Chromosome-level assembly of triploid genome of Sichuan pepper(Zanthoxylum armatum)

As an important spice species in Rutaceae, the Sichuan pepper (Zanthoxylum armatum) can provide pungent and numbing taste, as well as aroma in its mature fruit. Here we assembled a chromosome-level genome of green prickly ash which was widely cultivated in a major production area including Chongqing and Sichuan province, China. We generated 712 Gb (~112×) PacBio long reads and 511 Gb (~82×) Hi-C data, and yielded an assembly of 99 pseudochromosomes with total size of 5.32 Gb and contig N50 of 796 kb. The genomic analyses and cytogenetic experiments both indicated that the cultivarZhuye Huajiao’ was a triploid. We identified a Zanthoxylum-specific whole genome duplication event emerging about 24.8 million years ago (Mya). We also detected a transposition burst event (0.3-0.4 Mya) responsible for the large genome size of Z. armatum. Metabolomic analysis of the Zanthoxylum fruits during development stages revealed profiles of39 volatile aroma compounds and 528 secondary metabolites, from which six types of sanshools were identified. Based on metabolomic and transcriptomic network analysis, we screened candidate genes encoding long chain acyl-CoA synthetase, fatty acid desaturase,branched-chain amino acid aminotransferase involved in sanshool biosynthesis and three genes encoding terpene synthase during fruit development. The multi-omics data provide insights into the evolution of Zanthoxylum and molecular basis of numbing and aroma flavor of Sichuan pepper.

PGSLM:Edge-Enabled Probabilistic Graph Structure Learning Model for Traffic Forecasting in Internet of Vehicles

With the rapid development of the 5G communications,the edge intelligence enables Internet of Vehicles(IoV)to provide traffic forecasting to alleviate traffic congestion and improve quality of experience of users simultaneously.To enhance the forecasting performance,a novel edge-enabled probabilistic graph structure learning model(PGSLM)is proposed,which learns the graph structure and parameters by the edge sensing information and discrete probability distribution on the edges of the traffic road network.To obtain the spatio-temporal dependencies of traffic data,the learned dynamic graphs are combined with a predefined static graph to generate the graph convolution part of the recurrent graph convolution module.During the training process,a new graph training loss is introduced,which is composed of the K nearest neighbor(KNN)graph constructed by the traffic feature tensors and the graph structure.Detailed experimental results show that,compared with existing models,the proposed PGSLM improves the traffic prediction performance in terms of average absolute error and root mean square error in IoV.

Association mapping of lignin response to Verticillium wilt through an eight-way MAGIC population in Upland cotton

Lignin metabolism plays a pivotal role in plant defense against pathogens and is always positively correlated as a response to pathogen infection. Thus, understanding resistance genes against plant pathogens depends on a genetic analysis of the lignin response. This study used eight Upland cotton lines to construct a multi-parent advanced generation intercross(MAGIC) population(n=280), which exhibited peculiar characteristics from the convergence of various alleles coding for advantageous traits. In order to measure the lignin response to Verticillium wilt(LRVW), the artificial disease nursery(ADN) and rotation nursery(RN) were prepared for MAGIC population planting in four environments. The stem lignin contents were collected, and the LRVW was measured with the lignin value of ADN/RN in each environment, which showed significant variations. We employed 9 323 high-quality single-nucleotide polymorphism(SNP) markers obtained from the Cotton-SNP63K array for genotyping the MAGIC population. The SNPs were distributed through the whole genome with 4.78 SNP/Mb density, ranging from 1.14(ChrA06) to 10.08(ChrD08). In addition, a genome-wide association study was performed using a Mixed Linear Model(MLM) for LRVW. Three stable quantitative trait loci(QTLs), qLRVW-A04, qLRVW-A10, and qLRVW-D05, were identified in more than two environments. Two key candidate genes, Ghi_D05G01046 and Ghi_D05G01221, were selected within the QTLs through the combination of variations in the coding sequence, induced expression patterns, and function annotations. Both genes presented nonsynonymous mutations in coding regions and were strongly induced by Verticillium dahliae. Ghi_D05G01046 encodes a leucine-rich extensin(LRx) protein involved in Arabidopsis cell wall biosynthesis and organization. Ghi_D05G01221 encodes a transcriptional co-repressor novel interactor of novel interactor of jasmonic acid ZIM-domain(JAZ–NINJA), which functions in the jasmonic acid(JA) signaling pathway. In summary, the study creates valuable genetic resources for breeding and QTL mapping and opens up a new perspective to uncover the genetic basis of VW resistance in Upland cotton.

