Heat-inducible SlWRKY3 confers thermotolerance by activating the SlGRXS1 gene cluster in tomato

High temperature stress is one of the major environmental factors that affect the growth and development of plants. Although WRKY transcription factors play a critical role in stress responses, there are few studies on the regulation of heat stress by WRKY transcription factors,especially in tomato. Here, we identified a group I WRKY transcription factor, SlWRKY3, involved in thermotolerance in tomato. First, SlWRKY3 was induced and upregulated under heat stress. Accordingly, overexpression of SlWRKY3 led to an increase, whereas knock-out of SlWRKY3 resulted in decreased tolerance to heat stress. Overexpression of SlWRKY3 accumulated less reactive oxygen species(ROS), whereas knock-out of SlWRKY3 accumulated more ROS under heat stress. This indicated that SlWRKY3 positively regulates heat stress in tomato. In addition,SlWRKY3 activated the expression of a range of abiotic stress-responsive genes involved in ROS scavenging, such as a SlGRXS1 gene cluster.Further analysis showed that SlWRKY3 can bind to the promoters of the SlGRXS1 gene cluster and activate their expression. Collectively, these results imply that SlWRKY3 is a positive regulator of thermotolerance through direct binding to the promoters of the SlGRXS1 gene cluster and activating their expression and ROS scavenging.

In silico curation of QTL-rich clusters and candidate gene identification for plant height of bread wheat

Many genetic loci for wheat plant height(PH) have been reported, and 26 dwarfing genes have been catalogued. To identify major and stable genetic loci for PH, here we thoroughly summarized these functionally or genetic verified dwarfing loci from QTL linkage analysis and genome-wide association study published from 2003 to 2022. A total of 332 QTL, 270 GWAS loci and 83 genes for PH were integrated onto chromosomes according to their locations in the IWGSC RefSeq v2.1 and 65 QTL-rich clusters(QRC) were defined. Candidate genes in each QRC were predicted based on IWGSC Annotation v2.1 and the information on functional validation of homologous genes in other species. A total of 38 candidate genes were predicted for 65 QRC including three GA2ox genes in QRC-4B-IV, QRC-5A-VIII and QRC-6A-II(Rht24) as well as GA 20-oxidase 2(TaSD1-3A) in QRC-3A-IV. These outcomes lay concrete foundations for mapbased cloning of wheat dwarfing genes and application in breeding.

GST family genes in jujube actively respond to phytoplasma infection

Jujube witches’broom(JWB)caused by phytoplasma has a severely negative effect on multiple metabolisms in jujube.The GST gene family in plants participates in the regulation of a variety of biotic and abiotic stresses.This study aims to identify and reveal the changes in the jujube GST gene family in response to phytoplasma infection.Here,70 ZjGSTs were identified in the jujube genome and divided into 8 classes.Among them,the Tau-class,including 44 genes,was the largest.Phylogenetic analysis indicated that Tau-class genes were highly conserved among species,such as Arabidopsis,cotton,chickpea,and rice.Through chromosome location analysis,37.1%of genes were clustered,and 8 of 9 gene clusters were composed of Tau class members.Through RT-PCR,qRT-PCR and enzyme activity detection,the results showed that the expression of half(20/40)of the tested ZjGSTs was inhibited by phytoplasma infection in field and tissue culture conditions,and GST activity was also significantly reduced.In the resistant and susceptible varieties under phytoplasma infection,ZjGSTU49-ZjGSTU54 in the cluster IV showed opposite expression patterns,which may be due to functional divergence during evolution.Some upregulated genes(ZjGSTU45,ZjGSTU49,ZjGSTU59,and ZjGSTU70)might be involved in the process of jujube against JWB.The yeast two-hybrid results showed that all 6 Tauclass proteins tested could form homodimers or heterodimers.Overall,the comprehensive analysis of the jujube GST gene family revealed that ZjGSTs responded actively to phytoplasma infection.Furthermore,some screened genes(ZjGSTU24,ZjGSTU49-52,ZjGSTU70,and ZjDHAR10)will contribute to further functional studies of jujube-phytoplasma interactions.

