Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interacti...Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.展开更多
To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empiri...To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empirical studies of the gene ontology with various perspectives, this paper shows that the whole gene ontology displays the same topological features as complex networks including ＂small world＂ and ＂scale-free＂,while some sub-ontologies have the ＂scale-free＂ property but no ＂small world＂ effect.The potential important terms in an ontology are discovered by some famous complex network centralization methods.An evaluation method based on information retrieval in MEDLINE is designed to measure the effectiveness of the discovered important terms.According to the relevant literature of the gene ontology terms,the suitability of these centralization methods for ontology important concepts discovering is quantitatively evaluated.The experimental results indicate that the betweenness centrality is the most appropriate method among all the evaluated centralization measures.展开更多
Taking AuCu3-type sublattice system as an example, three discoveries have been presented: First, the third barrier hindering the progress in metal materials science is that researchers have got used to recognizing exp...Taking AuCu3-type sublattice system as an example, three discoveries have been presented: First, the third barrier hindering the progress in metal materials science is that researchers have got used to recognizing experimental phenomena of alloy phase transitions during extremely slow variation in temperature by equilibrium thinking mode and then taking erroneous knowledge of experimental phenomena as selected information for establishing Gibbs energy function and so-called equilibrium phase diagram. Second, the equilibrium holographic network phase diagrams of AuCu3-type sublattice system may be used to describe systematic correlativity of the composition?temperature-dependent alloy gene arranging structures and complete thermodynamic properties, and to be a standard for studying experimental subequilibrium order-disorder transition. Third, the equilibrium transition of each alloy is a homogeneous single-phase rather than a heterogeneous two-phase, and there exists a single-phase boundary curve without two-phase region of the ordered and disordered phases; the composition and temperature of the top point on the phase-boundary curve are far away from the ones of the critical point of the AuCu3 compound.展开更多
Taking Au3Cu-type sublattice system as an example, three discoveries have been presented. First, the fourth barrier to hinder the progress of metal materials science is that today’s researchers do not understand that...Taking Au3Cu-type sublattice system as an example, three discoveries have been presented. First, the fourth barrier to hinder the progress of metal materials science is that today’s researchers do not understand that the Gibbs energy function of an alloy phase should be derived from Gibbs energy partition function constructed of alloy gene sequence and their Gibbs energy sequence. Second, the six rules for establishing alloy gene Gibbs energy partition function have been discovered, and it has been specially proved that the probabilities of structure units occupied at the Gibbs energy levels in the degeneracy factor for calculating configuration entropy should be degenerated as ones of component atoms occupied at the lattice points. Third, the main characteristics unexpected by today’s researchers are as follows. There exists a single-phase boundary curve without two-phase region coexisting by the ordered and disordered phases. The composition and temperature of the top point on the phase-boundary curve are far away from those of the critical point of the Au3Cu compound; At 0 K, the composition of the lowest point on the composition-dependent Gibbs energy curve is notably deviated from that of the Au3Cu compounds. The theoretical limit composition range of long range ordered Au3Cu-type alloys is determined by the first jumping order degree.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
MicroRNAs （miRNAs） are endogenous -22 nucleotide noncoding RNAs that regulate the expression of complementary messenger RNAs （mRNAs）. Thousands of miRNA genes have been found in diverse species, and many of them a...MicroRNAs （miRNAs） are endogenous -22 nucleotide noncoding RNAs that regulate the expression of complementary messenger RNAs （mRNAs）. Thousands of miRNA genes have been found in diverse species, and many of them are highly conserved. With the miRNA roles identified in nearly all aspects of biological processes, evidence is mounting that miRNAs could represent a new layer of regulatory network, and their regulatory effect might be much more pervasive than previously suspected. Here we focus on the posttranscriptional level gene regulation of miRNAs in animals and review how the miRNAs act to sustain and shape up the expression profiles of specific cell types; how the miRNAs integrate into the existing gene regulatory networks; and how the miRNAs influence the evolution of 3＇UTR of mammalian mRNAs.展开更多
Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abunda...Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abundance and bacterial communities in different WWTPs located at continental scales are still not comprehensively understood. Here, we applied quantitative PCR and Miseq sequence approaches to unveil the changing profiles of ARGs(sul1, sul2, tet W, tet Q, tet X), int I1 gene, and bacterial communities in 18 geographically distributed WWTPs. The results showed that the average relative abundance of sul1 and sul2 genes were 2.08 × 10^(-1) and 1.32 × 10^(-1) copies/16 S rRNA copies, respectively. The abundance of tet W gene was positively correlated with the Shannon diversity index(H′), while both studied sul genes had significant positive relationship with the int I1 gene. The highest average relative abundances of sul1, sul2, tet X, and int I1 genes were found in south region and oxidation ditch system. Network analysis found that 16 bacterial genera co-occurred with tet W gene. Co-occurrence patterns were revealed distinct community interactions between aerobic/anoxic/aerobic and oxidation ditch systems. The redundancy analysis model plot of the bacterial community composition clearly demonstrated that the sludge samples were significant differences among those from the different geographical areas,and the shifts in bacterial community composition were correlated with ARGs. Together,these findings from the present study will highlight the potential risks of ARGs and bacterial populations carrying these ARGs, and enable the development of suitable technique to control the dissemination of ARGs from WWTPs into aquatic environments.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
