Mapping of major QTL and candidate gene analysis for hull colour in foxtail millet (Setaria italica (L.) P. Beauv.).

BACKGROUND: Hull colour is an important morphological marker for selection in seed production of foxtail millet. However, the molecular mechanisms underlying hull colour variation remain unknown. RESULTS: An F7 recombinant inbred line (RIL) population containing 215 lines derived from Hongjiugu × Yugu18 was used to analyze inheritance and detect the quantitative trait loci (QTL) for four hull colour traits using major gene plus polygene mixed inheritance analysis and composite interval mapping (CIM) in four environments. Genetic analysis revealed that the hull colour L* value (HCL*) was controlled by two major genes plus additive polygenes, the hull colour a* value (HCa*) was controlled by three major genes, the hull colour b* value (HCb*) was controlled by two major genes plus polygenes, and the hull colour C* value (HCC*) was controlled by four major genes. A high-density genetic linkage map covering 1227.383 cM of the foxtail millet genome, with an average interval of 0.879 cM between adjacent bin markers, was constructed using 1420 bin markers. Based on the genetic linkage map and the phenotypic data, a total of 39 QTL were detected for these four hull colour traits across four environments, each explaining 1.50%-49.20% of the phenotypic variation. Of these, six environmentally stable major QTL were co-localized to regions on chromosomes 1 and 9, playing a major role in hull colour. There were 556 annotated genes within the two QTL regions. Based on the functions of homologous genes in Arabidopsis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) gene annotations, five genes were predicted as candidate genes for further studies. CONCLUSIONS: This is the first study to use an inheritance model and QTL mapping to determine the genetic mechanisms of hull colour trait in foxtail millet. We identified six major environmentally stable QTL and predicted five potential candidate genes to be associated with hull colour. These results advance the current understanding of the genetic mechanisms underlying hull colour traits in foxtail millet and provide additional resources for application in genomics-assisted breeding and potential isolation and functional characterization of the candidate genes.

DMBT1 Alleviates Nasal Airway Inflammatory Response in the LPS-Induced Nasal Polyp Model.

INTRODUCTION: The aim of this study was to investigate the effects and mechanism of deleted in malignant brain tumors 1 (DMBT1) protein on the mouse model of nasal polyps. METHODS: The mouse model of nasal polyps was induced by intranasal drip intervention of lipopolysaccharide (LPS) 3 times a week for 12 weeks. A total of 42 mice were randomly divided into blank group, LPS group, and LPS+DMBT1 group. DMBT1 protein was applied by intranasal drip intervention in each nostril after LPS. After 12 weeks, 5 mice in each group were randomly picked for the mouse olfactory disorder experiment, 3 mice were randomly picked for histopathological observation of nasal mucosa, 3 mice for olfactory marker protein (OMP) immunofluorescence analysis and the last 3 mice were grabbed for nasal lavage, and the levels of cytokines interleukin (IL)-4, IL-5, IL-13, and phosphatidylinositide 3-kinases (PI3K) in the nasal lavage fluid were detected by enzyme-linked immunosorbent assay (ELISA). RESULTS: Compared with the blank group, mice in LPS group had olfactory dysfunction, the level of OMP was significantly reduced, the nasal mucosa was swollen, discontinuous, and contained a large number of inflammatory cells. The levels of IL-4, IL-5, IL-13, and PI3K in the nasal lavage fluid were significantly increased in LPS group (p < 0.01). Compared with the LPS group, the number of mice with olfactory dysfunction in the LPS+DMBT1 group was less, the infiltration of inflammatory cells was reduced, the OMP-positive cells were significantly increased, and the IL-4, IL-5, IL-13, and PI3K in the nasal lavage fluid were significantly increased, p < 0.01. CONCLUSIONS: DMBT1 protein alleviates the nasal airway inflammatory response in the mouse nasal polyp model, and the mechanism may be through the PI3K-AKT signaling pathway.

Design and Psychophysical Evaluation of a Novel Wearable Upper-Arm Tactile Display Device.

