Transcriptional Regulatory Networks Activated by PI3K and ERK Transduced Growth Signals in Human Glioblastoma Cells

Determining how cells regulate their transcriptional response toextracellular signals is key to the understanding of complex eukaryotic systems. This study wasinitiated with the goals of furthering the study of mammalian transcriptional regulation andanalyzing the relative benefits of related computational methodologies. One dataset available forsuch an analysis involved gene expression profiling of the early growth factor response to plateletderived growth factor (PDGF) in a human glioblastoma cell line; this study differentiated geneswhose expression was regulated by signaling through the phosphoinositide-3-kinase (PI3K) versus theextracellular-signal regulated kinase (ERK) pathways. We have compared the inferred transcriptionfactors from this previous study with additional predictions of regulatory transcription factorsusing two alternative promoter sequence analysis techniques. This comparative analysis, in which thealgorithms predict overlapping, although not identical, sets of factors, argues for meticulousbenchmarking of promoter sequence analysis methods to determine the positive and negative attributesthat contribute to their varying results. Finally, we inferred transcriptional regulatory networksderiving from various signaling pathways using the CARRIE program suite. These networks not onlyincluded previously described transcriptional features of the response to growth signals, but alsopredicted new regulatory features for the propagation and modulation of the growth signal.

The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network （TRN） for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model. While many large-scale TRN reconstructions have been reported for yeast, these reconstructions still need to be improved regarding the functionality and dynamic property of the regulatory interactions. In addition, mathematical modeling approaches need to be further developed to efficiently integrate transcriptional regulatory interactions to genome-scale metabolic models in a quantitative manner.

Single-cell RNA-Seq reveals transcriptional regulatory networks directing the development of mouse maxillary prominence

During vertebrate embryonic development,neural crest-derived ectomesenchyme within the maxillary prominences undergoes precisely coordinated proliferation and differentiation to give rise to diverse craniofacial structures,such as tooth and palate.However,the transcriptional regulatory networks underpinning such an intricate process have not been fully elucidated.Here,we perform single-cell RNA-Seq to comprehensively characterize the transcriptional dynamics during mouse maxillary development from embryonic day(E)10.5eE14.5.Our single-cell transcriptome atlas of~28,000 cells uncovers mesenchymal cell populations representing distinct differentiating states and reveals their developmental trajectory,suggesting that the segregation of dental from the palatal mesenchyme occurs at E11.5.Moreover,we identify a series of key transcription factors(TFs)associated with mesenchymal fate transitions and deduce the gene regulatory networks directed by these TFs.Collectively,our study provides important resources and insights for achieving a systems-level understanding of craniofacial morphogenesis and abnormality.

A Vertex Network Model of Arabidopsis Leaf Growth

Biology provides many examples of complex systems whose properties allow organisms to develop in a highly reproducible,or robust,manner.One such system is the growth and development of flat leaves in Arabidopsis thaliana.This mechanistically challenging process results from multiple inputs including gene interactions,cellular geometry,growth rates,and coordinated cell divisions.To better understand how this complex genetic and cellular information controls leaf growth,we developed a mathematical model of flat leaf production.This two-dimensional model describes the gene interactions in a vertex network of cells which grow and divide according to physical forces and genetic information.Interestingly,the model predicts the presence of an unknown additional factor required for the formation of biologically realistic gene expression domains and iterative cell division.This two-dimensional model will form the basis for future studies into robustness of adaxial-abaxial patterning.

Identification of the target genes of AhTWRKY24 and AhTWRKY106 transcription factors reveals their regulatory network in Arachis hypogaea cv.Tifrunner using DAP-seq