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
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
Axon regeneration is crucial for recovery from neurological diseases. Numerous studies have identified several genes, microRNAs （miRNAs）, and transcription factors （TFs） that influence axon regeneration. However, ...Axon regeneration is crucial for recovery from neurological diseases. Numerous studies have identified several genes, microRNAs （miRNAs）, and transcription factors （TFs） that influence axon regeneration. However, the regulatory networks involved have not been fully elucidated. In the present study, we analyzed a regulatory network of 51 miRNAs, 27 TFs, and 59 target genes, which is involved in axon regeneration. We identified 359 pairs of feed- forward loops （FFLs）, seven important genes （Naplll, Arhgef12, Sema6d, Akt3, Trim2, Rabllfip2, and Rps6ka3）, six important miRNAs （hsa-miR-204-5p, hsa-miR-124-3p, hsa-miR-26a-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa- miR-15b-5p）, and eight important TFs （Smada2, Flil, Wtl, Sp6, Sp3, Smad4, Smad5, and Crebl）, which appear to play an important role in axon regeneration. Functional enrichment analysis revealed that axon-associated genes are involved mainly in the regulation of cellular component organization, axonogenesis, and cell morphogenesis during neuronal differentiation. However, these findings need to be validated by further studies.展开更多
Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic ca...Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.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
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t...Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.展开更多
This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga...This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga- tion artificial neural network （BPANN）. We established the model based on data gathered from metabolic syndrome patients （n = 1012） and normal controls （n = 1069） by BPANN. Mean impact value （MIV） for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction （GMDR） confirmed a joint effect of PPAR-9＂ and RXR-a based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk fac- tors were in the order of body mass index （BMI）, serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 （rs4240711, rs4842194, rs2920502 and rs3856806） models were the best models （cross-validation consistency 10/10, P = 0.0107） with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.展开更多
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
Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair perip...Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.展开更多
Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actu...Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly. In this paper, we propose a novel approach based on combining neuro-fu^zy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory nctworks＋ but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without lhctitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast, The results show that this approach can work effectively.展开更多
Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compa...Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compacta（SNpc）results in a severe and gradual depletion of dopamine content in the striatum,a phenomena that is responsible for the characteristic motor symptoms of this disease.展开更多
We developed a computational framework to identify common gene association sub-network. This framework combines graphical lasso model, graph product and a replicator equation based clique solver. We applied this metho...We developed a computational framework to identify common gene association sub-network. This framework combines graphical lasso model, graph product and a replicator equation based clique solver. We applied this method to find common stress responsive sub-networks from two related Deinococcus-Thermus bacterial species.展开更多
基金supported by the National Natural Science Foundation of China(32222064 and 32341030)the Natural Science Foundation of Shanghai(22ZR1445800)Zhejiang Provincial Natural Science Foundation of China(LQ24C130008).
文摘Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.
基金The National Basic Research Program of China (973Program) (No.2005CB321802)Program for New Century Excellent Talents in University (No.NCET-06-0926)the National Natural Science Foundation of China (No.60873097,90612009)
文摘To resolve the ontology understanding problem, the structural features and the potential important terms of a large-scale ontology are investigated from the perspective of complex networks analysis. Through the empirical studies of the gene ontology with various perspectives, this paper shows that the whole gene ontology displays the same topological features as complex networks including ＂small world＂ and ＂scale-free＂,while some sub-ontologies have the ＂scale-free＂ property but no ＂small world＂ effect.The potential important terms in an ontology are discovered by some famous complex network centralization methods.An evaluation method based on information retrieval in MEDLINE is designed to measure the effectiveness of the discovered important terms.According to the relevant literature of the gene ontology terms,the suitability of these centralization methods for ontology important concepts discovering is quantitatively evaluated.The experimental results indicate that the betweenness centrality is the most appropriate method among all the evaluated centralization measures.