A novel wearable upper arm tactile display device, which can simultaneously provide three types of tactile stimuli (i.e., squeezing, stretching, and vibration) is presented. The squeezing and stretching stimulation of the skin is generated by two motors simultaneously driving the nylon belt in the opposite and the same direction, respectively. In addition, four evenly spaced vibration motors are fixed around the user's arm by an elastic nylon band. There is also a unique structural design for assembling the control module and actuator, powered by two lithium batteries, making it portable and wearable. Psychophysical experiments are conducted to investigate the effect of interference on the perception of squeezing and stretching stimulation by this device. Results show that (1) different tactile stimuli actually interfere with the user's perception compared to the case where only one stimulus is applied to the user; (2) the squeezing has a considerable impact on the stretch just noticeable difference (JND) values when both stimuli are exerted on the user, and when the squeezing is strong, while the impact of stretch on the squeezing JND values is negligible.

Event-Triggered Sliding Mode Neural Network Controller Design for Heterogeneous Multi-Agent Systems.

A class of heterogeneous second-order multi-agent consensus problems is studied, in which an event-triggered method is used to improve the feasibility of the control protocol. The sliding mode control method is used to achieve the robustness of the system. A special type of general radial basis function neural network is applied to estimate the uncertainties. The event-triggered mechanism is introduced to reduce the update frequency of the controller and the communication frequency among the agents. Zeno behavior is avoided by ensuring a lower bound between two adjacent trigger instants. Finally, the simulation results are provided to demonstrate that the time evolution of consensus errors eventually approaches zero. The consensus of multi-agent systems is achieved.

Effect of environment and variety on the physicochemical properties of Tartary buckwheat starch.

BACKGROUND: Starch is a major nutrient in the human diet and has been widely used as an ingredient in many food and non-food applications. However, the research on the quality characteristics of Tartary buckwheat is lagging behind, and there is a lack of high-quality special varieties, which makes it difficult to become a popular food. The physicochemical properties of Tartary buckwheat starch may be affected by different environments and varieties, and the stability of planted varieties in different regions is also an important issue in current research. RESULTS: The average amylose content and pasting properties of Dingxi Tartary buckwheat were lower, while the solubility, transparency, relative crystallinity and gelatinization enthalpy were higher compared with the other two regions, and there were significant differences between different varieties. All samples showed typical A-type structure, and the starch short-range order structure changed slightly. Amylose content, solubility, transparency, granule size distribution, pasting properties and thermal properties were significantly affected by environment and variety. CONCLUSION: When choosing high-quality special varieties and products for processing, it contributes to select different buckwheat varieties and planting areas based on various objectives by understanding the effects of environment and varieties on the physicochemical properties of Tartary buckwheat starch. In this study, the four varieties planted in Dingxi and the two varieties in Zhaojue were easy to digest, and the differences of pasting properties and thermal properties are helpful to improve the application of Tartary buckwheat starch in the food industry. © 2023 Society of Chemical Industry.

The accelerated aging skin in rhino-like SHJHhr mice.

SHJHhr mice line is rhino-like mice with a nonsense Hairless (Hr) mutant, which shows the characteristic of shedding hair and wrinkled skin with increasing age. Through histological analysis and aging indexes detection, SHJHhr mice show an increased thickness skin with degraded hair follicle and dermal cysts and disorganized collagen fibres, as well as decreased level of Hyp. Meanwhile, the aging markers p16 and p21 are significantly higher in SHJHhr mouse skin than ICR mouse skin at same age. Moreover, the data of MDA and SOD show a higher oxidative stress in SHJHhr mouse skin, and the levels of Nrf2 and its targets are significantly downregulated, which suggests SHJHhr mice have a faster aging skin and its reason maybe poor antioxidative protection. Overall, this study shows SHJHhr mice with an accelerated aging skin, which suggests the role of Hr gene in skin aging.

Therapeutic reversal of Huntington's disease by in vivo self-assembled siRNAs.