WRKY transcription factors(TFs)have been identified as important core regulators in the responses of plants to biotic and abiotic stresses.Cultivated peanut(Arachis hypogaea)is an important oil and protein crop.Previous studies have identified hundreds of WRKY TFs in peanut.However,their functions and regulatory networks remain unclear.Simultaneously,the AdWRKY40 TF is involved in drought tolerance in Arachis duranensis and has an orthologous relationship with the AhTWRKY24 TF,which has a homoeologous relationship with AhTWRKY106 TF in A.hypogaea cv.Tifrunner.To reveal how the homoeologous AhTWRKY24 and AhTWRKY106 TFs regulate the downstream genes,DNA affinity purification sequencing(DAP-seq)was performed to detect the binding sites of TFs at the genome-wide level.A total of 3486 downstream genes were identified that were collectively regulated by the AhTWRKY24 and AhTWRKY106 TFs.The results revealed that W-box elements were the binding sites for regulation of the downstream genes by AhTWRKY24 and AhTWRKY106 TFs.A gene ontology enrichment analysis indicated that these downstream genes were enriched in protein modification and reproduction in the biological process.In addition,RNA-seq data showed that the AhTWRKY24 and AhTWRKY106 TFs regulate differentially expressed genes involved in the response to drought stress.The AhTWRKY24 and AhTWRKY106 TFs can specifically regulate downstream genes,and they nearly equal the numbers of downstream genes from the two A.hypogaea cv.Tifrunner subgenomes.These results provide a theoretical basis to study the functions and regulatory networks of AhTWRKY24 and AhTWRKY106 TFs.

基于单细胞多组学数据解析结直肠癌动态调控扰动

目的探讨结直肠癌恶性转变过程中的分子特征及其调控网络扰动,深入剖析结直肠癌恶性转变的微环境异质性并识别潜在治疗靶点。方法首先从Gene Expression Omnibus(GEO)数据库中收集单细胞转录组测序数据,从欧洲分子生物学实验室(EMBL)收集单细胞ATAC测序数据。数据共涉及来自14例患者的70例样本,包含22例正常样本、43例息肉样本和5例肿瘤样本。首先对scRNA-Seq测序数据进行预处理,基于Seurat包筛除双细胞和低质量细胞,对scATAC-Seq测序数据使用10X Cell Ranger-atac进行原始数据处理,并使用Signac包去除低质量细胞,得到三个阶段的scRNA-Seq和scATAC-Seq细胞图谱。进一步数据整合,基于Pando R包推断T细胞和上皮细胞的转录调控网络,通过mfinder软件分析网络motif和拓扑属性,对转录因子进行分级分析。最后,基于随机森林算法进行细胞分子特征预测及预后分析。结果筛选出202465个scRNA-Seq测序细胞和136422个scATAC-Seq测序细胞。基于数据整合分析,构建不同癌变阶段的细胞图谱。结果发现,随着结直肠癌进展,肿瘤微环境组成发生显著变化,尤其是T细胞和上皮细胞在不同疾病阶段的比例有较大差异。基于单细胞多组学数据整合,利用Pando包推断结直肠癌不同阶段的转录调控网络,揭示了T细胞和上皮细胞中转录因子及其调控关系的动态变化。功能富集分析结果显示在T细胞和上皮细胞中,转录因子所调控的功能在不同的疾病阶段有明显差异。基于转录调控网络分析发现,T细胞和上皮细胞转录调控网络符合无标度网络特性。网络motif分析揭示了在不同阶段存在的特定motif模式,反映了网络拓扑结构的动态变化,且网络中大多数相互作用都具有阶段特异性。共享转录因子的层级在癌变过程中也会发生变化。最后基于转录因子调控网络构建的分类器可以成功识别T细胞和上皮细胞,表明其作为细胞分子特征的有效性。进一步识别出与患者生存显著相关的网络motif,揭示其在结直肠癌预后中的潜在作用。结论基于整合单细胞多组学数据构建转录调控网络,解析随结直肠癌的进展转录调控网络及其功能的动态变化,揭示了结直肠癌进展过程中的细胞分子特征及关键预后motif,为结直肠癌的分子机制及预后评估提供了深刻见解。

A PtrLBD39-mediated transcriptional network regulates tension wood formation in Populus trichocarpa

