The molecular dialogue between rice and the brown planthopper (BPH; Nilaparvata lugens) is mediated by insect salivary effectors, yet the molecular mechanisms underlying plant perception and immune activation remain largely unclear. Here, we characterized the BPH salivary protein NlSP2, which is secreted into rice tissues during feeding. Silencing of NlSP2 in BPH impairs salivary sheath formation, feeding ability, and survival, whereas its ectopic expression in rice enhances resistance to BPH via MAPK activation, H2O2 accumulation, and induction of defense-related genes. We identify the rice cystathionine β-synthase domain-containing protein OsCBSX3 as a direct intracellular target of NlSP2. Genetic analyses establish OsCBSX3 as a positive regulator of BPH resistance and an essential component of NlSP2-triggered immunity. NlSP2 binding promotes OsCBSX3 nuclear accumulation. In the nucleus, OsCBSX3 interacts with the NAC transcription factor SNAC3; NlSP2 enhances this interaction and potentiates SNAC3-mediated transcriptional activation of defense genes. Loss of SNAC3 compromises rice resistance to BPH. Together, our results elucidate a complete signaling pathway linking insect effector perception to defense gene activation and highlight the OsCBSX3-SNAC3 module as a key regulator of rice immunity, providing insights into plant-insect interactions and potential targets for breeding resistant crops.

Herbivorous insects pose a major threat to crop production, with rice suffering significant yield losses due to infestation by the brown planthopper (BPH). To understand the genetic and metabolic basis of BPH resistance in rice, we conducted metabolomic analysis and performed metabolite-based genome-wide association studies (mGWAS) on a rice population composed of 168 varieties, which exhibit a wide range of resistance to BPH. Metabolomic analysis revealed a trend of increasing metabolic divergence with increasing resistance levels compared with the susceptible group, with resistant groups maintaining greater metabolic stability after BPH infestation. Furthermore, using these metabolic biomarkers, we constructed a prediction model for BPH resistance and found that biomarkers in non-infested rice were sufficient to predict BPH resistance. We identified in total 2,738 single-nucleotide polymorphisms (SNPs) associated with key biomarkers in non-infested rice and 1,605 SNPs in BPH-infested rice. Gene Ontology (GO) enrichment analysis revealed that genes associated with biomarkers were enriched in different pathways between non-infested and BPH-infested rice. Notably, the SNP rs6_191562334 was significantly associated with the biomarker β-damascenone, which correlated positively with rice resistance to BPH and has been shown to inhibit BPH feeding on rice. Knockout of LOC_Os06g17970 increased β-damascenone levels and enhanced BPH resistance in rice. Collectively, this integrated approach provided novel insight into the metabolic and genetic mechanisms underlying BPH resistance and facilitated the development of strategies for sustainable control of BPH.

Parasitoids are crucial natural enemies of Liriomyza trifolii, a globally notorious pest. Upon parasitization, host metabolism and immune responses were profoundly disrupted, thereby favoring the development of wasps offsprings. However, the underlying regulatory mechanisms remain elusive. In this study, transcriptome sequencing was utilized to investigate the host metabolic and immune response changes at 4 h, 12 h, and 24 h postparasitization by Phaedrotoma sp.2. We identified 4070 differentially expressed genes, enriched in metabolic (e.g., tricarboxylic acid cycle, insulin synthesis) and immune (e.g., Toll/Imd pathways) pathways, and RT-qPCR further validated core gene expressions involved in these pathways. Physiological analyses revealed that Phaedrotoma sp.2 parasitism altered the host larvae's protein, lipid, and sugar content, inhibited hemocyte spreading, increased hemocyte mortality, and suppressed hemolymph melanization. Collectively, this study sheds light on the host metabolic and immune modulation by Phaedrotoma sp.2 parasitism and provides a novel insight into the mechanisms underpinning their interactions. This discovery lays a solid foundation for the practical application of parasitoids in biological control programs.

