distinct entities with limited material exchange. However, during rainfall, these two systems interconnect, resulting in the transfer of land-derived pollutants into rivers. Such transfer significantly increases river pollutant levels, adversely affecting water quality. Therefore, developing a water quality simulation and prediction model is crucial. This model should effectively illustrate pollutant movement and dispersion during rain events. This study proposes a comprehensive model that merges the Storm Water Management Model (SWMM) with the Environmental Fluid Dynamics Code (EFDC). This integrated model assesses the spread and dispersion of pollutants, including Ammonia Nitrogen (NH3-N), Total Phosphorus (TP), Total Nitrogen (TN), and Chemical Oxygen Demand (COD), within urban water cycles for various rainfall conditions, thus offering critical theoretical support for managing the water environment. The application of this model under different rainfall intensities (light, moderate and heavy) provides vital insights. During light rainfall, the river's natural purification process can sustain surface water quality at Class IV. Moderate rainfall causes accumulation of pollutants, reducing water quality to Class V. Conversely, heavy rainfall rapidly increases pollutant concentrations due to higher inflow, pushing the river to a degraded Class V status, which is beyond its natural purification capacity, necessitating engineering solutions to reattain Class IV quality. Furthermore, pollutant accumulation in downstream river sections is more influenced by flow rate than by rainfall intensity. In summary, the SWMM-EFDC integrated model proves highly effective in predicting river water quality, thereby significantly aiding urban water pollution control.

Effects of salt stress on soil enzyme activities and rhizosphere microbial structure in salt-tolerant and -sensitive soybean.

Salt is recognized as one of the most major factors that limits soybean yield in acidic soils. Soil enzyme activity and bacterial community have a critical function in improving the tolerance to soybean. Our aim was to assess the activities of soil enzyme, the structure of bacteria and their potential functions for salt resistance between Salt-tolerant (Salt-T) and -sensitive (Salt-S) soybean genotypes when subject to salt stress. Plant biomass, soil physicochemical properties, soil catalase, urease, sucrase, amylase, and acid phosphatase activities, and rhizosphere microbial characteristics were investigated in Salt-T and Salt-S soybean genotypes under salt stress with a pot experiment. Salt stress significantly decreased the soil enzyme activities and changed the rhizosphere microbial structure in a genotype-dependent manner. In addition, 46 ASVs which were enriched in the Salt-T geotype under the salt stress, such as ASV19 (Alicyclobacillus), ASV132 (Tumebacillus), ASV1760 (Mycobacterium) and ASV1357 (Bacillus), which may enhance the tolerance to soybean under salt stress. Moreover, the network structure of Salt-T soybean was simplified by salt stress, which may result in soil bacterial communities being susceptible to external factors. Salt stress altered the strength of soil enzyme activities and the assembly of microbial structure in Salt-T and Salt-S soybean genotypes. Na+, NO3--N, NH4+-N and Olsen-P were the most important driving factors in the structure of bacterial community in both genotypes. Salt-T genotypes enriched several microorganisms that contributed to enhance salt tolerance in soybeans, such as Alicyclobacillus, Tumebacillus, and Bacillus. Nevertheless, the simplified network structure of salt-T genotype due to salt stress may render its bacterial community structure unstable and susceptible.

Manipulating rhizosphere microorganisms to improve crop yield in saline-alkali soil: a study on soybean growth and development.