Altered gene expression in human brain microvascular endothelial cells in response to the infection of influenza H1N1 virus

Influenza viruses not only cause respiratory illness,but also have been reported to elicit neurological manifestations following acute viral infection.The central nervous system(CNS)has a specific defense mechanism against pathogens structured by cerebral microvasculature lined with brain endothelial cells to form the blood–brain barrier(BBB).To investigate the response of human brain microvascular endothelial cells(hBMECs)to the Influenza A virus(IAV),we inoculated the cells with the A/WSN/33(H1N1)virus.We then conducted an RNAseq experiment to determine the changes in gene expression levels and the activated disease pathways following infection.The analysis revealed an effective activation of the innate immune defense by inducing the pattern recognition receptors(PRRs).Along with the production of proinflammatory cytokines,we detected an upregulation of interferons and interferon-stimulated genes,such as IFN-β/λ,ISG15,CXCL11,CXCL3 and IL-6,etc.Moreover,infected hBMECs exhibited a disruption in the cytoskeletal structure both on the transcriptomic and cytological levels.The RNAseq analysis showed different pathways and candidate genes associated with the neuroactive ligand-receptor interaction,neuroinflammation,and neurodegenerative diseases,together with a predicted activation of the neuroglia.Likewise,some genes linked with the mitochondrial structure and function displayed a significantly altered expression.En masse,this data supports that hBMECs could be infected by the IAV,which induces the innate and inflammatory immune response.The results suggest that the influenza virus infection could potentially induce a subsequent aggravation of neurological disorders.

Structural basis of SARS-CoV-2 3CL^pro and anti-COVID-19 drug discovery from medicinal plants

The recent pandemic of coronavirus disease 2019(COVID-19)caused by SARS-CoV-2 has raised global health concerns.The viral 3-chymotrypsin-like cysteine protease(3CL^pro)enzyme controls coronavirus replication and is essential for its life cycle.3CL^pro is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus(SARS-CoV)and Middle East respiratory syndrome coronavirus(MERS-CoV).Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV.Therefore,herein,we analysed the 3CL^pro sequence,constructed its 3D homology model,and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds.Our analyses revealed that the top nine hits might serve as potential anti-SARS-CoV-2 lead molecules for further optimisation and drug development process to combat COVID-19.

Co-location of QTL for Sclerotinia stem rot resistance and flowering time in Brassica napus

Sclerotinia stem rot(SSR) caused by Sclerotinia sclerotiorum(Lib.) de Bary is one of the most devastating diseases of Brassica napus worldwide. Both SSR resistance and flowering time(FT) adaptation are major breeding goals in B. napus. However, early maturing rapeseed varieties, which are important for rice-rapeseed rotation in China, are often highly susceptible to SSR. Here, we found that SSR resistance was significantly negatively correlated with FT in a natural population containing 521 rapeseed inbred lines and a double haploid(DH) population with 150 individual lines, both of which had great variation in FT. Four chromosomal regions on A2, A6, C2, and C8 affecting both SSR resistance and FT were identified using quantitative trait loci(QTL) mapping after constructing a high-density genetic map based on single nucleotide polymorphism markers in the DH population.Furthermore, we aligned QTL for the two traits identified in the present and previous studies to the B. napus reference genome, and identified four colocalized QTL hotspots of SSR resistance and FT on A2(0–7.7 Mb), A3(0.8–7.5 Mb), C2(0–15.2 Mb), and C6(20.2–36.6 Mb). Our results revealed a genetic link between SSR resistance and FT in B.napus, which should facilitate the development of effective strategies in both early maturing and SSR resistance breeding and in map-based cloning of SSR resistance QTL.