Endosymbiotic fungi play an important role in the growth and development of insects. Understanding the endosymbiont communities hosted by the brown planthopper (BPH; Nilaparvata lugens Stål), the most destructive pest in rice, is a prerequisite for controlling BPH rice infestations. However, the endosymbiont diversity and dynamics of the BPH remain poorly studied. Here, we used circular consensus sequencing (CCS) to obtain 87,131 OTUs (operational taxonomic units), which annotated 730 species of endosymbiotic fungi in the various developmental stages and tissues. We found that three yeast-like symbionts (YLSs), Polycephalomyces prolificus, Ophiocordyceps heteropoda, and Hirsutella proturicola, were dominant in almost all samples, which was especially pronounced in instar nymphs 4–5, female adults, and the fat bodies of female and male adult BPH. Interestingly, honeydew as the only in vitro sample had a unique community structure. Various diversity indices might indicate the different activity of endosymbionts in these stages and tissues. The biomarkers analyzed using LEfSe suggested some special functions of samples at different developmental stages of growth and the active functions of specific tissues in different sexes. Finally, we found that the incidence of occurrence of three species of Malassezia and Fusarium sp. was higher in males than in females in all comparison groups. In summary, our study provides a comprehensive survey of symbiotic fungi in the BPH, which complements the previous research on YLSs. These results offer new theoretical insights and practical implications for novel pest management strategies to understand the BPH–microbe symbiosis and devise effective pest control strategies.

The brown planthopper (BPH) is the most destructive insect pest that threatens rice production globally. Developing rice varieties incorporating BPH-resistant genes has proven to be an effective control measure against BPH. In this study, we assessed the resistance of a core collection consisting of 502 rice germplasms by evaluating resistance scores, weight gain rates and honeydew excretions. A total of 117 rice varieties (23.31%) exhibited resistance to BPH. Genome-wide association studies (GWAS) were performed on both the entire panel of 502 rice varieties and its subspecies, and 6 loci were significantly associated with resistance scores (P value < 1.0e-8). Within these loci, we identified eight candidate genes encoding receptor-like protein kinase (RLK), nucleotide-binding and leucine-rich repeat (NB-LRR), or LRR proteins. Two loci had not been detected in previous study and were entirely novel. Furthermore, we evaluated the predictive ability of genomic selection for resistance to BPH. The results revealed that the highest prediction accuracy for BPH resistance reached 0.633. As expected, the prediction accuracy increased progressively with an increasing number of SNPs, and a total of 6.7K SNPs displayed comparable accuracy to 268K SNPs. Among various statistical models tested, the random forest model exhibited superior predictive accuracy. Moreover, increasing the size of training population improved prediction accuracy; however, there was no significant difference in prediction accuracy between a training population size of 737 and 1179. Additionally, when there existed close genetic relatedness between the training and validation populations, higher prediction accuracies were observed compared to scenarios when they were genetically distant. These findings provide valuable resistance candidate genes and germplasm resources and are crucial for the application of genomic selection for breeding durable BPH-resistant rice varieties.

Deep learning models often rely on a large number of labeled data to achieve good performance. However, labeling such a large number of data requires exhaustive labor efforts. In recent years, a pivotal research direction is to generalize deep learning models to learn from not only unlabeled data of seen classes but also data of novel classes which are not predefined, known as open-world semi-supervised learning (open-world SSL). Existing works tackled this challenging task by manually designing different optimizations for labeled/unlabeled data and seen/novel classes. In this paper, we propose a simple unified framework that can be applied to all images and all classes in the same form. In this framework, we exploit the Sinkhorn–Knopp algorithm to overcome the overconfidence issue of pseudo labels on seen classes and thus lead to a more balanced distribution of seen and novel classes. To reduce the intra-class variance and avoid model collapse, we take as input two different views of an image and regard one’s prediction as the other’s pseudo label. However, in a unified framework, the model converges much faster on the seen classes than those novel classes. To balance them and encourage knowledge transfer from seen classes to novel classes, we further propose mixing up any two training images during our unified optimization. Extensive experiments on three benchmarks (i.e., CIFAR-10, CIFAR-100, and ImageNet-100) show that our unified framework achieved comparable performance with existing state-of-the-art methods. Our code is available on https://github.com/happytianhao/OWSSL.