Tension wood(TW)is a specialized xylem tissue formed in angiosperm trees under gravitational stimulus or mechanical stresses(e.g.,bending).The genetic regulation that underlies this important mechanism remains poorly understood.Here,we used laser capture microdissection of stem xylem cells coupled with full transcriptome RNA-sequencing to analyze TW formation in Populus trichocarpa.After tree bending,PtrLBD39 was the most significantly induced transcription factor gene;it has a phylogenetically paired homolog,PtrLBD22.CRISPR-based knockout of PtrLBD39/22 severely inhibited TW formation,reducing cellulose and increasing lignin content.Transcriptomic analyses of CRISPR-based PtrLBD39/22 double mutants showed that these two genes regulate a set of TW-related genes.Chromatin immunoprecipitation sequencing(ChIP-seq)was used to identify direct targets of PtrLBD39.We integrated transcriptomic analyses and ChIP-seq assays to construct a transcriptional regulatory network(TRN)mediated by PtrLBD39.In this TRN,PtrLBD39 directly regulates 26 novel TW-responsive transcription factor genes.Our work suggests that PtrLBD39 and PtrLBD22 specifically control TW formation by mediating a TW-specific TRN in Populus.

Single-cell analysis of transcription factor regulatory networks reveals molecular basis for subtype-specific dysregulation in acute myeloid leukemia

Highly heterogeneous acute myeloid leukemia(AML)exhibits dysregulated transcriptional programs.Transcription factor(TF)regulatory networks underlying AML subtypes have not been elucidated at single-cell resolution.Here,we comprehensively mapped malignancy-related TFs activated in different AML subtypes by analyzing single-cell RNA sequencing data from AMLs and healthy donors.We first identified six modules of regulatory networks which were prevalently dysregulated in all AML patients.AML subtypes featured with different malignant cellular composition possessed subtype-specific regulatory TFs associated with differentiation suppression or immune modulation.At last,we validated that ERF was crucial for the development of hematopoietic stem/progenitor cells by performing loss-and gain-of-function experiments in zebrafish embryos.Collectively,our work thoroughly documents an abnormal spectrum of transcriptional regulatory networks in AML and reveals subtype-specific dysregulation basis,which provides a prospective view to AML pathogenesis and potential targets for both diagnosis and therapy.

m^(6)A相关基因在激素性股骨头坏死中的生物信息学分析

背景:m^(6)A修饰与股骨头坏死的发生发展相关,但在激素性股骨头坏死中的作用尚不清楚。目的:基于GEO数据库,采用生物信息学方法分析激素性股骨头坏死中表达差异的m^(6)A基因及互作miRNAs,探寻其潜在发病机制。方法:在GEO数据库中检索并下载与激素性股骨头坏死相关的mRNA表达谱数据集(GSE123568),通过R软件对数据集进行差异基因筛选及GO功能、KEGG通路富集分析。识别差异基因中的m^(6)A差异表达基因(m^(6)A-DEGs)并对其进行GO功能与KEGG通路富集分析,比较m^(6)A-DEGs的表达量并分析它们之间的相关性。最后通过Cytoscape构建m^(6)A-DEGs的PPI互作网络及筛选核心基因。使用TargetScan,miRTarBase和miRBD数据库预测m^(6)A-DEGs相关的潜在miRNAs,同时使用ChIPBase及hTFtarget数据库预测7个核心基因潜在转录因子,然后分别构建m^(6)A-miRNA与转录因子m^(6)A调控网络。最后使用数据集GSE74089验证7个核心m^(6)A-DEGs的表达水平。结果与结论:①从数据集中共筛选出2460个差异表达的基因,其中1455个上调,1005个下调。②从数据集中筛选出了14个m^(6)A-DEGs,包括3个下调和11个上调基因,m^(6)A-DEGs在激素性股骨头坏死中的表达具有显著差异(P<0.05),Spearman分析表明它们之间具有一定相关性。③m^(6)A-DEGs的GO和KEGG富集分析主要集中在骨髓细胞分化与发育、免疫受体与细胞因子受体活性、破骨细胞分化、AMPK与白细胞介素17信号通路。④m^(6)A-DEGs前7个核心基因包括YTHDF3,YTHDF1,YTHDF2,ALKBH5,METTL3,HNRNPA2B1及HNRNPC,它们在miRTarBase,miRDB和TargetScan数据库中共有44个miRNA重叠,在ChIPBase及hTFtarget数据库中共有79个重叠转录因子。⑤在GSE74089数据集中有6个核心m^(6)A-DEGs的表达水平与GSE123568数据集一致。⑥结果证实,根据生物信息学方法筛选的7个m^(6)A-DEGs可能通过调控多个miRNA、转录因子和AMPK及白细胞介素17信号通路表达,进而影响激素性股骨头坏死中骨髓细胞分化发育与破骨细胞分化,为进一步深入研究激素性股骨头坏死的发病机制和靶向治疗提供了数据支持和研究方向。