Introduction: Rhizosphere microorganisms can effectively promote the stress resistance of plants, and some beneficial rhizosphere microorganisms can significantly promote the growth of crops under salt stress, which has the potential to develop special microbial fertilizers for increasing the yield of saline-alkali land and provides a low-cost and environmentally friendly new strategy for improving the crop yield of saline-alkali cultivated land by using agricultural microbial technology. Methods: In May 2022, a field study in a completely randomized block design was conducted at the Heilongjiang Academy of Agricultural Sciences to explore the correlation between plant rhizosphere microorganisms and soybean growth in saline-alkali soil. Two soybean cultivars (Hening 531, a salt-tolerant variety, and 20_1846, a salt-sensitive variety) were planted at two experimental sites [Daqing (normal condition) and Harbin (saline-alkali conditions)], aiming to investigate the performance of soybean in saline-alkali environments. Results: Soybeans grown in saline-alkali soil showed substantial reductions in key traits: plant height (25%), pod number (26.6%), seed yield (33%), and 100 seed weight (13%). This underscores the unsuitability of this soil type for soybean cultivation. Additionally, microbial analysis revealed 43 depleted and 56 enriched operational taxonomic units (OTUs) in the saline-alkali soil compared to normal soil. Furthermore, an analysis of ion-associated microbes identified 85 mOTUs with significant correlations with various ions. A co-occurrence network analysis revealed strong relationships between specific mOTUs and ions, such as Proteobacteria with multiple ions. In addition, the study investigated the differences in rhizosphere species between salt-tolerant and salt-sensitive soybean varieties under saline-alkali soil conditions. Redundancy analysis (RDA) indicated that mOTUs in saline-alkali soil were associated with pH and ions, while mOTUs in normal soil were correlated with Ca2+ and K+. Comparative analyses identified significant differences in mOTUs between salt-tolerant and salt-sensitive varieties under both saline-alkali and normal soil conditions. Planctomycetes, Proteobacteria, and Actinobacteria were dominant in the bacterial community of saline-alkali soil, with significant enrichment compared to normal soil. The study explored the functioning of the soybean rhizosphere key microbiome by comparing metagenomic data to four databases related to the carbon, nitrogen, phosphorus, and sulfur cycles. A total of 141 KOs (KEGG orthologues) were identified, with 66 KOs related to the carbon cycle, 16 KOs related to the nitrogen cycle, 48 KOs associated with the phosphorus cycle, and 11 KOs linked to the sulfur cycle. Significant correlations were found between specific mOTUs, functional genes, and phenotypic traits, including per mu yield (PMY), grain weight, and effective pod number per plant. Conclusion: Overall, this study provides comprehensive insights into the structure, function, and salt-related species of soil microorganisms in saline-alkali soil and their associations with salt tolerance and soybean phenotype. The identification of key microbial species and functional categories offers valuable information for understanding the mechanisms underlying plant-microbe interactions in challenging soil conditions.

CD22 blockade modulates microglia activity to suppress neuroinflammation following intracerebral hemorrhage.

Microglia are first responders to acute brain insults and initiate neuroinflammation to drive secondary tissue injury. Yet the key molecular switches in control of the inflammatory activity of microglia remain poorly understood. Intracerebral hemorrhage (ICH) is a devastating stroke subtype whereby a hematoma is formed within the brain parenchyma and associated with high mortality. Using a mouse model of ICH, we found upregulation of CD22 that predominantly occurred in microglia. Antibody blockade of CD22 led to a reduction in neurological deficits, brain lesion and hematoma volume. This was accompanied by reduced inflammatory activity, increased expression of alternative activation markers (CD206 and IL-10) and enhanced phagocytosis activity in microglia after ICH. CD22 blockade also led to an increase of phosphorylated SYK and AKT after ICH. Notably, the benefits of CD22 blockade were ablated in ICH mice subjected to microglial depletion with a colony-stimulating factor 1 receptor inhibitor PLX5622. Additionally, the protective effects of CD22 blockade was diminished in ICH mice receiving a SYK inhibitor R406. Together, our findings highlight CD22 as a key molecular switch to control the detrimental effects of microglia after acute brain injury, and provide a novel strategy to improve the outcome of ICH injury.

Improving outcomes in intracerebral hemorrhage through microglia/macrophage-targeted IL-10 delivery with phosphatidylserine liposomes.