Huntington's disease is an autosomal-dominant neurodegenerative disease caused by CAG expansion in exon 1 of the huntingtin (HTT) gene. Since mutant huntingtin (mHTT) protein is the root cause of Huntington's disease, oligonucleotide-based therapeutic approaches using small interfering RNAs (siRNAs) and antisense oligonucleotides designed to specifically silence mHTT may be novel therapeutic strategies for Huntington's disease. Unfortunately, the lack of an effective in vivo delivery system remains a major obstacle to realizing the full potential of oligonucleotide therapeutics, especially regarding the delivery of oligonucleotides to the cortex and striatum, the most severely affected brain regions in Huntington's disease. In this study, we present a synthetic biology strategy that integrates the naturally existing exosome-circulating system with artificial genetic circuits for self-assembly and delivery of mHTT-silencing siRNA to the cortex and striatum. We designed a cytomegalovirus promoter-directed genetic circuit encoding both a neuron-targeting rabies virus glycoprotein tag and an mHTT siRNA. After being taken up by mouse livers after intravenous injection, this circuit was able to reprogramme hepatocytes to transcribe and self-assemble mHTT siRNA into rabies virus glycoprotein-tagged exosomes. The mHTT siRNA was further delivered through the exosome-circulating system and guided by a rabies virus glycoprotein tag to the cortex and striatum. Consequently, in three mouse models of Huntington's disease treated with this circuit, the levels of mHTT protein and toxic aggregates were successfully reduced in the cortex and striatum, therefore ameliorating behavioural deficits and striatal and cortical neuropathologies. Overall, our findings establish a convenient, effective and safe strategy for self-assembly of siRNAs in vivo that may provide a significant therapeutic benefit for Huntington's disease.

The global transmission of new coronavirus variants.

Coronavirus Disease 2019 (COVID-19) has caused tremendous losses to the world. This study addresses the impact and diffusion of the five major new coronavirus variants namely Alpha, Beta, Gamma, Eta, and Delta lineage. The results of this study indicate that Africa and Europe will be affected by new coronavirus variants the most compared with other continents. The comparative analysis indicates that vaccination can contain the spread of the virus in most of the continent, and non-pharmaceutical interventions (NPIs), such as restriction on gatherings and close public transport, will effectively curb the pandemic, especially in densely populated continents. According to our Global Prediction System of COVID-19 Pandemic, the diffusion of delta lineage in the US shows seasonal oscillation characteristics, and the first wave will occur in October 2021, with the record of 323,360, and followed by a small resurgence in April 2022, with the record of 184,196, while the second wave will reach to 232,622 cases in October 2022. Our study will raise the awareness of new coronavirus variants among the public, and will help the governments make appropriate directives to cope with the new coronavirus variants.

Targeted neutrophil-mimetic liposomes promote cardiac repair by adsorbing proinflammatory cytokines and regulating the immune microenvironment.

Acute myocardial infarction (MI) induces a sterile inflammatory response that may result in poor cardiac remodeling and dysfunction. Despite the progress in anti-cytokine biologics, anti-inflammation therapy of MI remains unsatisfactory, due largely to the lack of targeting and the complexity of cytokine interactions. Based on the nature of inflammatory chemotaxis and the cytokine-binding properties of neutrophils, we fabricated biomimetic nanoparticles for targeted and broad-spectrum anti-inflammation therapy of MI. By fusing neutrophil membranes with conventional liposomes, we fabricated biomimetic liposomes (Neu-LPs) that inherited the surface antigens of the source cells, making them ideal decoys of neutrophil-targeted biological molecules. Based on their abundant chemokine and cytokine membrane receptors, Neu-LPs targeted infarcted hearts, neutralized proinflammatory cytokines, and thus suppressed intense inflammation and regulated the immune microenvironment. Consequently, Neu-LPs showed significant therapeutic efficacy by providing cardiac protection and promoting angiogenesis in a mouse model of myocardial ischemia-reperfusion. Therefore, Neu-LPs have high clinical translation potential and could be developed as an anti-inflammatory agent to remove broad-spectrum inflammatory cytokines during MI and other neutrophil-involved diseases.

Targeted delivery and ROS-responsive release of Resolvin D1 by platelet chimeric liposome ameliorates myocardial ischemia-reperfusion injury.

