Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been wide...Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been widely applied to the wholegenome profiling of gene expression.The commonality of these experiments is that they measure the gene expression levels of"bulk"sample,which pools a large number(often in the scale of millions)of cells,and thus the measurements reflect the average expression展开更多
The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL ...The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.展开更多
The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the g...The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function （transitions and outputs） of the cellular automata as models for the intracellular governing gene/epigene networks.展开更多
Background:To provide a reference for the clinical development of drugs to suppress severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods:Retrieving genes related to SARS-CoV-2 with Genecards database an...Background:To provide a reference for the clinical development of drugs to suppress severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods:Retrieving genes related to SARS-CoV-2 with Genecards database and then importing the obtained gene data into the database of Database for Annotation,Visualization and Integrated Discovery(DAVID)(Version 6.8)to collect relevant information on pathways and genes.Genes enriched in the first 20 most significant pathways and genes with gene occurrence frequency≥6 were respectively imported into the STRING database to construct protein-protein interaction(PPI)network diagrams,and the two network diagrams were compared.Results:In the two network graphs,RELA,MAPK1,MAPK3,PIK3CA,PIK3R1,MAPK8,JAK1,STAT1,TNF,IL6,MAPK14,and IL1B ranked higher,and the occurrence frequency of the first 20 pathways was≥10.Conclusion:The pathogenesis of SARS-CoV-2 is associated with multiple pathways such as influenza A,TNF signaling pathway,chemokine signaling pathway,toll-like receptor signaling pathway,T cell receptor signaling pathway et al.RELA,MAPK1,MAPK3,PIK3CA,PIK3R1,MAPK8,JAK1,STAT1,TNF,IL6,MAPK14 and IL1B are closely related to SARS-CoV-2 and need further study.Gene interaction network and pathway analysis of diseaseassociated genes will help us to screen the key target genes of SARS-CoV-2 and provide a reference for the clinical development of effective drugs.展开更多
Objective:To use bioinformatics and gene networks to screen key target genes of coronavirus disease 2019,which provides references for clinical research and development of drugs for coronavirus disease 2019.Methods:Ta...Objective:To use bioinformatics and gene networks to screen key target genes of coronavirus disease 2019,which provides references for clinical research and development of drugs for coronavirus disease 2019.Methods:Target genes related to coronavirus disease 2019 were screened in the GeneCards and National Center for Biotechnology Information databases,and the obtained gene data were imported into the Database for Annotation,Visualization and Integrated Discovery(Version 6.8)database to collect the related information about pathways and genes.The genes enriched in the first 20 pathways and the genes whose occurrence frequency≥5 were imported into the String database respectively to construct protein-protein interaction network diagram and compare the two network diagrams.Results:TNF,IL-6,IL-2,IL-8,CXCL8,IL1B,CCL2,IFNG,STAT1,MAPK1,MAPK3,MAPK8,TP53 and RELA are ranked top in the two network diagrams,and the frequency of occurrence in the first 20 pathways was≥5.Conclusion:The incidence of coronavirus disease 2019 is associated with multiple signaling pathways,including influenza A,pathways in cancer,toll-like receptor signaling pathway,hypoxia-inducible factor-1 signaling pathway,et al.TNF,IL-6,IL-2,IL-8,CXCL8,IL1B,CCL2,IFNG,STAT1,MAPK1,MAPK3,MAPK8,TP53 and RELA are closely related to coronavirus disease 2019,which needs to be further studied.By analyzing the pathways of the genes related to coronavirus disease 2019 and the interactive network diagrams between the genes,it is helpful to understand the pathogenesis of the disease and provide a reference for clinical research and development of effective drugs for coronavirus disease 2019.展开更多
This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology ...This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology for solving the nonlinear partial differential equations, namely the Hamilton-Jacobi-Bellman and Hamilton-Jacobi-Isaacs equations through successive Galerkin’s approximation is implemented and the results are compared. Throughout the implementation, there were several caveats that need to be further resolved for practical applications in general cases. Such issues and the clarification of causes are mathematically established and reviewed.展开更多
Analyzing gene network structure is an important way to discover and understand some unknown relevant functions and regulatory mechanisms of organism at the molecular level. In this work, mutual information networks a...Analyzing gene network structure is an important way to discover and understand some unknown relevant functions and regulatory mechanisms of organism at the molecular level. In this work, mutual information networks and Boolean logic networks are constructed using the methods of reverse modeling based on gene expression profiles in lung tissues with and without cancer. The comparison of these network structures shows that average degree, the proportion of non-isolated nodes, average betweenness and average coreness can distinguish the networks corresponding to the lung tissues with and without cancer. According to the difference of degree, betweenness and coreness of each gene in these networks, nine structural key genes are obtained. Seven of them which are related to lung cancer are supported by literatures. The remaining two genes AKT1 and RBL may have important roles in the formation, development and metastasis of lung cancer. Furthermore, the contrast of these logic networks suggests that the distributions of logic types are obviously different. The structural differences can help us to understand the mechanism of formation and development of lung cancer.展开更多