基金Project(51071181)supported by the National Natural Science Foundation of ChinaProject(2013FJ4043)supported by the Natural Science Foundation of Hunan Province,China
文摘Taking AuCu3-type sublattice system as an example, three discoveries have been presented: First, the third barrier hindering the progress in metal materials science is that researchers have got used to recognizing experimental phenomena of alloy phase transitions during extremely slow variation in temperature by equilibrium thinking mode and then taking erroneous knowledge of experimental phenomena as selected information for establishing Gibbs energy function and so-called equilibrium phase diagram. Second, the equilibrium holographic network phase diagrams of AuCu3-type sublattice system may be used to describe systematic correlativity of the composition?temperature-dependent alloy gene arranging structures and complete thermodynamic properties, and to be a standard for studying experimental subequilibrium order-disorder transition. Third, the equilibrium transition of each alloy is a homogeneous single-phase rather than a heterogeneous two-phase, and there exists a single-phase boundary curve without two-phase region of the ordered and disordered phases; the composition and temperature of the top point on the phase-boundary curve are far away from the ones of the critical point of the AuCu3 compound.
基金Project(51071181)supported by the National Natural Science Foundation of ChinaProject(2013FJ4043)supported by the Natural Science Foundation of Hunan Province,China
文摘Taking Au3Cu-type sublattice system as an example, three discoveries have been presented. First, the fourth barrier to hinder the progress of metal materials science is that today’s researchers do not understand that the Gibbs energy function of an alloy phase should be derived from Gibbs energy partition function constructed of alloy gene sequence and their Gibbs energy sequence. Second, the six rules for establishing alloy gene Gibbs energy partition function have been discovered, and it has been specially proved that the probabilities of structure units occupied at the Gibbs energy levels in the degeneracy factor for calculating configuration entropy should be degenerated as ones of component atoms occupied at the lattice points. Third, the main characteristics unexpected by today’s researchers are as follows. There exists a single-phase boundary curve without two-phase region coexisting by the ordered and disordered phases. The composition and temperature of the top point on the phase-boundary curve are far away from those of the critical point of the Au3Cu compound; At 0 K, the composition of the lowest point on the composition-dependent Gibbs energy curve is notably deviated from that of the Au3Cu compounds. The theoretical limit composition range of long range ordered Au3Cu-type alloys is determined by the first jumping order degree.
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 Basic Research Program of China (973 Program) (No. 2006CB701506 and 2007CB815705)the Chinese Academy of Sciences (No. KSCX1-YW-R-34)+1 种基金the National Natural Science Foundation of China (No. 30525028, 30630013 and 30871343)the Natural Science Foundation of Yunnan Province of China.
文摘MicroRNAs （miRNAs） are endogenous -22 nucleotide noncoding RNAs that regulate the expression of complementary messenger RNAs （mRNAs）. Thousands of miRNA genes have been found in diverse species, and many of them are highly conserved. With the miRNA roles identified in nearly all aspects of biological processes, evidence is mounting that miRNAs could represent a new layer of regulatory network, and their regulatory effect might be much more pervasive than previously suspected. Here we focus on the posttranscriptional level gene regulation of miRNAs in animals and review how the miRNAs act to sustain and shape up the expression profiles of specific cell types; how the miRNAs integrate into the existing gene regulatory networks; and how the miRNAs influence the evolution of 3＇UTR of mammalian mRNAs.
基金supported by the International Science and Technology Cooperation Program(No.2018KW-011)the National Key Research and Development Program of China(No.2016YFC0400706)+1 种基金the grant from "Young Outstanding Talents" in Universities of Shaanxi Provincesupport from the "Yanta Outstanding Youth Scholar" project from Xi'an University of Architecture and Technology(XAUAT)
文摘Wastewater treatment plants(WWTPs) are deemed reservoirs of antibiotic resistance genes(ARGs). Bacterial phylogeny can shape the resistome in activated sludge. However, the co-occurrence and interaction of ARGs abundance and bacterial communities in different WWTPs located at continental scales are still not comprehensively understood. Here, we applied quantitative PCR and Miseq sequence approaches to unveil the changing profiles of ARGs(sul1, sul2, tet W, tet Q, tet X), int I1 gene, and bacterial communities in 18 geographically distributed WWTPs. The results showed that the average relative abundance of sul1 and sul2 genes were 2.08 × 10^(-1) and 1.32 × 10^(-1) copies/16 S rRNA copies, respectively. The abundance of tet W gene was positively correlated with the Shannon diversity index(H′), while both studied sul genes had significant positive relationship with the int I1 gene. The highest average relative abundances of sul1, sul2, tet X, and int I1 genes were found in south region and oxidation ditch system. Network analysis found that 16 bacterial genera co-occurred with tet W gene. Co-occurrence patterns were revealed distinct community interactions between aerobic/anoxic/aerobic and oxidation ditch systems. The redundancy analysis model plot of the bacterial community composition clearly demonstrated that the sludge samples were significant differences among those from the different geographical areas,and the shifts in bacterial community composition were correlated with ARGs. Together,these findings from the present study will highlight the potential risks of ARGs and bacterial populations carrying these ARGs, and enable the development of suitable technique to control the dissemination of ARGs from WWTPs into aquatic environments.