Resolvin D1 (RvD1) has been shown to provide effective protection against ischemia-reperfusion injury in multiple vital organs such as the heart, brain, kidney. However, the clinical translational potential of systemic administration of RvD1 in the treatment of ischemia-reperfusion injury is greatly limited due to biological instability and lack of targeting ability. Combining the natural inflammatory response and reactive oxygen species (ROS) overproduction after reperfusion injury, we developed a platelet-bionic, ROS-responsive RvD1 delivery platform. The resulting formulation enables targeted delivery of RvD1 to the injury site by hijacking circulating chemotactic monocytes, while achieving locally controlled release. In a mouse model of myocardial ischemia repefusuin (MI/R) injury, intravenous injection of our formula resulted in the enrichment of RvD1 in the injured area, which in turn promotes clearance of dead cells, production of specialized proresolving mediators (SPMs), and angiogenesis during injury repair, effectively improving cardiac function. This delivery system integrates drug bio-protection, targeted delivery and controlled release, which endow it with great clinical translational value.

Effect of the increase rate of blood lipid concentration during pregnancy on the adverse pregnancy outcomes: a cohort study of 1051 singleton pregnancy.

OBJECTIVE: To investigate the effects of blood lipid concentration and blood lipid growth rate in the first and third trimesters of pregnancy on adverse pregnancy outcomes. METHODS: The study subjects were 1051 singleton pregnant women who established archives in Chengdu Maternity and Child Specialty Hospital. The pregnancy information was continuously recorded until the pregnant woman gave birth, and lipid biochemical indicators were performed every three months. RESULTS: The average age of the pregnant women recruited was 27.82 ± 3.07 years. Compared with the first trimester, the concentration of triglyceride, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol in the third trimester were increased significantly (all p < .05). The growth rate of triglyceride was closely related to the occurrence of gestational diabetes mellitus and large for gestational, and the growth rate of total cholesterol and low-density lipoprotein cholesterol was closely related to gestational diabetes mellitus and cholestasis of pregnancy. For every unit increase in triglyceride growth rate, the risk of gestational diabetes mellitus and large for gestational age increases by 1.237 times and 1.317 times, respectively. CONCLUSION: Among non-high-risk pregnant women, blood lipid concentration is generally high among pregnant women with complications during pregnancy. It is necessary to combine a single blood lipid test concentration during pregnancy with the blood lipid growth rate to assess the condition of pregnant women and provide better guidance during pregnancy.

Bearing Fault Diagnosis Based on Randomized Fisher Discriminant Analysis.

In this paper, a novel randomized Fisher discriminant analysis (RFDA) based bearing fault diagnosis method is proposed. First, several representative time-domain features are extracted from the raw vibration signals. Second, linear Fisher discriminant analysis (FDA) is extended to nonlinear FDA named RFDA by introducing the random feature map to deal with the non-linearity issue. Specifically, the extracted time-domain features data are mapped onto a high-dimensional space using the random feature map function rather than kernel functions. Third, the time-domain features are fed into the built RFDA model to extract the discriminant features for diagnosis. Moreover, a Bayesian inference is employed to identify the class of the collected vibration signals to diagnose the bearing status. The proposed method uses random Fourier features to approximate the kernel matrix in the kernel Fisher discriminant analysis. Through employing randomized Fisher discriminant analysis, the nonlinearity issue is dealt with, and the computational burden is remarkably reduced compared to the kernel Fisher discriminant analysis (KFDA). To illustrate the superior performance of the proposed RFDA-based bearing fault diagnosis method, comparative experiments are conducted on two widely used datasets, the Case Western Reserve University (CWRU) bearing dataset and the Paderborn University (PU) bearing dataset. For the CWRU dataset, the computation time of RFDA is much shorter than KFDA, while the accuracy rate reaches the same level of KFDA. For the PU dataset, the accuracy rate of RFDA is slightly higher than KFDA, and the computation time is only 44.14% of KFDA.