Intracerebral hemorrhage (ICH) remains the most lethal type of stroke, and effective clinical therapies that can speed up hematoma resolution after ICH are still lacking. While the beneficial effects of IL-10 on ICH recovery have been demonstrated, the clinical translation of IL-10 requires effective delivery methods by which sufficient IL-10 can be delivered to ICH-affected regions in the brain. Here we report the use of a phosphatidylserine (PS) liposome (PSL)-based nanoparticle system for microglia/macrophage-targeted delivery of IL-10 in ICH. We first prepared IL-10-conjugated PSL (PSL-IL10) and characterized their immunomodulating effects in vitro. Then we evaluated the therapeutic effects, including hematoma absorption, short-term outcomes, and neuroinflammation, of intranasally administered PSL-IL10 (3 µg IL-10 per mouse, 2 h post-ICH) in a collagenase-induced ICH mouse model. We also isolated microglia/macrophages from the mouse brains with ICH to analyze their morphology, phagocytosis ability, and polarization. Our study reveals that, 1) PSL-IL10 treatment resulted in significantly improved outcomes and accelerated hematoma resolution in the acute phase of ICH; 2) PSL-IL10 inhibited glial activation and down-regulated pro-inflammatory cytokine production; 3) PSL-IL10 induced Iba1+ cells with a stronger phagocytosis ability; 4) PSL-IL10 activated STAT3 and upregulated CD36 expression in microglia/macrophage. These findings collectively show that PSL-IL10 is a promising nanotherapeutic for effectively ameliorating ICH.

Cultivation model and deficit irrigation strategy for reducing leakage of bundle sheath cells to CO2, improve 13C carbon isotope, photosynthesis and soybean yield in semi-arid areas.

A better understanding of the photosynthesis and soil water storage regulation of soybean production will be helpful to develop a water conservation strategy under a rain-fed farming system. Reducing the leakage of CO2 bundle sheath cells and improving the photosynthesis capacity and gas exchange characteristics of soybean leaves will contribute to increase yield under the dryland agricultural system and provide a scientific basis. Therefore, during 2019 and 2020, soybean exposed to different cultivation modes to analyze the response curves of photosynthesis and CO2 under different deficit irrigation strategies. In this study, we used two cultivation models: RB: ridge covered with biodegradable film and furrow area not covered; CF: conventional flat land planting under four deficit irrigation modes (R: rainwater irrigation; IB: branch stage irrigation (220 mm); IP: Irrigation during podding (220 mm); IBP: branch stage irrigation (110 mm), podding stage irrigation (110 mm). Compared with CF-IBP treatment, RB-IBP had significant effects on rainwater collection, SWS, and soybean yield. Photo-response curve analysis showed that RB-IBP treatment a significant increase in Pn, Gs, Ci, Tr, leaf WUE, and chlorophyll ab content. Under different irrigation strategies, maximum net photosynthetic rate (Pnmax), light saturation point (LSP), and apparent quantum efficiency under RB-IBP treatment (α), Pn under respiration rate and CO2 response curve were significantly higher than that under CF cultivation mode. Compared with RB culture mode under different irrigation strategies, CF cultivation mode significantly increases Δ13C and CO2 sheath cell leakage (Փ); it also led to a significant decline in the ratio of Ci/Ca concentration. This study shows that RB-IBP treatment is the best water-saving strategy because it means reducing the leakage of CO2 from the bundle sheath, thus significantly increasing soil water storage, photosynthetic capacity, and soybean yield.

ZmG6PDH1 in glucose-6-phosphate dehydrogenase family enhances cold stress tolerance in maize.