Two gene clusters and their positive regulator SlMYB13 that have undergone domestication-associated negative selection control phenolamide accumulation and drought tolerance in tomato

Among plant metabolites,phenolamides,which are conjugates of hydroxycinnamic acid derivatives and polyamines,play important roles in plant adaptation to abiotic and biotic stresses.However,the molecular mechanisms underlying phenolamide metabolism and regulation as well as the effects of domestication and breeding on phenolamide diversity in tomato remain largely unclear.In this study,we performed a metabolite-based genome-wide association study and identified two biosynthetic gene clusters(BGC7 and BGC11)containing 12 genes involved in phenolamide metabolism,including four biosynthesis genes(two 4CL genes,one C3H gene,and one CPA gene),seven decoration genes(five AT genes and two UGT genes),and one transport protein gene(DTX29).Using gene co-expression network analysis we further discovered that SlMYB13 positively regulates the expression of two gene clusters,thereby promoting phenolamide accumulation.Genetic and physiological analyses showed that BGC7,BGC11 and SlMYB13 enhance drought tolerance by enhancing scavenging of reactive oxygen species and increasing abscisic acid content in tomato.Natural variation analysis suggested that BGC7,BGC11 and SlMYB13 were negatively selected during tomato domestication and improvement,leading to reduced phenolamide content and drought tolerance of cultivated tomato.Collectively,our study discovers a key mechanism of phenolamide biosynthesis and regulation in tomato and reveals that crop domestication and improvement shapes metabolic diversity to affect plant environmental adaptation.

Form Gene Clustering Method about Pan-Ethnic-Group Products Based on Emotional Semantic

The use of pan-ethnic-group products form knowledge primarily depends on a designer＇s subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers＇ perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

A novel and complete gene cluster involved in the degradation of aniline by Delftia sp. AN3

A recombinant strain, Escherichia coli JM109-AN1, was obtained by constructing of a genomic library of the total DNA of Delftia sp. AN3 in E. coli JM109 and screening for catechol 2,3-dioxygenase activity. This recombinant strain could grow on aniline as sole carbon, nitrogen and energy source. Enzymatic assays revealed that the exogenous genes including aniline dioxygenase （AD） and catechol 2,3-dioxygenase （C230） genes could well express in the recombinant strain with the activities of AD and C230 up to 0.31 U/mg wet cell and 1.92 U/mg crude proteins, respectively. The AD or C23O of strain AN3 could only catalyze aniline or catechol but not any other substituted substrates. This recombinant strain contained a recombinant plasmid, pKC505-AN1, in which a 29.7-kb DNA fragment from Delftia sp. AN3 was inserted. Sequencing and open reading frame （orfs） analysis of this 29.7 kb fragment revealed that it contained at least 27 orfs, among them a gene cluster （consisting of at least 16 genes, named danQTA1A2BRDCEFG1HIJKG2） was responsible for the complete metabolism of aniline to TCA-cycle intermediates. This gene cluster could be divided into two main parts, the upper sequences consisted of 7 genes （danQTA1A2BRD） were predicted to encode a multi-component aniline dioxygenase and a LysR-type regulator, and the central genes （danCEFG1HIJKG2） were expected to encode meta-cleavage pathway enzymes for catechol degradation to TCA-cycle intermediates. Unlike clusters tad from Delftia tsuruhatensis AD9 and tdn from Pseudomonas putida UCC22, in this gene cluster, all the genes were in the same transcriptional direction. There was only one set of C230 gene （danC） and ferredoxin-like protein gene （danD）. The presence of only one set of these two genes and specificity of AD and C230 might be the reason for strain AN3 could only degrade aniline. The products of danQTA1A2BRDC showed 99%-100% identity to those from Delftia acidovorans 7N, and 50%-85% identity to those of tad cluster from D. tsuruhatensis AD9 in amino acid residues. Besides this dan cluster, the 29.7 kb fragment also contained genes encoding the trans-membrane transporter and transposases which might be needed for transposition of the gene cluster. Pulsed-field gel electrophoresis （PFGE） and plasmid curing experiments suggested that the dan cluster might be encoded on the chromosome of strain AN3. The GenBank accession number for the dan cluster of Delftia sp. AN3 is DQ661649.

Clustering of Major Genes Conferring Blast Resistance in a Durable Resistance Rice Cultivar Gumei 2

By using 304 recombinant inbred lines derived from indica rice cross Zhong 156/Gumei 2, a linkage map consisting of 177 marker loci and covering 12 rice chromosomes was constructed and employed for mapping genes conferring blast resistance in rice. Genomic location of gene Pi25(t) conferring neck blast resistance to the Chinese isolate 92-183 (race ZC15) was verified to be located between markers A7 and RG456 on chromosome 6, with genetic distances of 1.7 cM and 1.5 cM to A7 and RG456, respectively. Leaf blast resistance of Gumei 2 to the Philippine isolate Ca89 (lineage 4) was found to be controlled by a single gene. The gene tentatively designated as Pi26(\) was located between makers B10 and R674 on chromosome 6, with genetic distances of 5.7 cM and 25.8 cM to B10 and R674 respectively. Resistant alleles at both gene loci were derived from Gumei 2, indicating an existence of resistance gene cluster in Gumei 2.