Conuping BSA-Seq and RNA-Seq Reveal the Molecular Pathway and Genes Associated with the Plant Height of Foxtail Millet (Setaria italica).

Foxtail millet (Setaria italica) plays an important role in C4 crop research and agricultural development in arid areas due to its short growth period, drought tolerance, and barren tolerance. Exploration of the dwarfing mechanism and the dwarf genes of foxtail millet can provide a reference for dwarf breeding and dwarf research of other C4 crops. In this study, genetic analysis was performed using phenotypic data, candidate genes were screened by bulk segregant analysis sequencing (BSA-Seq); differentially expressed genes and metabolic pathways in different strains of high samples were analyzed by RNA sequencing (RNA-Seq). The association analysis of BSA-Seq and RNA-Seq further narrowed the candidate range. As a result, a total of three quantitative trait loci (QTLs) and nine candidate genes related to plant height were obtained on chromosomes I and IX. Based on the functional prediction of the candidate genes, we propose a hypothetical mechanism for the formation of millet dwarfing, in which, metabolism and MAPK signaling play important roles in the formation of foxtail millet plant height.

Bearing-Fault Diagnosis with Signal-to-RGB Image Mapping and Multichannel Multiscale Convolutional Neural Network.

Deep learning bearing-fault diagnosis has shown strong vitality in recent years. In industrial practice, the running state of bearings is monitored by collecting data from multiple sensors, for instance, the drive end, the fan end, and the base. Given the complexity of the operating conditions and the limited number of bearing-fault samples, obtaining complementary fault features using the traditional fault-diagnosis method, which uses statistical characteristic in time or frequency, is difficult and relies heavily on prior knowledge. In addition, intelligent bearing-fault diagnosis based on a convolutional neural network (CNN) has several deficiencies, such as single-scale fixed convolutional kernels, excessive dependence on experts' experience, and a limited capacity for learning a small training dataset. Considering these drawbacks, a novel intelligent bearing-fault-diagnosis method based on signal-to-RGB image mapping (STRIM) and multichannel multiscale CNN (MCMS-CNN) is proposed. First, the signals from three different sensors are converted into RGB images by the STRIM method to achieve feature fusion. To extract RGB image features effectively, the proposed MCMS-CNN is established, which can automatically learn complementary and abundant features at different scales. By increasing the width and decreasing the depth of the network, the overfitting caused by the complex network for a small dataset is eliminated, and the fault classification capability is guaranteed simultaneously. The performance of the method is verified through the Case Western Reserve University's (CWRU) bearing dataset. Compared with different DL approaches, the proposed approach can effectively realize fault diagnosis and substantially outperform other methods.

Protective effect of HINT2 on mitochondrial function via repressing MCU complex activation attenuates cardiac microvascular ischemia-reperfusion injury.

Current evidence indicates that coronary microcirculation is a key target for protecting against cardiac ischemia-reperfusion (I/R) injury. Mitochondrial calcium uniporter (MCU) complex activation and mitochondrial calcium ([Ca2+]m) overload are underlying mechanisms involved in cardiovascular disease. Histidine triad nucleotide-binding 2 (HINT2) has been reported to modulate [Ca2+]m via the MCU complex, and our previous work demonstrated that HINT2 improved cardiomyocyte survival and preserved heart function in mice with cardiac ischemia. This study aimed to explore the benefits of HINT2 on cardiac microcirculation in I/R injury with a focus on mitochondria, the MCU complex, and [Ca2+]m overload in endothelial cells. The present work demonstrated that HINT2 overexpression significantly reduced the no-reflow area and improved microvascular perfusion in I/R-injured mouse hearts, potentially by promoting endothelial nitric oxide synthase (eNOS) expression and phosphorylation. Microvascular barrier function was compromised by reperfusion injury, but was repaired by HINT2 overexpression via inhibiting VE-Cadherin phosphorylation at Tyr731 and enhancing the VE-Cadherin/ß-Catenin interaction. In addition, HINT2 overexpression inhibited the inflammatory response by suppressing vascular cell adhesion molecule-1 (VCAM-1) and intercellular adhesion molecule-1 (ICAM-1). Mitochondrial fission occurred in cardiac microvascular endothelial cells (CMECs) subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) injury and resulted in mitochondrial dysfunction and mitochondrion-dependent apoptosis, the effects of which were largely relieved by HINT2 overexpression. Additional experiments confirmed that [Ca2+]m overload was an initiating factor for mitochondrial fission and that HINT2 suppressed [Ca2+]m overload via modulation of the MCU complex through directly interacting with MCU in CMECs. Regaining [Ca2+]m overload by spermine, an MCU agonist, abolished all the protective effects of HINT2 on OGD/R-injured CMECs and I/R-injured cardiac microcirculation. In conclusion, the present report demonstrated that HINT2 overexpression inhibited MCU complex-mitochondrial calcium overload-mitochondrial fission and apoptosis pathway, and thereby attenuated cardiac microvascular ischemia-reperfusion injury.