For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most im...For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most important environmental stress factors that limits plant productivity worldwide. Today, transcriptomic approaches seem to give the best coverage of genome level responses. Therefore, microarray serves as an invaluable tool for global gene expression analyses, unravelling new information about gene pathways, in-species and cross-species gene expression comparison, and for the characterization of unknown relationships between genes. In this review we summarize the recent progress in the transcriptomics of ozone to demonstrate the benefits that can be harvested from the application of integrative and systematic analytical approaches to study ozone stress response. We focused our consideration on microarray analyses identifying gene networks responsible for response and tolerance to elevated ozone concentration. From these analyses it is now possible to notice how plant ozone defense responses depend on the interplay between many complex signaling pathways and metabolite signals.展开更多
The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the comp...The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the complicated regulation mechanism of shoot genes of Arabidopsis Thaliana in response to stimuli. The dynamics of the complicated logic network is analyzed, discussed, and simulated. The simulation results show that the logic network of the active genes of shoot eventually evolves into eleven attractors under the stimuli, including five 1-periodic and six 2-periodic attractors. Our work provides valuable reference and guidance for biologists to understand and explain Arabidopsis＇ response to external stimuli by experiments.展开更多
Although genome-wide association studies （GWAS） have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing herit...Although genome-wide association studies （GWAS） have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET （Simultaneously Inference of GeNEs and Tissues） to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.展开更多
The identification of communities is imperative in the understanding of network structures and functions.Using community detection algorithms in biological networks, the community structure of biological networks can ...The identification of communities is imperative in the understanding of network structures and functions.Using community detection algorithms in biological networks, the community structure of biological networks can be determined, which is helpful in analyzing the topological structures and predicting the behaviors of biological networks. In this paper, we analyze the diseasome network using a new method called disease-gene network detecting algorithm based on principal component analysis, which can be used to investigate the connection between nodes within the same group. Experimental results on real-world networks have demonstrated that our algorithm is more efficient in detecting community structures when compared with other well-known results.展开更多
The flowering time of Arabidopsis is sensitive to climate variability, with lighting conditions being a major determinant of the flowering time. Long-days induce early flowering, while short-days induce late flowering...The flowering time of Arabidopsis is sensitive to climate variability, with lighting conditions being a major determinant of the flowering time. Long-days induce early flowering, while short-days induce late flowering or even no flowers. This study investigates the intrinsic mechanisms for Arabidopsis flowering in different lighting conditions using mutual information networks and logic networks. The structure parameters of the mutual information networks show that the average degree and the average core clearly distinguish these networks. A method is then given to find the key structural genes in the mutual information networks and the logic networks respectively. Ten genes are found to possibly promote flowering with three genes that may restrain flowering. The sensitivity of this method to find the genes that promote flowering is 80%, while the sensitivity of the method to find the genes that restrain flowering is 100%.展开更多
The association of Zika virus(ZIKV)infection with microcephaly has raised alarm worldwide.Their causal link has been confirmed in different animal models infected by ZIKV.However,the molecular mechanisms underlying ZI...The association of Zika virus(ZIKV)infection with microcephaly has raised alarm worldwide.Their causal link has been confirmed in different animal models infected by ZIKV.However,the molecular mechanisms underlying ZIKV pathogenesis are far from clear.Hence,we performed global gene expression analysis of ZIKV-infected mouse brains to unveil the biological and molecular networks underpinning microcephaly.We found significant dysregulation of the sub-networks associated with brain development,immune response,cell death,microglial cell activation,and autophagy amongst others.We provided detailed analysis of the related complicated gene networks and the links between them.Additionally,we analyzed the signaling pathways that were likely to be involved.This report provides systemic insights into not only the pathogenesis,but also a path to the development of prophylactic and therapeutic strategies against ZIKV infection.展开更多