类受体胞质激酶(receptor-like cytoplasmic kinases,RLCKs)家族是一类特殊蛋白激酶,在植物生长和病原菌防御中发挥着重要的生物学功能.在对水稻RLCK Ⅵ家族成员OsRRK1 基因的研究中发现水稻 4号染色体上存在一个与其同源性特别高的基因,即OsRLCK167(LOC_Os04g56060).为了丰富类受体胞质激酶家族并探究水稻胞质受体激酶基因的作用,本研究利用ExPASy-Protparam、Protscale、CD-search等在线工具和DNAMAN软件对OsRLCK167 基因进行生物信息学分析;采用qRT-PCR技术对OsRLCK167 基因做组织表达模式分析.结果显示:OsRLCK167 蛋白的分子量为43.77776 kD,为疏水性、不稳定的酸性蛋白;对该蛋白的二级结构进行预测,显示其主要由无规则卷曲(41.94％)、α-螺旋(35.29％)、延伸链(15.35％)和β-转角(7.42％)组成;该基因在水稻不同组织均有表达,且在叶鞘中的表达量最高.结果表明,OsRLCK167 基因在进化过程中具有高度的保守性,在水稻中具有功能多样性.

The Bph15 gene, known for its ability to confer resistance to the brown planthopper (BPH; Nilaparvata lugens Stål), has been extensively employed in rice breeding. However, the molecular mechanism by which Bph15 provides resistance against BPH in rice remains poorly understood. In this study, we reported that the transcription factor OsWRKY71 was highly responsive to BPH infestation and exhibited early-induced expression in Bph15-NIL (near-isogenic line) plants, and OsWRKY71 was localized in the nucleus of rice protoplasts. The knockout of OsWRKY71 in the Bph15-NIL background by CRISPR-Cas9 technology resulted in an impaired Bph15-mediated resistance against BPH. Transcriptome analysis revealed that the transcript profiles responsive to BPH differed between the wrky71 mutant and Bph15-NIL, and the knockout of OsWRKY71 altered the expression of defense genes. Subsequent quantitative RT-PCR analysis identified three genes, namely sesquiterpene synthase OsSTPS2, EXO70 family gene OsEXO70J1, and disease resistance gene RGA2, which might participate in BPH resistance conferred by OsWRKY71 in Bph15-NIL plants. Our investigation demonstrated the pivotal involvement of OsWRKY71 in Bph15-mediated resistance and provided new insights into the rice defense mechanisms against BPH.

Plants deploy receptor-like kinases and nucleotide-binding leucine-rich repeat receptors to confer host plant resistance (HPR) to herbivores1. These gene-for-gene interactions between insects and their hosts have been proposed for more than 50 years2. However, the molecular and cellular mechanisms that underlie HPR have been elusive, as the identity and sensing mechanisms of insect avirulence effectors have remained unknown. Here we identify an insect salivary protein perceived by a plant immune receptor. The BPH14-interacting salivary protein (BISP) from the brown planthopper (Nilaparvata lugens Stål) is secreted into rice (Oryza sativa) during feeding. In susceptible plants, BISP targets O. satvia RLCK185 (OsRLCK185; hereafter Os is used to denote O. satvia-related proteins or genes) to suppress basal defences. In resistant plants, the nucleotide-binding leucine-rich repeat receptor BPH14 directly binds BISP to activate HPR. Constitutive activation of Bph14-mediated immunity is detrimental to plant growth and productivity. The fine-tuning of Bph14-mediated HPR is achieved through direct binding of BISP and BPH14 to the selective autophagy cargo receptor OsNBR1, which delivers BISP to OsATG8 for degradation. Autophagy therefore controls BISP levels. In Bph14 plants, autophagy restores cellular homeostasis by downregulating HPR when feeding by brown planthoppers ceases. We identify an insect saliva protein sensed by a plant immune receptor and discover a three-way interaction system that offers opportunities for developing high-yield, insect-resistant crops.