Glucose-6-phosphate dehydrogenase (G6PDH) is a key enzyme in the pentose phosphate pathway responsible for the generation of nicotinamide adenine dinucleotide phosphate (NADPH), thereby playing a central role in facilitating cellular responses to stress and maintaining redox homeostasis. This study aimed to characterize five G6PDH gene family members in maize. The classification of these ZmG6PDHs into plastidic and cytosolic isoforms was enabled by phylogenetic and transit peptide predictive analyses and confirmed by subcellular localization imaging analyses using maize mesophyll protoplasts. These ZmG6PDH genes exhibited distinctive expression patterns across tissues and developmental stages. Exposure to stressors, including cold, osmotic stress, salinity, and alkaline conditions, also significantly affected the expression and activity of the ZmG6PDHs, with particularly high expression of a cytosolic isoform (ZmG6PDH1) in response to cold stress and closely correlated with G6PDH enzymatic activity, suggesting that it may play a central role in shaping responses to cold conditions. CRISPR/Cas9-mediated knockout of ZmG6PDH1 on the B73 background led to enhanced cold stress sensitivity. Significant changes in the redox status of the NADPH, ascorbic acid (ASA), and glutathione (GSH) pools were observed after exposure of the zmg6pdh1 mutants to cold stress, with this disrupted redox balance contributing to increased production of reactive oxygen species and resultant cellular damage and death. Overall, these results highlight the importance of cytosolic ZmG6PDH1 in supporting maize resistance to cold stress, at least in part by producing NADPH that can be used by the ASA-GSH cycle to mitigate cold-induced oxidative damage.

Research on the Optimal Regulation of Sudden Water Pollution.

For the needs of the whole region's emergency regulation of the nullah sudden water pollution event, the emergency regulation strategy of the accident section and upstream and downstream of the sudden water pollution event is studied. For the accident section, the duration of the whole emergency event is calculated using the parameter quantification method; for the upstream of the accident section, the NSGA-II is used to adjust the gate opening to ensure the water level stability of the upstream pools; for the downstream section, the optimized partition method is used to identify the unfavorable pools and close the unfavorable pool to extend the water supply time. Based on the example of an emergency event in the section of the Liyanghe gate-Guyunhe gate of the middle line project, the research results are as follows: the accident section is identified as the Xiaohe gate-Hutuohe gate, the upstream of the accident section is the Liyanghe gate-Xiaohe gate, and the downstream of the accident section is the Hutuohe gate-Gangtou Tunnel gate. The duration of the emergency event in the accident section is 7.9 h; the maximum average water level deviation before the gate upstream of the accident section is 0.05 m; two unfavorable canal pools are identified in the stream of the accident section, and the water supply time of the unfavorable pools is extended by 6.13 and 5.61 d.

Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat.

Neural communication networks form the fundamental basis for brain function. These communication networks are enabled by emitted ligands such as neurotransmitters, which activate receptor complexes to facilitate communication. Thus, neural communication is fundamentally dependent on the transcriptome. Here we develop NeuronChat, a method and package for the inference, visualization and analysis of neural-specific communication networks among pre-defined cell groups using single-cell expression data. We incorporate a manually curated molecular interaction database of neural signaling for both human and mouse, and benchmark NeuronChat on several published datasets to validate its ability in predicting neural connectivity. Then, we apply NeuronChat to three different neural tissue datasets to illustrate its functionalities in identifying interneural communication networks, revealing conserved or context-specific interactions across different biological contexts, and predicting communication pattern changes in diseased brains with autism spectrum disorder. Finally, we demonstrate NeuronChat can utilize spatial transcriptomics data to infer and visualize neural-specific cell-cell communication.

A Study of Strength Parameter Evolution and a Statistical Damage Constitutive Model of Cemented Sand and Gravel.

