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Magnesium chelatase (MgCh) plays a pivotal role in photosynthesis, catalyzing the insertion of magnesium into protoporphyrin IX (Proto IX), a key intermediate in chlorophyll (Chl) biosynthesis. MgCh is a heteromeric complex composed of the MgCh D subunit (CHLD), the MgCh H subunit (CHLH), and the MgCh I subunit (CHLI). The bright yellow leaves (byl) mutant was obtained through ethyl methanesulfonate (EMS) mutagenesis of the ‘FT’ Chinese cabbage (Brassica rapa L. ssp. pekinensis) doubled haploid line, whose Chl content, net photosynthetic rate (Pn), and non-photochemical quenching coefficient (NPQ) were decreased, and whose chloroplast development was incomplete. byl recovered to a light green phenotype under weak light conditions. Genetic analysis revealed that the bright yellow leaves phenotype of byl was caused by a single recessive nuclear gene. Using Mutmap sequencing and Kompetitive allele-specific PCR (KASP) identification, BraA01g010040.3.5C, encoding the CHLI subunit of MgCh, was identified as the candidate gene and named Brchli1. A nonsynonymous G-to-A mutation in the Brchli1 exon resulted in the substitution of aspartic acid with asparagine. Brchli1-silenced Chinese cabbage displayed bright yellow leaves with decreased Brchli1 expression. Transiently overexpressed Brchli1 in the byl mutant restored the green leaf phenotype and significantly increased relative Brchli1 expression levels. Both BrCHLI1 and its mutated variant were localized in chloroplasts. Yeast two-hybrid and luciferase complementation imaging assays demonstrated that BrCHLI1 interacted with both BrCHLD and itself. BrCHLI1 mutations did not affect its interaction with BrCHLD. Together, Brchli1 mutations impaired the function of MgCh, providing insights into the molecular mechanism of leaf coloration.

Abstract Background Epidermal wax covers the surfaces of terrestrial plants to resist biotic and abiotic stresses. Wax-less flowering Chinese cabbage (Brassica campestris L. ssp. chinesis var. utilis tsen et lee) has the charateristics of lustrous green leaves and flower stalks, which are of high commercial value. Results To clarify the mechanism of the wax deficiency, the wax-less flowering Chinese cabbage doubled-haploid (DH) line ‘CX001’ and Chinese cabbage DH line ‘FT’, obtained from isolated microspore culture, were used in the experiments. Genetic analysis showed that the wax-less phenotype of ‘CX001’ was controlled by a recessive nuclear gene, named wlm1 (wax-less mutation 1), which was fine-mapped on chromosome A09 by bulked segregant analysis sequencing (BSA-seq) of B.rapa genome V3.0. There was only one gene (BraA09g066480.3C) present in the mapping region. The homologous gene in Arabidopsis thaliana is AT1G02205 (CER1) that encodes an aldehyde decarboxylase in the epidermal wax metabolism pathway. Semi-quantitative reverse transcription PCR and transcriptome analysis indicated that BraA09g066480.3C was expressed in ‘FT’ but not in ‘CX001’. BraA09g066480.3C was lost in the CXA genome to which ‘CX001’ belonged. Conclusion The work presented herein demonstrated that BraA09g066480.3C was the causal gene for wax-less flowering Chinese cabbage ‘CX001’. This study will lay a foundation for further research on the molecular mechanism of epidermal wax synthesis in flowering Chinese cabbage.