Most person re-identification (re-ID) approaches are based on representation learning of pedestrian images, which assume that the person’s appearance captured by cameras in the target is fully available. However, the exposure of appearance could cause serious privacy leakages. To address this issue, we focus on a new privacy-protected person re-ID task where the person’s appearance is unavailable for training. We first overcome the dilemma of lacking real person images by utilizing the virtual pedestrian samples (e.g., PersonX). Then, we introduce a composition of data augmentations to simulate real conditions, where the learned model is transferred to the real target in a black way. Specifically, the background behind, surrounding illumination, pose, scale, and attributes of pedestrians from the target scene, irrelevant to privacy, are utilized to generate virtual images. With above privacy-irrelevant information, we propose a Translation-Rendering-Sampling (TRS) framework to generate images toward the distribution of the real-world dataset (including background, pose, attribute, etc). Extensive experiments are conducted on several realistic re-ID datasets excluding the person’s appearance. The experiments show that our method outperforms the baseline significantly as well as some transfer learning methods.

Rice ( Oryza sativa L.) is a staple food crop globally. Brown planthopper ( Nilaparvata lugens Stål, BPH) is the most destructive insect that threatens rice production annually. More than 40 BPH resistance genes have been identified so far, which provide valuable gene resources for marker-assisted breeding against BPH. However, it is still urgent to evaluate rice germplasms and to explore more new wide-spectrum BPH resistance genes to combat newly occurring virulent BPH populations. To this end, 560 germplasm accessions were collected from the International Rice Research Institute (IRRI), and their resistance to current BPH population of China was examined. A total of 105 highly resistant materials were identified. Molecular screening of BPH resistance genes in these rice germplasms was conducted by developing specific functional molecular markers of eight cloned resistance genes. Twenty-three resistant germplasms were found to contain none of the 8 cloned BPH resistance genes. These accessions also exhibited a variety of resistance mechanisms as indicated by an improved insect weight gain (WG) method, suggesting the existence of new resistance genes. One new BPH resistance gene, Bph44 ( t ), was identified in rice accession IRGC 15344 and preliminarily mapped to a 0–2 Mb region on chromosome 4. This study systematically sorted out the corresponding relationships between BPH resistance genes and germplasm resources using a functional molecular marker system. Newly explored resistant germplasms will provide valualble donors for the identification of new resistance genes and BPH resistance breeding programs.

Brown planthopper (BPH) has become the most devastating insect pests of rice and a serious threat to rice production. To combat newly occurring virulent BPH populations, it is still urgent to explore more new broad-spectrum BPH resistance genes and integrate them into rice cultivars. In the present study, we explored the genetic basis of BPH resistance in IRGC 8678. We identified and mapped a new resistance gene Bph43 to a region of ~380 kb on chromosome 11. Genes encoding nucleotide-binding domain leucine-rich repeat-containing (NBS-LRR)-type disease resistance proteins or Leucine Rich Repeat family proteins annotated in this region were predicted as the possible candidates for Bph43. Meanwhile, we developed near isogenic lines of Bph43 (NIL-Bph43-9311) in an elite restorer line 9311 background using marker-assisted selection (MAS). The further characterization of NIL-Bph43-9311 demonstrated that Bph43 confers strong antibiosis and antixenosis effects on BPH. Comparative transcriptome analysis revealed that genes related to the defense response and resistance gene-dependent signaling pathway were significantly and uniquely enriched in BPH-infested NIL-Bph43-9311. Our work demonstrated that Bph43 can be deployed as a valuable donor in BPH resistance breeding programs.