The effects of noise and a periodic signal on a synthetic gene network have been investigated. By tuning the distance of a parameter from the Hopf bifurcation point, both implicit internal signal stochastic resonance ...The effects of noise and a periodic signal on a synthetic gene network have been investigated. By tuning the distance of a parameter from the Hopf bifurcation point, both implicit internal signal stochastic resonance and explicit internal signal stochastic resonance can be induced by noise. Furthermore, a switch process can also be elicited. When a periodic signal is coupled to the gene network, two interesting phenomena occur with the modulation of the frequency of the signal: the effect of noise amplifying cellular signal can be inhibited or even destroyed, and "locked" coherence resonance occurs.展开更多
The feed forward loop （FFL）, wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small nu...The feed forward loop （FFL）, wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small number of reactant molecules and thus internal molecular fluctuation is considerable. Here we studied how an FFL responds to small external signal inputs at gene X, with particular attention paid to the fluctuation resonance （FR） phenomenon of gene Z. We found that for all coherent FFLs, where the sign of the direct regulation path from X to Z is the same as the overall sign of the indirect path via Y, the FR shows a regular single peak, while for incoherent FFLs, the FR exhibits distinct bimodal shapes. The results indicate that one could use small external signals to help identify the regulatory structure of an unknown FFL in complex gene networks.展开更多
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.展开更多
The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite...The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite,with pearl production displaying notable sexual dimorphism.Consequently,understanding the molecular mechanisms governing sex determination and differentiation is crucial for advancing breeding strategies in the pearl oyster industry.To elucidate these mechanisms,this study conducted integrative transcriptomic analyses of P.maxima gonadal tissues using isoform sequencing(Isoseq)and RNA sequencing(RNA-seq).Comparative analysis of ovarian and testicular tissues identified 2768 differentially expressed genes(DEGs).Gene coexpression network analysis delineated four key modules,including three sex-specific modules and one shared module.Key genes implicated in sex determination and maintenance were identified,including FOXL2,NANOS1,andβ-catenin,important for ovarian maintenance,and DMRT,SOX30,FEM1,and FOXJ1,crucial for testicular maintenance.These genes,widely studied in other taxa,were confirmed as hub genes in the sex-related modules of P.maxima.Interestingly,genes within the shared module were significantly enriched in the spliceosome pathway.Alternative splicing analysis highlighted its extensive role in gonadal tissues,with more pronounced activity observed in the testis compared to the ovary.Nearly half(47.83%,375)of the identified genes undergoing differential alternative splicing(DASGs)also exhibited differential transcript usage(DTUGs),while only 17%of DTUGs overlapped with DEGs.Genes associated with sex differentiation,such as DMRT,β-catenin,and U2AF2,displayed sex-specific and/or sex-biased isoforms.These findings offer novel insights into the molecular basis of sex differentiation in P.maxima,which could inform the development of targeted breeding strategies aimed at sex control,thereby enhancing pearl quality and yield in aquaculture.This study offers a robust molecular foundation for advancing breeding programs and optimizing production in the pearl oyster industry.展开更多
In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task i...In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task in bioinformatics.The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determine the network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use of both simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.展开更多
Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is s...Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).展开更多
Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks fro...Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples.Here,we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.展开更多
基金partially supported by NIH grants (2U19AI090023,5P30AI50409,and R01GM122083)
文摘Study of gene expression has been arguably the most active research field in functional genomics.Over the last two decades,various high-throughput technologies,from gene expression microarray to RNA-seq,have been widely applied to the wholegenome profiling of gene expression.The commonality of these experiments is that they measure the gene expression levels of"bulk"sample,which pools a large number(often in the scale of millions)of cells,and thus the measurements reflect the average expression
基金supported by Indian Council of Agricultural Research(ICAR),New Delhi for assistance.
文摘The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.
文摘The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function （transitions and outputs） of the cellular automata as models for the intracellular governing gene/epigene networks.