Feasibility of MRI Radiomics for Predicting KRAS Mutation in Rectal Cancer

The mutation status of KRAS is a significant biomarker in the prognosis of rectal cancer.This study investigated the feasibility of MRI-based radiomics in predicting the mutation status of KRAS with a composite index which could be an important criterion for KRAS mutation in clinical practice.In this retrospective study,a total of 127 patients with rectal cancer were enrolled.The 3D Slicer was used to extract the radiomics features from the MRI images,and sparse support vector machine(SVM)with linear kernel was applied for feature reduction.The radiomics classifier for predicting the KRAS status was then constructed by Linear Discriminant Analysis(LDA)and its performance was evaluated.The composite index was determined with LDA model.Out of 127 rectal cancer subjects,there were 44 KRAS mutation cases and 83 wild cases.A total of 104 radiomics features were extracted,54 features were filtered by linear SVM with L1-norm regularization and 6 features that had no significant correlations within them were finally selected.The radiomics classifier constructed using the 6 features featured an AUC value of 0.669(specificity:0.506;sensitivity:0.773)with LDA.Furthermore,the composite index(Radscore)had statistically significant difference between the KRAS mutation and wild groups.It is suggested that the MRI-based radiomics has the potential in predicting the KRAS status in patients with rectal cancer,which may enhance the diagnostic value of MRI in rectal cancer.

Study of the Preparation Technology and Mechanics of the Compound Temperature-Humidity Sensor

The development and character of compound temperature-humidity sensor were discussed in this study.The design of sampling,control and output unit of temperature-humidity sensor as well as their manufacture method and character were studied in detail.The relationship between components of humidity resistance materials and negative temperature coefficient ( NTC) thermistor materials in sampling unit of compound sensor and character of electrical resistance and temperature was obtained.Couples of character curves of compound temperature-humidity sensor and data of materials of sampling unit were shown in this paper too.

Identification of candidate genes controlling fiber quality traits in upland cotton through integration of meta-QTL,significant SNP and transcriptomic data

Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL intervals,significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.Results:In our study,884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1,as a result,74 meta-QTLs were identified,including 19 meta-QTLs for fiber length;18 meta-QTLs for fiber strength;11 meta-QTLs for fiber uniformity;11 meta-QTLs for fiber elongation;and 15 meta-QTLs for micronaire.Combined with 8589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies,297 candidate genes were identified in the meta-QTL intervals,20 of which showed high expression levels specifically in the developing fibers.According to the function annotations,some of the 20 key candidate genes are associated with the fiber development.Conclusions:This study provides not only stable QTLs used for marker-assisted selection,but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

Molecular and in vitro biochemical assessment of chemosensory protein 10 from brown planthopper Nilaparvata lugens at acidic pH

Chemosensory proteins(CSPs)are important molecular components of the insect olfactory system,which are involved in capturing,binding,and transporting hydrophobic odour molecules across the sensillum in sensillar lymph in regulating insect behavior.This protein family(CSPs)is also involved in many other systems that are not linked to olfactory receptors in olfactory sensilla.The brown planthopper(BPH)is a monophagous pest of rice that causes damage by sucking phloem sap and transmitting a number of diseases caused by viruses.In this study,fluorescence competitive binding assay and fluorescence quenching assay at acidic p H were performed as well as homology modelling to describe the binding affinity of Nlug CSP10.Fluorescence competitive binding assay(FCBA)demonstrated that Nlug CSP10 bound strongly to nonadecane,farnesene,and 2-tridecanone at acidic p H.The results of FCBA indicated that Nlug CSP10 bound different ligands at the physiological p H(5.0)of the bulk sensillum lymph.Fluorescence quenching assay demonstrated that Nlug CSP10 generated a stable complex with 2-tridecanone,while two ligands nonadecane and farnesene collided due to molecular collisions.The interaction of selected ligands with the modelled structure of Nlug CSP10 was also analyzed,which found the key amino acids(Gln23,Gln24,Gln25,Asn27,Met33,Ser34,Ile35,Tyr36,Asn42,Met43,Val45,Asn46,Asn93,Arg96,Ala97,Lys99,and Ala100)in Nlug CSP10 that were involved in binding of volatile compounds.The present study contributes to the binding profile of Nlug CSP10 that promotes the development of behaviorally active ligands based on BPH olfactory system.

Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches

The papain-like protease(PLpro)is vital for the replication of coronaviruses(Co Vs),as well as for escaping innate-immune responses of the host.Hence,it has emerged as an attractive antiviral drug-target.In this study,computational approaches were employed,mainly the structure-based virtual screening coupled with all-atom molecular dynamics(MD)simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)PLpro,which can be further developed as potential pan-PLprobased broad-spectrum antiviral drugs.The sequence,structure,and functional conserveness of most deadly human Co Vs PLprowere explored,and it was revealed that functionally important catalytic triad residues are well conserved among SARS-Co V,SARS-Co V-2,and middle east respiratory syndrome coronavirus(MERS-Co V).The subsequent screening of a focused protease inhibitors database composed of^7,000 compounds resulted in the identification of three candidate compounds,ADM13083841,LMG15521745,and SYN15517940.These three compounds established conserved interactions which were further explored through MD simulations,free energy calculations,and residual energy contribution estimated by MM-PB(GB)SA method.All these compounds showed stable conformation and interacted well with the active residues of SARS-Co V-2 PLpro,and showed consistent interaction profile with SARS-Co V PLproand MERS-Co V PLproas well.Conclusively,the reported SARS-Co V-2 PLprospecific compounds could serve as seeds for developing potent pan-PLprobased broad-spectrum antiviral drugs against deadly human coronaviruses.Moreover,the presented information related to binding site residual energy contribution could lead to further optimization of these compounds.

Energy-Efficient Optimal Guaranteed Cost Intermittent-Switch Control of a Direct Expansion Air Conditioning System

To improve the energy efficiency of a direct expansion air conditioning(DX A/C) system while guaranteeing occupancy comfort, a hierarchical controller for a DX A/C system with uncertain parameters is proposed. The control strategy consists of an open loop optimization controller and a closed-loop guaranteed cost periodically intermittent-switch controller(GCPISC). The error dynamics system of the closed-loop control is modelled based on the GCPISC principle. The difference,compared to the previous DX A/C system control methods, is that the controller designed in this paper performs control at discrete times. For the ease of designing the controller, a series of matrix inequalities are derived to be the sufficient conditions of the lower-layer closed-loop GCPISC controller. In this way, the DX A/C system output is derived to follow the optimal references obtained through the upper-layer open loop controller in exponential time, and the energy efficiency of the system is improved. Moreover, a static optimization problem is addressed for obtaining an optimal GCPISC law to ensure a minimum upper bound on the DX A/C system performance considering energy efficiency and output tracking error. The advantages of the designed hierarchical controller for a DX A/C system with uncertain parameters are demonstrated through some simulation results.

Genetic parameter estimation and genome-wide association study(GWAS) of red blood cell count at three stages in a Duroc×Erhualian pig population

Red blood cells play an essential role in the immune system.Moreover,red blood cell count(RBC) is an important clinical indicator of various diseases,including anemia,type 2 diabetes and the metabolic syndrome.Thus,it is necessary to reveal the genetic mechanism of RBC for animal disease resistance breeding.However,quite a few studies had focused on porcine RBC,especially at different stages.Thus,studies on porcine RBC at different stages are needed for disease resistant breeding.In this study,the porcine RBC of 20-,33-,and 80-day old were measured,and genetic parameter estimation and genome-wide association study(GWAS) were both performed.As a result,the heritability was about 0.6 at the early stages,much higher than that at 80 days.Nine novel genome wide significant single nucleotide polymorphisms(SNPs),located at Sus scrofa chromosome(SSC)3,4,8,9,10 and 15,respectively,were identified.Further,TGFβ2,TMCC2 and PPP1 R15 B genes were identified as important candidate genes of porcine red blood cell count.So different SNPs and candidate genes were found significantly associated with porcine RBC at different stages,suggesting that different genes might play key roles on porcine RBC at different stages.Overall,new evidences were offered in this study for the genetic bases of animal RBC,and that the SNPs and candidate genes would be useful for disease resistant breeding of pig.

Guidance for use of weights: an analysis of different types of weights and their implications when using SAS PROCs

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures.

Progress of Research on Origins of Life in China

The development of Chinese space science and technology plays a great role in promoting the researches in the field of the origin of life.With the multidisciplinary cooperation,there are fruitful achievements in this research field obtained over the past two years.This report summarizes the major progress of the basic researches about the origin of life in China during 2018–2020.