Cemented sand and gravel (CSG) has a wide range of applications in dam construction, and its properties are between rockfill and roller compacted concrete (RCC). A difference in gel content will result in a variance in CSG's structure and mechanical properties. To investigate the intricate structural mechanical properties of CSG, this study conducted a series of laboratory tests and associated discrete element analyses. Accordingly, the evolution law of the strength parameters of CSG is explored and a statistical damage constitutive model suitable for CSG is established. The main contributions of this study are as follows: (1) The failure mechanism of the CSG was described from the microscopic level, and the evolution law of the strength parameter cohesion and friction angle of the CSG was analyzed and summarized. (2) Based on the particle flow model, the energy development law and the spatiotemporal distribution law of acoustic emission (AE) provide illustrations of the strain hardening-softening transition features and the interaction between cohesion and friction of CSG. (3) The evolution function between the strength parameter and the strain softening parameter was built, and the critical strain softening parameter was determined by the microcrack evolution law of the particle flow model. (4) The accuracy of the evolution curve was confirmed by comparing it to experimental results. (5) Based on the relationship between cohesion loss and material damage, a statistical damage constitutive model was developed using the improved Mohr-Coulomb strength criterion as the micro strength function. The constitutive model can accurately describe the stress-strain curves of CSG with different gel content. Furthermore, the model reflects the strain hardening-softening properties of CSG and reveals the relationship between the weakening of cohesion and material damage at the microscopic level. These findings provide valuable guidelines for investigating the damage laws and microcosmic failure features of CSG and other relevant materials.

Inferring neuron-neuron communications from single-cell transcriptomics through NeuronChat.

Neural communication networks form the fundamental basis for brain function. These communication networks are enabled by emitted ligands such as neurotransmitters, which activate receptor complexes to facilitate communication. Thus, neural communication is fundamentally dependent on the transcriptome. Here we develop NeuronChat, a method and package for the inference, visualization and analysis of neural-specific communication networks among pre-defined cell groups using single-cell expression data. We incorporate a manually curated molecular interaction database of neural signaling for both human and mouse, and benchmark NeuronChat on several published datasets to validate its ability in predicting neural connectivity. Then, we apply NeuronChat to three different neural tissue datasets to illustrate its functionalities in identifying interneural communication networks, revealing conserved or context-specific interactions across different biological contexts, and predicting communication pattern changes in diseased brains with autism spectrum disorder. Finally, we demonstrate NeuronChat can utilize spatial transcriptomics data to infer and visualize neural-specific cell-cell communication.

Planting models and deficit irrigation strategies to improve radiation use efficiency, dry matter translocation and winter wheat productivity under semi-arid regions.

The dry-land farming system of China relies on plastic film mulching and natural rainfall to mitigate damage caused by drought. However, the applications of deficit irrigation modes combined with the planting models can significantly increase production of wheat, dry matter translocation and radiation use efficiency (RUE) remains unidentified. Thus, in 2016-2018, we conducted field trials that implemented four deficit irrigation modes (IJF: irrigation at jointing and flowering stages; IF: irrigation at flowering stage; IJ: irrigation at jointing stage; NI: no irrigation) under two cultivation patterns (ridge furrow rainfall harvesting system (RF); traditional flat cultivation (TF)). The results indicated that the effects of RF system with deficit irrigation (IJF: 250 mm) could significantly increase the soil moisture, and thus enhanced LAI, In value, IPAR, RUE, and PAR capture ratio than that of TF-NI planting. This is due to decreased canopy light transmittance (LT), reflection and penetration ratio of PAR, as a result considerable improve the biomass translocation and grain yield. Owing to the very low soil water content after the seed-filling, the LAI, IPAR, and In value decreased during the seed-filling under water stress, ultimately affecting the dry matter translocation efficiency. While the IJF and IF treatments provided water for reproductive growth stage, therefore, the production of wheat and RUE were significantly maximum compared with IJ and NI irrigation mode. Under the RF system with IJF, IF, and IJ treatments the grain yield increased by 81.2%, 56.8%, 45.6% and 17.2%, then that of TF-NI treatment, respectively. The highest RUE (1.93 g MJ-1), dry-matter translocation (154.2%) and seed yield (81.2%) were obtained in the RF-IJF treatment compared with TF-NI. Therefore, the RF-IJF treatment significantly improved the earlier development and rapid plant growth, which is a suitable planting model for increasing soil moisture, LAI, RUE, DMT, and winter wheat production.