文摘Background:To provide a reference for the clinical development of drugs to suppress severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods:Retrieving genes related to SARS-CoV-2 with Genecards database and then importing the obtained gene data into the database of Database for Annotation,Visualization and Integrated Discovery(DAVID)(Version 6.8)to collect relevant information on pathways and genes.Genes enriched in the first 20 most significant pathways and genes with gene occurrence frequency≥6 were respectively imported into the STRING database to construct protein-protein interaction(PPI)network diagrams,and the two network diagrams were compared.Results:In the two network graphs,RELA,MAPK1,MAPK3,PIK3CA,PIK3R1,MAPK8,JAK1,STAT1,TNF,IL6,MAPK14,and IL1B ranked higher,and the occurrence frequency of the first 20 pathways was≥10.Conclusion:The pathogenesis of SARS-CoV-2 is associated with multiple pathways such as influenza A,TNF signaling pathway,chemokine signaling pathway,toll-like receptor signaling pathway,T cell receptor signaling pathway et al.RELA,MAPK1,MAPK3,PIK3CA,PIK3R1,MAPK8,JAK1,STAT1,TNF,IL6,MAPK14 and IL1B are closely related to SARS-CoV-2 and need further study.Gene interaction network and pathway analysis of diseaseassociated genes will help us to screen the key target genes of SARS-CoV-2 and provide a reference for the clinical development of effective drugs.
文摘Objective:To use bioinformatics and gene networks to screen key target genes of coronavirus disease 2019,which provides references for clinical research and development of drugs for coronavirus disease 2019.Methods:Target genes related to coronavirus disease 2019 were screened in the GeneCards and National Center for Biotechnology Information databases,and the obtained gene data were imported into the Database for Annotation,Visualization and Integrated Discovery(Version 6.8)database to collect the related information about pathways and genes.The genes enriched in the first 20 pathways and the genes whose occurrence frequency≥5 were imported into the String database respectively to construct protein-protein interaction network diagram and compare the two network diagrams.Results:TNF,IL-6,IL-2,IL-8,CXCL8,IL1B,CCL2,IFNG,STAT1,MAPK1,MAPK3,MAPK8,TP53 and RELA are ranked top in the two network diagrams,and the frequency of occurrence in the first 20 pathways was≥5.Conclusion:The incidence of coronavirus disease 2019 is associated with multiple signaling pathways,including influenza A,pathways in cancer,toll-like receptor signaling pathway,hypoxia-inducible factor-1 signaling pathway,et al.TNF,IL-6,IL-2,IL-8,CXCL8,IL1B,CCL2,IFNG,STAT1,MAPK1,MAPK3,MAPK8,TP53 and RELA are closely related to coronavirus disease 2019,which needs to be further studied.By analyzing the pathways of the genes related to coronavirus disease 2019 and the interactive network diagrams between the genes,it is helpful to understand the pathogenesis of the disease and provide a reference for clinical research and development of effective drugs for coronavirus disease 2019.
文摘This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology for solving the nonlinear partial differential equations, namely the Hamilton-Jacobi-Bellman and Hamilton-Jacobi-Isaacs equations through successive Galerkin’s approximation is implemented and the results are compared. Throughout the implementation, there were several caveats that need to be further resolved for practical applications in general cases. Such issues and the clarification of causes are mathematically established and reviewed.
文摘Analyzing gene network structure is an important way to discover and understand some unknown relevant functions and regulatory mechanisms of organism at the molecular level. In this work, mutual information networks and Boolean logic networks are constructed using the methods of reverse modeling based on gene expression profiles in lung tissues with and without cancer. The comparison of these network structures shows that average degree, the proportion of non-isolated nodes, average betweenness and average coreness can distinguish the networks corresponding to the lung tissues with and without cancer. According to the difference of degree, betweenness and coreness of each gene in these networks, nine structural key genes are obtained. Seven of them which are related to lung cancer are supported by literatures. The remaining two genes AKT1 and RBL may have important roles in the formation, development and metastasis of lung cancer. Furthermore, the contrast of these logic networks suggests that the distributions of logic types are obviously different. The structural differences can help us to understand the mechanism of formation and development of lung cancer.