Brown planthopper (Nilaparvata lugens Stål, BPH) is one of the most destructive insects affecting rice production. To better understand the physiological mechanisms of how rice responds to BPH feeding, we analyzed BPH-induced transcriptomic and metabolic changes in leaf sheaths of both BPH-susceptible and -resistant rice varieties. Our results demonstrated that the resistant rice reduced the settling, feeding and growth of BPH. Metabolic analyses indicated that BPH infestation caused more drastic overall metabolic changes in the susceptible variety than the resistant rice. Differently accumulated metabolites (DAMs) belonging to flavonoids were downregulated in the susceptible rice but upregulated in resistant variety. Transcriptomic analyses revealed more differentially expressed genes (DEGs) in susceptible rice than resistant rice, and DEGs related to stimulus were significantly upregulated in resistant rice but downregulated in susceptible rice. Combined analyses of transcriptome and metabolome showed that many DEGs and DAMs were enriched in phenylpropane biosynthesis, flavonoid biosynthesis, and plant hormone signal transduction. We conducted correlation analyses of DEGs and DAMs in these pathways and found a high correlation between DEGs and DAMs. Then, we found that the contents of endogenous indole 3-acetic acid (IAA) in resistant rice was lower than that of susceptible rice after BPH feeding, while the salicylic acid (SA) content was the opposite. For functional analysis, an exogenous application of IAA decreased rice resistance to BPH, but the exogenous application of SA increased resistance. In addition, biochemical assessment and quantitative PCR analysis showed that the lignin content of resistant accession was constitutively higher than in susceptible accession. By adding epigallocatechin, the substrate of anthocyanidin reductase (ANR), to the artificial diet decreased the performance of BPH. We first combined a transcriptome-metabolome-wide association study (TMWAS) on rice resistance to BPH in this study. We demonstrated that rice promoted resistance to BPH by inducing epigallocatechin and decreasing IAA. These findings provided useful transcriptomic and metabolic information for understanding the rice-BPH interactions.

Rice is the most important food crop globally and a model species for basic biological research. Brown planthopper (BPH) is one of the major insect pests of rice. In the past decades, scientists have explored the BPH resistance gene from rice germplasm and revealed the molecular mechanism underlying the host plant resistance of rice to BPH. Research results have promoted the development of BPH-resistant rice varieties and their release in rice production. This review briefly introduces the research progress on brown planthopper resistance gene discovery, mechanism analysis, germplasm innovation, and utilization in rice breeding programs to help readers understand the mystery of plant resistance against insects and the practical significance of insect resistance research in plants.

The planthopper resistance gene Bph6 encodes a protein that interacts with OsEXO70E1. EXO70 forms a family of paralogues in rice. We hypothesized that the EXO70-dependent trafficking pathway affects the excretion of resistance-related proteins, thus impacting plant resistance to planthoppers. Here, we further explored the function of EXO70 members in rice resistance against planthoppers. We used the yeast two-hybrid and co-immunoprecipitation assays to identify proteins that play roles in Bph6-mediated planthopper resistance. The functions of the identified proteins were characterized via gene transformation, plant resistance evaluation, insect performance, cell excretion observation and cell wall component analyses. We discovered that another EXO70 member, OsEXO70H3, interacted with BPH6 and functioned in cell excretion and in Bph6-mediated planthopper resistance. We further found that OsEXO70H3 interacted with an S-adenosylmethionine synthetase-like protein (SAMSL) and increased the delivery of SAMSL outside the cells. The functional impairment of OsEXO70H3 and SAMSL reduced the lignin content and the planthopper resistance level of rice plants. Our results suggest that OsEXO70H3 may recruit SAMSL and help its excretion to the apoplast where it may be involved in lignin deposition in cell walls, thus contributing to rice resistance to planthoppers.

Unsupervised person re-identification (re-ID) has attracted increasing research interests because of its scalability and possibility for real-world applications. State-of-the-art unsupervised re-ID methods usually follow a clustering-based strategy, which generates pseudo labels by clustering and maintains a memory to store instance features and represent the centroid of the clusters for contrastive learning. This approach suffers two problems. First, the centroid generated by unsupervised learning may not be a perfect prototype. Forcing images to get closer to the centroid emphasizes the result of clustering, which could accumulate clustering errors during iterations. Second, previous instance memory based methods utilize features updated at different training iterations to represent one centroid, these features are inconsistent due to the change of encoder. To this end, we propose an unsupervised re-ID approach with a stochastic learning strategy. Specifically, we adopt a stochastic updated memory, where a random instance from a cluster is used to update the cluster-level memory for contrastive learning. In this way, the relationship between randomly selected pair of images are learned to avoid the training bias caused by unreliable pseudo labels. By picking a sole last seen sample to directly update each cluster center, the stochastic memory is also always up-to-date for classifying to keep the consistency. Besides, to relieve the issue of camera variance, a unified distance matrix is proposed during clustering, where the distance bias from different camera domains is reduced and the variances of identities are emphasized. Our proposed method outperforms the state-of-the-arts in all the common unsupervised and UDA re-ID tasks. The code will be available at https://github.com/lithium770/ Unsupervised-Person-re-ID-with-Stochastic-Training-Strategy.