Abstract Background The growth and development of leaves and petioles have a significant effect on photosynthesis. Understanding the molecular mechanisms underlying leaf and petiole development is necessary for improving photosynthetic efficiency, cultivating varieties with high photosynthetic efficiency, and improving the yield of crops of which the leaves are foodstuffs. This study aimed to identify the mRNAs, long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) related to leaf and petiole development in Chinese cabbage (Brassica campestris L. ssp. pekinensis). The data were used to construct a competitive endogenous RNA (ceRNA) network to obtain insights into the mechanisms underlying leaf and petiole development. Results The leaves and petioles of the ‘PHL’ inbred line of Chinese cabbage were used as research materials for whole transcriptome sequencing. A total of 10,646 differentially expressed (DE) mRNAs, 303 DElncRNAs, 7 DEcircRNAs, and 195 DEmiRNAs were identified between leaves and petioles. Transcription factors and proteins that play important roles in leaf and petiole development were identified, including xyloglucan endotransglucosylase/hydrolase, expansion proteins and their precursors, transcription factors TCP15 and bHLH, lateral organ boundary domain protein, cellulose synthase, MOR1-like protein, and proteins related to plant hormone biosynthesis. A ceRNA regulatory network related to leaf and petiole development was constructed, and 85 pairs of ceRNA relationships were identified, including 71 DEmiRNA–DEmRNA, 12 DEmiRNA–DElncRNA, and 2 DEmiRNA–DEcircRNA pairs. Three LSH genes (BrLSH1, BrLSH2 and BrLSH3) with significant differential expression between leaves and petioles were screened from transcriptome data, and their functions were explored through subcellular localization analysis and transgenic overexpression verification. BrLSH1, BrLSH2 and BrLSH3 were nuclear proteins, and BrLSH2 inhibited the growth and development of Arabidopsis thaliana. Conclusions This study identifies mRNAs and non-coding RNAs that may be involved in the development of leaves and petioles in Chinese cabbage, and establishes a ceRNA regulatory network related to development of the leaves and petioles, providing valuable genomic resources for further research on the molecular mechanisms underlying leaf and petiole development in this crop species.

Traditional resource allocation methods are difficult to meet the needs of various services to accurately understand the semantics of a large amount of multimedia data in the intelligent networked environment.Facing with this challenge, taking intelligent task-oriented internet of vehicles scenarios as an example, two resource allocation optimization criteria for the semantic communication were firstly proposed.Then, according to different dimensions of resources, the models and algorithms of the resource allocation for the semantic communication were described.Then, a semantic communication-oriented image dataset was constructed, and the performance advantages of the proposed resource allocation methods in the simulation scenario of the internet of vehicles were analyzed.Finally, the future challenges of the resource allocation for the semantic communication were presented.

Objectives: In the future, intelligent interconnection of all things, such as machine-to-machine and human-to-machine, poses challenges to traditional communication methods. The semantic communication method that extracts semantic information from source information and transmits them provides a novel solution for the sixth generation (6G) communication system. However, there are challenges in how to measure semantic information and how to achieve optimal semantic codec.This paper reviews the existing works related to semantic communication,and proposes a semantic communication method and framework for intelligent tasks,paving the way for further development of semantic communication. Methods: Firstly, the development history and research status of semantic communication are reviewed, the two bottleneck problems faced by semantic communication are analyzed and summarized, and a semantic communication method oriented to intelligent tasks is proposed. Aiming at the difficulty of semantic entropy,this paper defines the smallest basic unit of semantic message as semantic element,introduces fuzzy mathematics theory to describe the fuzzy degree of semantic understanding, and gives the calculation expression of semantic information entropy. Then, based on the information bottleneck theory, this paper proposes a semantic information coding scheme and a semantic channel joint coding scheme,respectively considering whether the receiver needs to reconstruct the original source. Furthermore, from the perspective of neural network interpretability,an interpretability-based semantic encoding method is proposed.Finally, a semantic communication platform for intelligent tasks is built based on software and hardware such as USRP and LabView,and the performance of the proposed algorithm is verified. Results:In the communication scenario where the source needs to be reconstructed,the semantic communication method proposed in this paper can greatly improve the compression ratio of the source data and greatly reduce the amount of transmitted data.Under the same compression ratio, the performance of the receiver to perform subsequent intelligent tasks can be improved,and the performance of source reconstruction can be improved at the same time.In scenarios where there is no need to reconstruct the source,the semantic communication method can better accomplish intelligent tasks with a large compression ratio.This is because semantic communication transmits the semantic information of the image instead of all the data of the image,which greatly reduces its bandwidth requirements,and the bandwidth utilization rate of semantic communication is 100 times higher than that of traditional communication methods. In addition, the anti-noise performance of the semantic communication method is much better than that of the traditional communication method, because the data transmitted by the semantic communication method retains the semantic features of the image,and the influence of channel noise is considered during model training, which makes the performance of intelligent tasks better and makes the communication system more robust. The semantic communication method greatly reduces the amount of data transmitted, so the transmission delay is significantly reduced under the same bandwidth resources.In addition,since image reconstruction is not required,the processing load of software and hardware is reduced, and the processing delay is also reduced. Therefore, the scheme proposed in this paper can greatly reduce the delay of end-to-end intelligent tasks while ensuring high-precision classification performance. Conclusions: Compared with traditional communication methods, the semantic communication method oriented to intelligent tasks has obvious advantages,which can greatly reduce the amount of transmitted data and improve the performance of intelligent tasks at the receiving end. Therefore, semantic communication will continue to maintain the trend of rapid development. However,there are still a lot of basic concepts and basic problems in semantic communication that need to be further discussed and improved,such as the basic theory of semantic information,the unified architecture of semantic communication,and the resource allocation strategy in semantic communication. Research is of great significance to promoting technological innovation and breakthroughs in the 6G era,and academic colleagues need to jointly promote the realization.