Implementation of Legendre Neural Network to Solve Time-Varying Singular Bilinear Systems

Bilinear singular systems can be used in the investigation of different types of engineering systems.In the past decade,considerable attention has been paid to analyzing and synthesizing singular bilinear systems.Their importance lies in their real world application such as economic,ecological,and socioeconomic processes.They are also applied in several biological processes,such as population dynamics of biological species,water balance,temperature regulation in the human body,carbon dioxide control in lungs,blood pressure,immune system,cardiac regulation,etc.Bilinear singular systems naturally represent different physical processes such as the fundamental law of mass action,the DC motor,the induction motor drives,the mechanical brake systems,aerial combat between two aircraft,the missile intercept problem,modeling and control of small furnaces and hydraulic rotary multimotor systems.The current research work discusses the Legendre Neural Network’s implementation to evaluate time-varying singular bilinear systems for finding the exact solution.The results were obtained from two methods namely the RK-Butcher algorithm and the Runge Kutta Arithmetic Mean(RKAM)method.Compared with the results attained from Legendre Neural Network Method for time-varying singular bilinear systems,the output proved to be accurate.As such,this research article established that the proposed Legendre Neural Network could be easily implemented in MATLAB.One can obtain the solution for any length of time from this method in time-varying singular bilinear systems.

Association mapping and domestication analysis to dissect genetic improvement process of upland cotton yield-related traits in China

Background: Cotton fiber yield is a complex trait,which can be influenced by multiple agronomic traits.Unravelling the genetic basis of cotton fiber yield-related traits contributes to genetic improvement of cotton.Results: In this study,503 upland cotton varieties covering the four breeding stages(BS1–BS4,1911–2011)in China were used for association mapping and domestication analysis.One hundred and forty SSR markers significantly associated with ten fiber yield-related traits were identified,among which,29 markers showed an increasing trend contribution to cotton yield-related traits from BS1 to BS4,and 26 markers showed decreased trend effect.Four favorable alleles of 9 major loci(R^(2)≥3)were strongly selected during the breeding stages,and the candidate genes of the four strongly selected alleles were predicated according to the gene function annotation and tissue expression data.Conclusions :The study not only uncovers the genetic basis of 10 cotton yield-related traits but also provides genetic evidence for cotton improvement during the cotton breeding process in China.

iBP-seq:An efficient and low-cost multiplex targeted genotyping and epigenotyping system

Inter-and intra-specific variations in phenotype are common and can be associated with genomic mutations as well as epigenomic variation.Profiling both genomic and epigenomic variants is at the core of dissecting phenotypic variation.However,an efficient targeted genotyping and epigenotyping system is lacking.We describe a new multiplex targeted genotyping and epigenotyping system called improved bulked-PCR sequencing(iBP-seq).We employed iBP-seq for the detection of genotypes and methylation levels of dozens of target regions in mixed DNA samples.iBP-seq can be adapted for the construction of linkage maps,fine mapping of quantitative-trait loci,and detection of genome editing mutations at a cost as low as$0.016 per site per sample.We developed an automated bioinformatics pipeline,including primer design,a series of bioinformatic analyses for genotyping and epigenotyping,and visualization of results.iBP-seq and its bioinformatics pipeline,available at http://zeasystemsbio.hzau.edu.cn/tools/ibp/,can be adapted to a wide variety of species.

A Multi-Stream Scrambling and DNA Encoding Method Based Image Encryption

Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and networks.Thus,the progress of image encryption techniques is becoming an increasingly serious issue and considerable problem.Small space of the key,encryption-based low confidentiality,low key sensitivity,and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this study.In our proposed scheme,a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption scheme.In the confusion stage,different scrambling operations related to the original plain image pixels are designed using Chen’s map.A stream pixel scrambling operation related to the plain image is constructed.Then,a block scrambling-based image encryption-related stream pixel scrambled image is designed.In the diffusion stage,two rounds of pixel diffusion are generated related to the confusing image for intra-image diffusion.Chen’s map,logistic map,and DNA computing are employed to construct diffusion operations.A reverse complementary rule is applied to obtain a new form of DNA.A Chen’s map is used to produce a pseudorandom DNA sequence,and then another DNA form is constructed from a reverse pseudorandom DNA sequence.Finally,the XOR operation is performed multiple times to obtain the encrypted image.According to the simulation of experiments and security analysis,this approach extends the key space,has great sensitivity,and is able to withstand various typical attacks.An adequate encryption effect is achieved by the proposed algorithm,which can simultaneously decrease the correlation between adjacent pixels by making it near zero,also the information entropy is increased.The number of pixels changing rate(NPCR)and the unified average change intensity(UACI)both are very near to optimal values.