Identification of anrF gene, a homology of admM of andrimid biosynthetic gene cluster related to the antagonistic activity of Enterobacter cloacae B8

AIM: To identify the gene (s) related to the antagonistic activity of Enterobacter cloacae B8 and to elucidate its antagonistic mechanism.METHODS: Transposon-mediated mutagenesis and tagging method and cassette PCR-based chromosomal walking method were adopted to isolate the mutant strain(s) of B8 that lost the antagonistic activity and to clone DNA fragments around Tn5 insertion site. Sequence compiling and open reading frame (ORF) finding were done with DNAStar program and homologous sequence and conserved domain searches were performed with BlastN or BlastP programs at www. ncbi.nlm.nih.gov. To verify the gene involved in the antagonistic activity, complementation of a full-length clone of the anrFgene to the mutant B8F strain was used.RESULTS: A 3 321 bp contig around the Tn5 insertion site was obtained and an ORF of 2 634 bp in length designated as anrFgene encoding for a 877 aa polyketide synthase-like protein was identified. It had a homology of 83% at the nucleotide level and 79% ID/87% SIM at the protein level, to the admM gene of Pantoea agglornerans andrimid biosynthetic gene cluster (AY192157). The Tn5was inserted at 2 420 bp of the gene corresponding to the COG3319 (the thioesterase domain of type Ⅰ polyketide synthase) coding region on B8F. The antagonistic activity against Xanthomonas oryzae pv. oryzae was resumed with complementation of the full-length anrFgene to the mutant B8F.CONCLUSION: The anrFgene obtained is related to the antagonistic activity of B8, and the antagonistic substances produced by B8 are andrimid and/or its analogs.

Incorporating heterogeneous biological data sources in clustering gene expression data

In this paper, a similarity measure between genes with protein-protein interactions is pro-posed. The chip-chip data are converted into the same form of gene expression data with pear-son correlation as its similarity measure. On the basis of the similarity measures of protein- protein interaction data and chip-chip data, the combined dissimilarity measure is defined. The combined distance measure is introduced into K-means method, which can be considered as an improved K-means method. The improved K-means method and other three clustering methods are evaluated by a real dataset. Per-formance of these methods is assessed by a prediction accuracy analysis through known gene annotations. Our results show that the improved K-means method outperforms other clustering methods. The performance of the improved K-means method is also tested by varying the tuning coefficients of the combined dissimilarity measure. The results show that it is very helpful and meaningful to incorporate het-erogeneous data sources in clustering gene expression data, and those coefficients for the genome-wide or completed data sources should be given larger values when constructing the combined dissimilarity measure.

Cluster Analysis on the Nucleotide Sequences of Six Genes in Rice

[ Objective] This study aimed to construct four-dimensional graphics of nucleotide sequences of six genes in rice （ GluB-6, GtuB-7, PDIL2, OsMPK1, OsCATC, OsCATA） and to conduct phase-space clustering, thus demonstrating the relationship between the structure and function of rice genes. [ Method ] Base sequences were represented by four-dimensional graphics and clustered in the phase space. The relationship between clustering results and biological characteristics of these genes were analyzed. [ Result] Genes with similar four-dimensional graphics exhibit similar biological characteristics. [ Conclusion] Four-dimensional graphics of genes with different functions and base lengths present phase-space relationship with their biological functions, which provided an effective way for the prediction of gene function.

Clustering Gene Expression Data Through Modified Agglomerative M-CURE Hierarchical Algorithm

Gene expression refers to the process in which the gene information isused in the functional gene product synthesis. They basically encode the proteinswhich in turn dictate the functionality of the cell. The first step in gene expressionstudy involves the clustering usage. This is due to the reason that biological networks are very complex and the genes volume increases the comprehending challenges along with the data interpretation which itself inhibit vagueness, noise andimprecision. For a biological system to function, the essential cellular moleculesmust interact with its surrounding including RNA, DNA, metabolites and proteins. Clustering methods will help to expose the structures and the patterns inthe original data for taking further decisions. The traditional clustering techniquesinvolve hierarchical, model based, partitioning, density based, grid based and softclustering methods. Though many of these methods provide a reliable output inclustering, they fail to incorporate huge data of gene expressions. Also, thereare statistical issues along with choosing the right method and the choice of dissimilarity matrix when dealing with gene expression data. We propose to use amodified clustering algorithm using representatives (M-CURE) in this workwhich is more robust to outliers as compared to K-means clustering and also ableto find clusters with size variances.