IntroductionThe cuticle wax covering the plant surface is a whitish hydrophobic protective barrier in Chinese cabbage, and the epicuticular wax crystal deficiency normally has higher commodity value for a tender texture and glossy appearance. Herein, two allelic epicuticular wax crystal deficiency mutants, wdm1 and wdm7, were obtained from the EMS mutagenesis population of a Chinese cabbage DH line ‘FT’.MethodsThe cuticle wax morphology was observed by Cryo-scanning electron microscopy (Cryo-SEM) and the composition of wax was determined by GC-MS. The candidate mutant gene was found by MutMap and validated by KASP. The function of candidate gene was verified by allelic variation.ResultsThe mutants had fewer wax crystals and lower leaf primary alcohol and ester content. Genetic analysis revealed that the epicuticular wax crystal deficiency phenotype was controlled by a recessive nuclear gene, named Brwdm1. MutMap and KASP analyses indicated that BraA01g004350.3C, encoding an alcohol-forming fatty acyl-CoA reductase, was the candidate gene for Brwdm1. A SNP 2,113,772 (C to T) variation in the 6th exon of Brwdm1 in wdm1 led to the 262nd amino acid substitution from threonine (T) to isoleucine (I), which existed in a rather conserved site among the amino acid sequences from Brwdm1 and its homologs. Meanwhile, the substitution changed the three-dimensional structure of Brwdm1. The SNP 2,114,994 (G to A) in the 10th exon of Brwdm1 in wdm7 resulted in the change of the 434th amino acid from valine (V) to isoleucine (I), which occurred in the STERILE domain. KASP genotyping showed that SNP 2,114,994 was co-segregated with glossy phenotype. Compared with the wild type, the relative expression of Brwdm1 was significantly decreased in the leaves, flowers, buds and siliques of wdm1.DiscussionThese results indicated that Brwdm1 was indispensable for the wax crystals formation and its mutation resulted in glossy appearance in Chinese cabbage.

Abstract Anther development is precisely regulated by a complex gene network, which is of great significance to plant breeding. However, the molecular mechanism of anther development in Chinese cabbage is unclear. Here, we identified microRNAs (miRNAs), mRNAs, long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) related to anther development in Chinese cabbage (Brassica campestris L. ssp. pekinensis) to construct competitive endogenous RNA (ceRNA) regulatory networks and provide valuable knowledge on anther development. Using whole-transcriptome sequencing, 9055, 585, 1344, and 165 differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), lncRNAs (DElncRNAs), and circRNAs (DEcircRNAs) were identified, respectively, in the anthers of Chinese cabbage compared with those in samples of the vegetative mass of four true leaves. An anther-related ceRNA regulatory network was constructed using miRNA targeting relationships, and 450 pairs of ceRNA relationships, including 97 DEmiRNA–DEmRNA, 281 DEmiRNA–DElncRNA, and 23 DEmiRNA–DEcircRNA interactions, were obtained. We identified important genes and their interactions with lncRNAs, circRNAs, and miRNAs involved in microsporogenesis, tapetum and callose layer development, pollen wall formation, and anther dehiscence. We analyzed the promoter activity of six predominant anther expression genes, which were expressed specifically in the anthers of Arabidopsis thaliana, indicating that they may play an important role in anther development of Chinese cabbage. This study lays the foundation for further research on the molecular mechanisms of anther growth and development in Chinese cabbage.

With the integration and development of Internet of things (IoT) and artificial intelligence (AI) technologies, traditional data centralized cloud computing processing methods are difficult to effectively remove a large amount of redundant information in data, which brings challenges to the low-latency and high-precision requirements of intelligent tasks in the artificial intelligence of things (AIoT).In response to this challenge, a semantic communication method oriented to intelligent tasks in AIoT was proposed based on the deep learning method.For image classification tasks, convolutional neural networks (CNN) were used on IoT devices to extract image feature maps.Starting from semantic concepts, semantic concepts and feature maps were associated to extract semantic relationships.Based on the semantic relationships, semantic compression was implemented to reduce the pressure of network transmission and the processing delay of intelligent tasks.Experimental and simulation results show that, compared with traditional communication scheme, the proposed method is only about 0.8% of the traditional scheme, and at the same time it has higher classification task performance.Compared with the scheme that all feature maps are transmitted, the transmission delay of the proposed method is reduced by 80% and the effective accuracy of image classification task is greatly improved.