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 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 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.
基金Project supported by the Key Project of Hebei North University(No.120177)the Science and Technology Bureau Research Development Plan of Zhangjiakou City in Hebei(No.0911021D-4)China
文摘Axon regeneration is crucial for recovery from neurological diseases. Numerous studies have identified several genes, microRNAs （miRNAs）, and transcription factors （TFs） that influence axon regeneration. However, the regulatory networks involved have not been fully elucidated. In the present study, we analyzed a regulatory network of 51 miRNAs, 27 TFs, and 59 target genes, which is involved in axon regeneration. We identified 359 pairs of feed- forward loops （FFLs）, seven important genes （Naplll, Arhgef12, Sema6d, Akt3, Trim2, Rabllfip2, and Rps6ka3）, six important miRNAs （hsa-miR-204-5p, hsa-miR-124-3p, hsa-miR-26a-5p, hsa-miR-16-5p, hsa-miR-17-5p, and hsa- miR-15b-5p）, and eight important TFs （Smada2, Flil, Wtl, Sp6, Sp3, Smad4, Smad5, and Crebl）, which appear to play an important role in axon regeneration. Functional enrichment analysis revealed that axon-associated genes are involved mainly in the regulation of cellular component organization, axonogenesis, and cell morphogenesis during neuronal differentiation. However, these findings need to be validated by further studies.
基金partially supported by a Merit-Reviewed grant from the Department of Veterans Affairsa Peer-Reviewed Cancer Research Program grant from the Department of Defense (W81XWH-16-1-0488) to Y-FCL
文摘Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.
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).
文摘Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.
基金supported by the National Natural Science Foundation of China Grant No.30771858Jiangsu Provincial Natural Science Foundation Grant No.BK2007229Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga- tion artificial neural network （BPANN）. We established the model based on data gathered from metabolic syndrome patients （n = 1012） and normal controls （n = 1069） by BPANN. Mean impact value （MIV） for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction （GMDR） confirmed a joint effect of PPAR-9＂ and RXR-a based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk fac- tors were in the order of body mass index （BMI）, serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 （rs4240711, rs4842194, rs2920502 and rs3856806） models were the best models （cross-validation consistency 10/10, P = 0.0107） with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.
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 the National Major Project of Research and Development of China,No.2017YFA0104701(to BY)the National Natural Science Foundation of China,No.32000725(to QQC)+1 种基金the Natural Science Foundation of Jiangsu Province of China,No.BK20200973(to QQC)the Jiangsu Provincial University Innovation Training Key Project of China,No.202010304021Z(to ML)。
文摘Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.
基金Acknowledgement This paper is supported by National Natural Science Foundation of China （Grant No. 60973092 and No. 60873146）, the National High Technology Research and Development Program of China （Grant No.2009 AA02Z307）, the ＂211 Project＂ of Jilin University, the Key Laboratory for Symbol Computation and Knowledge Engineering （Ministry of Education, China）, and the Key Laboratory for New Technology of Biological Recognition of Jilin Province （No. 20082209）.
文摘Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly. In this paper, we propose a novel approach based on combining neuro-fu^zy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory nctworks＋ but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without lhctitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast, The results show that this approach can work effectively.
基金supported by FONDECYT-11140738 (G.M.).Michael J. Fox Foundation for Parkinson Research, Ring Initiative ACT1109+1 种基金FONDEF D11I1007 (C.H.). We also thank, FONDECYT-1140549Millennium Institute P09-015-F, COPEC-UC, and Frick Foundation (C.H.). V.C. is supported by CONICYT fellowship
文摘Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compacta（SNpc）results in a severe and gradual depletion of dopamine content in the striatum,a phenomena that is responsible for the characteristic motor symptoms of this disease.
文摘We developed a computational framework to identify common gene association sub-network. This framework combines graphical lasso model, graph product and a replicator equation based clique solver. We applied this method to find common stress responsive sub-networks from two related Deinococcus-Thermus bacterial species.