Fuzzy Cluster Analysis of Alzheimer’s Disease-Related Gene Sequences

The objective of this paper is to analyze the relationship among the interrelated gene sequences of Alzheimer’s disease (AD). Further this paper will provide a study on genetic factor of the occurrence about Alzheimer’s disease, so as to provide more information on the prevention of Alzheimer’s disease, the clinical diagnosis and gene therapy for Alzheimer’s disease. The respective alignment of the Alzheimer’s disease interrelated gene sequences with those in The National Center for Biotechnology Information (NCBI) database was studied, and the measurement relationship of these sequences was identified and analyzed by the method of fuzzy cluster. The result of fuzzy cluster analysis indicates that the gene sequences interrelated within one group is consistently having closer relationship within the group other than in another group.

The QseB/QseC two-component system contributes to virulence of Actinobacillus pleuropneumoniae by downregulating apf gene cluster transcription

Actinobacillus pleuropneumoniae(APP)is the major pathogen of porcine contagious pleuropneumoniae(PCP).The QseB/QseC two-component system(TCS)consists of the regulator QseB and the kinase QseC,which relates to quorum sensing(QS)and virulence in some bacteria.Here,we investigated the role of QseB/QseC in apf gene cluster(apfABCD)expression of APP.Our results have showed that QseB/QseC TCS can potentially regulate the expression of apf gene cluster.The△qseBC,△apfA,△apfB,△apfC and△apfD strains are more sensitive to acidic and osmotic stressful conditions,and exhibite lower biofilm formation ability than wild-type(WT)strain,whereas the complemented strains show similar phenotype to the wr strain.In additon,the mutants have defective antiphagocytosis,adhesion and invasion when they come into contact with the host cells.In experimental animal models of infection,mice infected with△qseBC,△apfA,△apfB,△apfC and △apfD strains showed lower mortality and bacterial loads in the lung and the blood than those infected with wr strain.In conclusion,our results suggest that QseB/QseC TCS contributes to stress resistance,biofilm formation,phagocytosis,adhesion,invasion and virulence by downregulating expression of apf gene cluster in A.pleuropneumoniae.

Neurologic orphan diseases:Emerging innovations and role for genetic treatments

Orphan diseases are rare diseases that affect less than 200000 individuals within the United States.Most orphan diseases are of neurologic and genetic origin.With the current advances in technology,more funding has been devoted to developing therapeutic agents for patients with these conditions.In our review,we highlight emerging options for patients with neurologic orphan diseases,specifically including diseases resulting in muscular deterioration,epilepsy,seizures,neurodegenerative movement disorders,inhibited cognitive development,neuron deterioration,and tumors.After extensive literature review,gene therapy offers a promising route for the treatment of neurologic orphan diseases.The use of clustered regularly interspaced palindromic repeats/Cas9 has demonstrated positive results in experiments investigating its role in several diseases.Additionally,the use of adeno-associated viral vectors has shown improvement in survival,motor function,and developmental milestones,while also demonstrating reversal of sensory ataxia and cardiomyopathy in Friedreich ataxia patients.Antisense oligonucleotides have also been used in some neurologic orphan diseases with positive outcomes.Mammalian target of rapamycin inhibitors are currently being investigated and have reduced abnormal cell growth,proliferation,and angiogenesis.Emerging innovations and the role of genetic treatments open a new window of opportunity for the treatment of neurologic orphan diseases.