Detection of Specific Building in Remote Sensing Images Using a Novel YOLO-S-CIOU Model. Case: Gas Station Identification.

The specific building is of great significance in smart city planning, management practices, or even military use. However, traditional classification or target identification methods are difficult to distinguish different type of buildings from remote sensing images, because the characteristics of the environmental landscape around the buildings (like the pixels of the road and parking area) are complex, and it is difficult to define them with simple rules. Convolution neural networks (CNNs) have a strong capacity to mine information from the spatial context and have been used in many tasks of image processing. Here, we developed a novel CNN model named YOLO-S-CIOU, which was improved based on YOLOv3 for specific building detection in two aspects: (1) module Darknet53 in YOLOv3 was replaced with SRXnet (constructed by superimposing multiple SE-ResNeXt) to significantly improve the feature learning ability of YOLO-S-CIOU while maintaining the similar complexity as YOLOv3; (2) Complete-IoU Loss (CIoU Loss) was used to obtain a better regression for the bounding box. We took the gas station as an example. The experimental results on the self-made gas station dataset (GS dataset) showed YOLO-S-CIOU achieved an average precision (AP) of 97.62%, an F1 score of 97.50%, and had 59,065,366 parameters. Compared with YOLOv3, YOLO-S-CIOU reduced the parameters' number by 2,510,977 (about 4%) and improved the AP by 2.23% and the F1 score by 0.5%. Moreover, in gas stations detection in Tumshuk City and Yanti City, the recall (R) and precision (P) of YOLO-S-CIOU were 50% and 40% higher than those of YOLOv3, respectively. It showed that our proposed network had stronger robustness and higher detection ability in remote sensing image detection of different regions.

Bearing Fault Diagnosis via Improved One-Dimensional Multi-Scale Dilated CNN.

Bearings are the key and important components of rotating machinery. Effective bearing fault diagnosis can ensure operation safety and reduce maintenance costs. This paper aims to develop a novel bearing fault diagnosis method via an improved multi-scale convolutional neural network (IMSCNN). In traditional convolutional neural network (CNN), a fixed convolutional kernel is often employed in the convolutional layer. Thus, informative features can not be fully extracted for fault diagnosis. In the proposed IMSCNN, a 1D dimensional convolutional layer is used to mitigate the effect of noise contained in vibration signals. Then, four dilated convolutional kernels with different dilation rates are integrated to extract multi-scale features through the inception structure. Experimental results from the popular CWRU and PU datasets show the superiority of the proposed method by comparison with other related methods.

Leaf Transcriptome Analysis of Broomcorn Millet Uncovers Key Genes and Pathways in Response to Sporisorium destruens.