文摘For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most important environmental stress factors that limits plant productivity worldwide. Today, transcriptomic approaches seem to give the best coverage of genome level responses. Therefore, microarray serves as an invaluable tool for global gene expression analyses, unravelling new information about gene pathways, in-species and cross-species gene expression comparison, and for the characterization of unknown relationships between genes. In this review we summarize the recent progress in the transcriptomics of ozone to demonstrate the benefits that can be harvested from the application of integrative and systematic analytical approaches to study ozone stress response. We focused our consideration on microarray analyses identifying gene networks responsible for response and tolerance to elevated ozone concentration. From these analyses it is now possible to notice how plant ozone defense responses depend on the interplay between many complex signaling pathways and metabolite signals.
基金This research is supported by the National Natural Science Foundation of China under Grant Nos. 60874036 and 60503002.
文摘The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the complicated regulation mechanism of shoot genes of Arabidopsis Thaliana in response to stimuli. The dynamics of the complicated logic network is analyzed, discussed, and simulated. The simulation results show that the logic network of the active genes of shoot eventually evolves into eleven attractors under the stimuli, including five 1-periodic and six 2-periodic attractors. Our work provides valuable reference and guidance for biologists to understand and explain Arabidopsis＇ response to external stimuli by experiments.
文摘Although genome-wide association studies （GWAS） have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET （Simultaneously Inference of GeNEs and Tissues） to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.
基金supported in part by the Natural Science Foundation of Education Department of Jiangsu Province(No.12KJB520019)the National Science Foundation of Jiangsu Province (No.BK20130452)+2 种基金Science and Technology Innovation Foundation of Yangzhou University (No.2012CXJ026)the National Natural Science Foundation of China (Nos.61070047,61070133,and 61003180)the National Key Basic Research and Development (973) Program of China (No.2012CB316003)
文摘The identification of communities is imperative in the understanding of network structures and functions.Using community detection algorithms in biological networks, the community structure of biological networks can be determined, which is helpful in analyzing the topological structures and predicting the behaviors of biological networks. In this paper, we analyze the diseasome network using a new method called disease-gene network detecting algorithm based on principal component analysis, which can be used to investigate the connection between nodes within the same group. Experimental results on real-world networks have demonstrated that our algorithm is more efficient in detecting community structures when compared with other well-known results.
基金Supported by the National Natural Science Foundation of China (Nos.61170183,61033003, and 91130034)the Foundation for the Excellent Middle-Aged and Youth Scientists of Shandong Province of China(No.BS2011SW025)
文摘The flowering time of Arabidopsis is sensitive to climate variability, with lighting conditions being a major determinant of the flowering time. Long-days induce early flowering, while short-days induce late flowering or even no flowers. This study investigates the intrinsic mechanisms for Arabidopsis flowering in different lighting conditions using mutual information networks and logic networks. The structure parameters of the mutual information networks show that the average degree and the average core clearly distinguish these networks. A method is then given to find the key structural genes in the mutual information networks and the logic networks respectively. Ten genes are found to possibly promote flowering with three genes that may restrain flowering. The sensitivity of this method to find the genes that promote flowering is 80%, while the sensitivity of the method to find the genes that restrain flowering is 100%.
基金This work was supported by the Strategic Priority Research Program and Innovation Program of the Chinese Academy of Sciences,China(Grant Nos.XDB32020100,XDA16010306,QYZDJ-SSW-SMC007,and GJHZ1827)the National Natural Science Foundation of China(Grant Nos.31730108,31430037,31571038,and 31871329)the Natural Science Foundation of Shanghai,China(Grant No.17ZR1413900).
文摘The association of Zika virus(ZIKV)infection with microcephaly has raised alarm worldwide.Their causal link has been confirmed in different animal models infected by ZIKV.However,the molecular mechanisms underlying ZIKV pathogenesis are far from clear.Hence,we performed global gene expression analysis of ZIKV-infected mouse brains to unveil the biological and molecular networks underpinning microcephaly.We found significant dysregulation of the sub-networks associated with brain development,immune response,cell death,microglial cell activation,and autophagy amongst others.We provided detailed analysis of the related complicated gene networks and the links between them.Additionally,we analyzed the signaling pathways that were likely to be involved.This report provides systemic insights into not only the pathogenesis,but also a path to the development of prophylactic and therapeutic strategies against ZIKV infection.