A data structure and function classification based method to evaluate clustering models for gene expression data

Objective:To establish a systematic framework for selecting the best clustering algorithm and provide an evaluation method for clustering analyses of gene expression data. Methods: Based on data structure (internal information) and function classification (external information), the evaluation of gene expression data analyses were carried out by using 2 approaches. Firstly, to assess the predictive power of clusteringalgorithms, Entropy was introduced to measure the consistency between the clustering results from different algorithms and the known and validated functional classifications. Secondly, a modified method of figure of merit (adjust-FOM) was used as internal assessment method. In this method, one clustering algorithm was used to analyze all data but one experimental condition, the remaining condition was used to assess the predictive power of the resulting clusters. This method was applied on 3 gene expression data sets (2 from the Lyer's Serum Data Sets, and 1 from the Ferea's Saccharomyces Cerevisiae Data Set). Results: A method based on entropy and figure of merit (FOM) was proposed to explore the results of the 3 data sets obtained by 6 different algorithms, SOM and Fuzzy clustering methods were confirmed to possess the highest ability to cluster. Conclusion: A method based on entropy is firstly brought forward to evaluate clustering analyses.Different results are attained in evaluating same data set due to different function classification. According to the curves of adjust_FOM and Entropy_FOM, SOM and Fuzzy clustering methods show the highest ability to cluster on the 3 data sets.

Involvement of clustered oyster Wnt genes in gut formation

Genes encoding Wnt ligands play important roles in organ development. The Wnt10-Wnt6-Wnt1-Wnt9 cluster widely presents in many metazoan genomes, indicating the importance of gene arrangement. Hypothesis has been proposed that they may be coordinately regulated. However, few expression correlations were identified in model animals. We analyzed the tissue expression pattern of clustered oyster Wnt10, Wnt6, Wnt1, and Wnt9 a genes in this study. The results indicated the highest expression level in adult gut system of these clustered W nt genes, except for Wnt6, which had highest expression in mantle. Further whole-mount immunofluorescence assay indicated that Wnt6 protein was restricted to gut region in oyster larvae. These results suggest the possible important role of the W nt10-Wnt6-Wnt1-Wnt9 cluster in oyster gut formation.

Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model

The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem.Considering the differences between these two modes of power replenishment,we constructed a joint location-planning model to minimize construction and operation costs,user costs,and user satisfaction-related penalty costs.We designed an improved genetic algorithm that changes the crossover rate using the fitness value,memorizes,and transfers excellent genes.In addition,the present model addresses the problem of“premature convergence”in conventional genetic algorithms.A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels under different charging modes with an improved computing efficiency.The example also proved that meeting more demand for power supply of electric vehicles does not necessarily mean increasing the sites of charging/battery-swap stations.Instead,optimizing the level and location planning of charging/battery-swap stations can maximize the investment profit.The proposed model can provide a reference for the government and enterprises to better plan the location of charging/battery-swap facilities.Hence,it is of both theoretical and practical value.

Gene Coding Sequence Identification Using Kernel Fuzzy C-Mean Clustering and Takagi-Sugeno Fuzzy Model

Sequence analysis technology under big data provides unprecedented opportunities for modern life science. A novel gene coding sequence identification method is proposed in this paper. Firstly, an improved short-time Fourier transform algorithm based on Morlet wavelet is applied to extract the power spectrum of DNA sequence. Then, threshold value determination method based on kernel fuzzy C-mean clustering is used to combine Signal to Noise Ratio (SNR) data of exon and intron into a sequence, classify the sequence into two types, calculate the weighted sum of two SNR clustering centers obtained and the discrimination threshold value. Finally, exon interval endpoint identification algorithm based on Takagi-Sugeno fuzzy identification model is presented to train Takagi-Sugeno model, optimize model parameters with Levenberg-Marquardt least square method, complete model and determine fuzzy rule. To verify the effectiveness of the proposed method, example tests are conducted on typical gene sequence sample data.

基于机器学习的茶树DNA聚类算法

为了研究茶树基因序列的聚类问题,设计一种基于累计方差贡献率进行改进的核主成分分析(KPCA)与k均值(k-means)++聚类算法相结合的降维聚类算法(KPCA-k-means++)。将基因库数据集筛选分组后,利用k-mers算法提取基因数据的数据特征,根据累计方差贡献率的占比大于85%的标准确定降维主元个数对KPCA进行降维改进并采用k-means++算法对降维后数据聚类,通过CH(Calinski-Harabaze Index)指标和响应时间分析聚类结果。结果表明:在单独聚类、KPCA聚类、改进PCA聚类、改进KPCA聚类4种处理方式中,改进KPCA-k-means++算法在不同处理方式和不同样本数的对比下,CH指标均为最高,与未改进时相比平均高出33%。在响应时间方面,改进KPCA-k-means++算法与同样改进PCA-k-means++算法在不同聚类数和样本数的对比下响应时间均较短。改进KPCA-k-means++算法能够保证对于茶树的基因序列的聚类准确率和聚类速度,表现出极好的聚类稳定性。