Broomcorn millet (Panicum miliaceum L.) affected by smut (caused by the pathogen Sporisorium destruens) has reduced production yields and quality. Determining the tolerance of broomcorn millet varieties is essential for smut control. This study focuses on the differences in the phenotypes, physiological characteristics, and transcriptomes of resistant and susceptible broomcorn millet varieties under Sporisorium destruens stress. In diseased broomcorn millet, the plant height and stem diameter were reduced, while the number of nodes increased. After infection, the activities of superoxide dismutase and peroxidase decreased, and malondialdehyde and relative chlorophyll content (SPAD) decreased. Transcriptome analysis showed 514 and 5452 differentially expressed genes (DEGs) in the resistant and susceptible varieties, respectively. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs showed that pathways related to plant disease resistance, such as phenylpropanoid biosynthesis, plant-pathogen interaction, and plant hormone signal transduction, were significantly enriched. In addition, the transcriptome changes of cluster leaves and normal leaves in diseased broomcorn millet were analysed. Gene ontology and KEGG enrichment analyses indicated that photosynthesis played an important role in both varieties. These findings lay a foundation for future research on the molecular mechanism of the interaction between broomcorn millet and Sporisorium destruens.

Comparative analysis of proso millet (Panicum miliaceum L.) leaf transcriptomes for insight into drought tolerance mechanisms.

BACKGROUND: Drought stress is a major abiotic stress that causes huge losses in agricultural production. Proso millet (Panicum miliaceum L.) can efficiently adapt to drought stress and provides important information and gene resources to improve drought tolerance. However, its complex drought-responsive mechanisms remain unclear. RESULTS: Among 37 core Chinese proso millet cultivars, Jinshu 6 (JS6) was selected as the drought-sensitive test material, whereas Neimi 5 (NM5) was selected as the drought-tolerant test material under PEG-induced water stress. After sequencing, 1695 differentially expressed genes (DEGs) were observed in JS6 and NM5 without PEG-induced water stress (JS6CK and NM5CK). A total of 833 and 2166 DEGs were found in the two cultivars under simulated drought by using 20% PEG-6000 for 6 (JS6T6 and NM5T6) and 24 h (JS6T24 and NM5T24), respectively. The DEGs in JS6T6 and JS6T24 treatments were approximately 0.298- and 0.754-fold higher than those in NM5T6 and NM5T24, respectively. Compared with the respective controls, more DEGs were found in T6 treatments than in T24 treatments. A delay in the transcriptional responses of the ROS scavenging system to simulated drought treatment and relatively easy recovery of the expression of photosynthesis-associated genes were observed in NM5. Compared with JS6, different regulation strategies were observed in the jasmonic acid (JA) signal transduction pathway of NM5. CONCLUSION: Under PEG-induced water stress, NM5 maintained highly stable gene expression levels. Compared with drought-sensitive cultivars, the different regulation strategies in the JA signal transduction pathway in drought-tolerant cultivars may be one of the driving forces underlying drought stress tolerance.

Identification of Differentially Expressed Genes Involved in the Molecular Mechanism of Pericarp Elongation and Differences in Sucrose and Starch Accumulation between Vegetable and Grain Pea (Pisum sativum L.).

Pea (Pisum sativum L.), as a major source of plant protein, is becoming one of the major cultivated crop species worldwide. In pea, the pericarp is an important determinant of the morphological characteristics and seed yield. To investigate the molecular mechanism of pericarp elongation as well as sucrose and starch accumulation in the pods of different pea cultivars, we performed transcriptomic analysis of the pericarp of two types of pea cultivar (vegetable pea and grain pea) using RNA-seq. A total of 239.44 Gb of clean sequence data were generated, and were aligned to the reference genome of Pisum sativum L. In the two samples, 1935 differentially expressed genes (DEGs) were identified. Among these DEGs, three antioxidant enzyme superoxide dismutase (SOD) were detected to have higher expression levels in the grain pea pericarps at the pod-elongating stages. Otherwise, five peroxidase (POD)-encoding genes were detected to have lower expression levels in the vegetative pericarps at the development stage of pea pod growth. Furthermore, genes related to starch and sucrose metabolism in the pea pod, such as SUS, INV, FBA, TPI, ADPase, SBE, SSS, and GBSS, were found to be differentially expressed. The RNA-seq data were validated through real-time quantitative RT-PCR of 13 randomly selected genes. Our findings provide the gene expression profile of, as well as differential expression information on, the two pea cultivars, which will lay the foundation for further studies on pod development and nutrition accumulation in the pea and provide valuable information for pea cultivar improvement.