A novel aged mouse model of recurrent intracerebral hemorrhage in the bilateral striatum.

The current animal models of stroke primarily model a single intracerebral hemorrhage (ICH) attack, and there is a lack of a reliable model of recurrent ICH. In this study, we established 16-month-old C57BL/6 male mouse models of ICH by injecting collagenase VII-S into the left striatum. Twenty-one days later, we injected collagenase VII-S into the right striatum to simulate recurrent ICH. Our results showed that mice subjected to bilateral striatal hemorrhage had poorer neurological function at the early stage of hemorrhage, delayed recovery in locomotor function, motor coordination, and movement speed, and more obvious emotional and cognitive dysfunction than mice subjected to unilateral striatal hemorrhage. These findings indicate that mouse models of bilateral striatal hemorrhage can well simulate clinically common recurrent ICH. These models should be used as a novel tool for investigating the pathogenesis and treatment targets of recurrent ICH.

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM.

Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

Genetic dissection of the soybean dwarf mutant dm with integrated genomic, transcriptomic and methylomic analyses.

Plant height affects crop production and breeding practices, while genetic control of dwarfism draws a broad interest of researchers. Dwarfism in soybean (Glycine max) is mainly unexplored. Here, we characterized a dwarf mutant dm screened from ethyl methanesulfonate (EMS) mutated seeds of the soybean cultivar Zhongpin 661(ZP). Phenotypically, dm showed shorter and thinner stems, smaller leaves, and more nodes than ZP under greenhouse conditions. Genetically, whole-genome sequencing and comparison revealed that 210K variants of SNPs and InDel in ZP relative to the soybean reference genome Williams82, and EMS mutagenesis affected 636 genes with variants predicted to have a large impact on protein function in dm. Whole-genome methylation sequencing found 704 differentially methylated regions in dm. Further whole-genome RNA-Seq based transcriptomic comparison between ZP and dm leaves revealed 687 differentially expressed genes (DEGs), including 263 up-regulated and 424 down-regulated genes. Integrated omics analyses revealed 11 genes with both differential expressions and DNA variants, one gene with differential expression and differential methylation, and three genes with differential methylation and sequence variation, worthy of future investigation. Genes in cellulose, fatty acids, and energy-associated processes could be the key candidate genes for the dwarf phenotype. This study provides genetic clues for further understanding of the genetic control of dwarfism in soybean. The genetic resources could help to inbreed new cultivars with a desirable dwarf characteristic.

Locally correlated kinetics of post-replication DNA methylation reveals processivity and region specificity in DNA methylation maintenance.

DNA methylation occurs predominantly on cytosine-phosphate-guanine (CpG) dinucleotides in the mammalian genome, and the methylation landscape is maintained over mitotic cell division. It has been posited that coupling of maintenance methylation activity among neighbouring CpGs is critical to stability over cellular generations; however, the mechanism is unclear. We used mathematical models and stochastic simulation to analyse data from experiments that probe genome-wide methylation of nascent DNA post-replication in cells. We find that DNA methylation maintenance rates on individual CpGs are locally correlated, and the degree of this correlation varies by genomic regional context. By using theory of protein diffusion along DNA, we show that exponential decay of methylation rate correlation with genomic distance is consistent with enzyme processivity. Our results provide quantitative evidence of genome-wide methyltransferase processivity in vivo. We further developed a method to disentangle different mechanistic sources of kinetic correlations. From the experimental data, we estimate that an individual methyltransferase methylates neighbour CpGs processively if they are 36 basepairs apart, on average. But other mechanisms of coupling dominate for longer inter-CpG distances. Our study demonstrates that quantitative insights into enzymatic mechanisms can be obtained from replication-associated, cell-based genome-wide measurements, by combining data-driven statistical analyses with hypothesis-driven mathematical modelling.

Soybean genetic resources contributing to sustainable protein production.

KEY MESSAGE: Genetic resources contributes to the sustainable protein production in soybean. Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.