为探明褐飞虱交配次数和性选择的生殖行为特征,构建了褐飞虱生物型1和生物型Y的近交系,筛选了在不同近交系之间存在明显差异的9个SSR(Simple Sequence Repeats)分子标记用于亲子鉴定.在雌虫交配次数试验中,观察并分子鉴定到23头成功交配的雌虫,其中19头雌虫一生仅进行1次交配,4头雌虫一生进行了2次交配,故褐飞虱雌虫是以单次交配为主、2次交配为辅的混合型交配策略.在性选择分析中,首先,性别内选择试验观察并鉴定到了23头交配成功的雄虫,其中18头生物型Y雄虫选择与雌虫进行交配;其次,性别间选择试验观察并鉴定到了83％生物型Y雄虫选择与雌虫进行交配.结果表明:在性选择行为中,生物型Y雄虫具有更强的竞争优势.

Phloem-feeding insects cause massive losses in agriculture and horticulture. Host plant resistance to phloem-feeding insects is often mediated by changes in phloem composition, which deter insect settling and feeding and decrease viability. Here, we report that rice plant resistance to the phloem-feeding brown planthopper (BPH) is associated with fortification of the sclerenchyma tissue, which is located just beneath the epidermis and a cell layer or two away from the vascular bundle in the rice leaf sheath. We found that BPHs prefer to feed on the smooth and soft region on the surface of rice leaf sheaths called the long-cell block. We identified Bph30 as a rice BPH resistance gene that prevents BPH stylets from reaching the phloemdue to the fortified sclerenchyma. Bph30 is strongly expressed in sclerenchyma cells and enhances cellulose and hemicellulose synthesis, making the cell walls stiffer and sclerenchyma thicker. The structurally fortified sclerenchyma is a formidable barrier preventing BPH stylets from penetrating the leaf sheath tissues and arriving at the phloem to feed. Bph30 belongs to a novel gene family, encoding a protein with two leucine-rich domains. Another member of the family, Bph40, also conferred resistance to BPH. Collectively, the fortified sclerenchyma-mediated resistance mechanism revealed in this study expands our understanding of plant-insect interactions and opens a new path for controlling planthoppers in rice.

现有的全球变化参数遥感产品由于时空分辨率不够精细、精度不够高,难以满足科研人员对全球变化特征分析与归因、全球气候变化辐射强迫与地表响应等的研究需求.随着我国国产卫星的数量逐渐增多、观测手段愈发丰富、时空分辨率不断提高,国产卫星在全球变化研究领域的应用潜力也与日俱增,尤其是在10～30米的中高空间分辨率尺度上的时间分辨率已超过同类型的国外卫星数据.因此,当务之急就是要充分发挥国产卫星数据在时空分辨率方面的优势,形成以国产数据为主的长时间序列、高时空分辨率的全球变化产品.

Rice (Oryza sativa) is both a vital source of food and a key model cereal for genomic research. Insect pests are major factors constraining rice production. Here, we provide an overview of recent progress in functional genomics research and the genetic improvements of insect resistance in rice. To date, many insect resistance genes have been identified in rice, and 14 such genes have been cloned via a map-based cloning approach. The proteins encoded by these genes perceive the effectors of insect and activate the defense pathways, including the expression of defense-related genes, including mitogen-activated protein kinase, plant hormone, and transcription factors; and defense mechanism against insects, including callose deposition, trypsin proteinase inhibitors (TryPIs), secondary metabolites, and green leaf volatiles (GLVs). These ongoing functional genomic studies provide insights into the molecular basis of rice–insect interactions and facilitate the development of novel insect-resistant rice varieties, improving long-term control of insect pests in this crucial crop.