Abstract Background The transition from vegetative growth to reproductive growth involves various pathways. Vernalization is a crucial process for floral organ formation and regulation of flowering time that is widely utilized in plant breeding. In this study, we aimed to identify the global landscape of mRNAs, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) related to vernalization in Chinese cabbage. These data were then used to construct a competitive endogenous RNA (ceRNA) network that provides valuable information to better understand the vernalization response. Results In this study, seeds sampled from the Chinese cabbage doubled haploid (DH) line ‘FT’ with or without vernalization treatment were used for whole-transcriptome sequencing. A total of 2702 differentially expressed (DE) mRNAs, 151 DE lncRNAs, 16 DE circRNAs, and 233 DE miRNAs were identified in the vernalization-treated seeds. Various transcription factors, such as WRKY, MYB, NAC, bHLH, MADS-box, zinc finger protein CONSTANS-like gene, and B3 domain protein, and regulatory proteins that play important roles in the vernalization pathway were identified. Additionally, we constructed a vernalization-related ceRNA–miRNA–target gene network and obtained 199 pairs of ceRNA relationships, including 108 DEmiRNA‒DEmRNA, 67 DEmiRNA‒DElncRNA, and 12 DEmiRNA‒DEcircRNA interactions, in Chinese cabbage. Furthermore, several important vernalization-related genes and their interacting lncRNAs, circRNAs, and miRNAs, which are involved in the regulation of flowering time, floral organ formation, bolting, and flowering, were identified. Conclusions Our results reveal the potential mRNA and non-coding RNAs involved in vernalization, providing a foundation for further studies on the molecular mechanisms underlying vernalization in Chinese cabbage.

Leafy head formation is one of the most important characteristics of Chinese cabbage, and the process is regulated by a series of genes and environmental factors. In this study, a non-heading short leaf mutant slm was identified from an ethyl methane sulfonate mutagenesis (EMS) population of the heading Chinese cabbage line FT. The most significant phenotypic characteristics of slm was shortening leaves and increasing leaf numbers, which led to failure to form a leafy head. Genetic analysis showed that a single recessive gene Brslm was responsible for the mutant phenotype. Mutmap analysis suggested that Brslm was located on chromosome A07, and four candidate genes were predicted. KASP analysis demonstrated that BraA07g039390.3C was the target gene of the candidates. BraA07g039390.3C is a homologous to Arabidopsis CLV1 encoding receptor kinase with an extracellular leucine-rich domain. Sequencing analysis revealed that a single SNP from G to A occurred in 904th nucleotide of Brclv1, which resulted in the change of the 302nd amino acid from Asp to Asn. The SNP was co-segregated with the mutant phenotype in F2 individuals and located on the conserved domains. These results indicated that BrCLV1 was the mutant gene for slm which led to shortening leaves and increasing leaf numbers, disrupting the leafy heading formation in FT. These findings contribute to revealing the BrCLV1 function in leafy head formation in Chinese cabbage.

Cut flower ornamental kale (Brassica oleracea var. acephala) is a biennial cultivar, which completes a sexual reproductive generation in two years. Isolated microspore culture (IMC) can accelerate plant homozygosity instead of self-pollinations. However, the application of IMC in cut flower ornamental kale was rare since its low rate of embryogenesis. It is proved that histone acetylation might affect the gene expression in microspores and led to the transformation of microspores from pollen development pathway to embryogenesis. In this paper, microspores, derived from three varieties of cut flower ornamental kale, Crane Bicolor (CB), Crane Pink (CP) and Crane Feather Queen (CFQ), were treated with histone deacetylation inhibitor (HDACI) trichostatin A (TSA). Results revealed that the appropriate concentration of TSA was 10 nM for CB with obtaining 5.39 embryos per bud, while for CP and CFQ was 5 nM with acquiring 10.89 and 16.99 embryos per bud, respectively. TSA treatment also reduced the embryonic mortality, of which 10 nM TSA treatments CB was the optimal and the embryonic mortality decreased to 25.01%. The double haploid (DH) proportion of regenerated plants reached 37.3%. These results contribute to improving the technology for IMC in cut flower ornamental kale.

In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.