基金supported by the National Natural Science Foundation of China (20905009 and 21003010)the Logistics Management & Engineering Platform of Beijing Area Logistics System & Technology Major Laboratory, and Excellent Young Scholars Research Fund of Beijing Institute of Technology (2009 Y1017)
文摘The effects of noise and a periodic signal on a synthetic gene network have been investigated. By tuning the distance of a parameter from the Hopf bifurcation point, both implicit internal signal stochastic resonance and explicit internal signal stochastic resonance can be induced by noise. Furthermore, a switch process can also be elicited. When a periodic signal is coupled to the gene network, two interesting phenomena occur with the modulation of the frequency of the signal: the effect of noise amplifying cellular signal can be inhibited or even destroyed, and "locked" coherence resonance occurs.
基金ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation of China （No.20673106）.
文摘The feed forward loop （FFL）, wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small number of reactant molecules and thus internal molecular fluctuation is considerable. Here we studied how an FFL responds to small external signal inputs at gene X, with particular attention paid to the fluctuation resonance （FR） phenomenon of gene Z. We found that for all coherent FFLs, where the sign of the direct regulation path from X to Z is the same as the overall sign of the indirect path via Y, the FR shows a regular single peak, while for incoherent FFLs, the FR exhibits distinct bimodal shapes. The results indicate that one could use small external signals to help identify the regulatory structure of an unknown FFL in complex gene networks.
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
基金supported by the Hainan Province Science and Technology Talent Innovation Project(KJRC2023A02)Project of Sanya Yazhouwan Science and Technology City Management Foundation(SKJC-KJ-2019KY01)Sanya Science and Technology Special Fund(2022KJCX91)。
文摘The silver-lipped pearl oyster(Pinctada maxima)is the largest and most commercially valuable pearl-producing oyster,renowned for its ability to generate large,lustrous pearls.This species is a sequential hermaphrodite,with pearl production displaying notable sexual dimorphism.Consequently,understanding the molecular mechanisms governing sex determination and differentiation is crucial for advancing breeding strategies in the pearl oyster industry.To elucidate these mechanisms,this study conducted integrative transcriptomic analyses of P.maxima gonadal tissues using isoform sequencing(Isoseq)and RNA sequencing(RNA-seq).Comparative analysis of ovarian and testicular tissues identified 2768 differentially expressed genes(DEGs).Gene coexpression network analysis delineated four key modules,including three sex-specific modules and one shared module.Key genes implicated in sex determination and maintenance were identified,including FOXL2,NANOS1,andβ-catenin,important for ovarian maintenance,and DMRT,SOX30,FEM1,and FOXJ1,crucial for testicular maintenance.These genes,widely studied in other taxa,were confirmed as hub genes in the sex-related modules of P.maxima.Interestingly,genes within the shared module were significantly enriched in the spliceosome pathway.Alternative splicing analysis highlighted its extensive role in gonadal tissues,with more pronounced activity observed in the testis compared to the ovary.Nearly half(47.83%,375)of the identified genes undergoing differential alternative splicing(DASGs)also exhibited differential transcript usage(DTUGs),while only 17%of DTUGs overlapped with DEGs.Genes associated with sex differentiation,such as DMRT,β-catenin,and U2AF2,displayed sex-specific and/or sex-biased isoforms.These findings offer novel insights into the molecular basis of sex differentiation in P.maxima,which could inform the development of targeted breeding strategies aimed at sex control,thereby enhancing pearl quality and yield in aquaculture.This study offers a robust molecular foundation for advancing breeding programs and optimizing production in the pearl oyster industry.
基金supported by National Natural Science Foundation of China (Grant Nos. 60433020, 60175024 and 60773095)European Commission under grant No. TH/Asia Link/010 (111084)the Key Science-Technology Project of the National Education Ministry of China (Grant No. 02090),and the Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, P. R. China
文摘In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task in bioinformatics.The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determine the network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use of both simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.
基金supported by the Notional Natural Science Foundation of China,No.81960417 (to JX)Guangxi Key Research and Development Program,No.GuiKeA B20159027 (to JX)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,No.2022GXNSFBA035545 (to YG)。
文摘Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).
基金supported by the National Key Research and Development Program of China(2017YFA0505500)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB38040400)+1 种基金National Science Foundation of China(31771476 and 31930022)Shanghai Municipal Science and Technology Major Project(2017SHZDZX01)。
文摘Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples.Here,we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.