基于GEO数据库和转录因子调控网络的结核病药物作用靶点筛选及其作用机制

目的基于GEO数据库和转录因子调控网络筛选抗结核病药物及药物作用靶点。方法通过NCBI的GEO数据库,筛选结核病患者和健康者之间差异表达的基因;通过AnimalTFDB 3.0数据库预测差异表达基因中的转录因子,并构建转录因子调控网络;通过调控网络中的关键基因筛选相关miRNA,并筛选关键节点,初步阐明结核病致病的分子机制。结果通过GEO数据库检索,筛选出的差异表达基因为784个;通过AnimalTFDB 3.0数据库筛选出23个转录因子和对应的790个靶基因,构建了转录因子-靶基因的调控网络;通过TargetScanHuman 7.2查询到关键节点对应的miRNA,构建“转录因子-靶基因-miRNA”调控网络,筛选出4个结核病药物靶点(EP300,CREBBP,ELAVL1,HSP90AA1),阐明了其与转录因子和miRNA之间的调控机制。结论通过构建结核“转录因子-靶基因-miRNA”网络,筛选出结核病新的潜在药物作用靶点——EP300、CREBBP、ELAVL1、HSP90AA1;同时发现,EP300、CREBBP、HSP90AA1通过激活转录因子STAT2,导致机体内炎症因子TNF-α水平增高,进而抑制了miR-9-5p的表达;而基因ELAVL1直接抑制miR-9-5p的表达,并且与NOD-like receptor signaling pathay通路密切相关,导致结核病的发生发展。

癌症中甲基化改变对增强子活性的影响

目的 分析识别癌症中甲基化改变对增强子活性的影响。方法 分别从人类增强子数据库FANTOM5、甲基化DNA结合转录因子数据库MeDReaders及分子特征数据库MSigDB中获取增强子、转录因子结合位点及分子通路数据等信息,识别受甲基化影响的活性增强子、正常与癌症差异甲基化增强子和探针,并在CpG Island上注释,根据增强子和基因的共表达情况进一步识别增强子甲基化调控的靶基因并在泛癌模块中进行功能富集分析,最后进行COX比例风险回归分析与功能分析模式的识别。结果 共识别出1 155个受甲基化调控的增强子,其对应的探针大部分是在癌症中表现差异甲基化的探针,少数在癌症中受甲基化调控的增强子所对应的探针没有表现出差异甲基化。根据增强子和基因的共表达筛选出的靶基因和癌症相关通路有关,这些基因还参与到癌症相关(P53通路)、转录相关(transcript通路)、信号转导相关以及代谢相关等重要功能的通路中;在膀胱尿路上皮癌中存在很多三元组合与生存相关,这些靶基因还分布在癌症相关通路以及其他生命健康相关通路中。结论 本研究系统分析了癌症中受甲基化影响的增强子调控,识别了关键的增强子通过调控重要的靶基因参与癌症发生发展的功能。

Conservation and Diversification of the SHR-SCR- SCL23 Regulatory Network in the Development of the Functional Endodermis in Arabidopsis Shoots

Development of the functional endodermis of Arabidopsis thaliana roots is controlled, in part, by GRAS transcription factors, namely SHORT-ROOT （SHR）, SCARECROW （SCR）, and SCARECROW-LIKE 23 （SCL23）. Recently, it has been shown that the SHR-SCR-SCL23 regulatory module is also essential for spec- ification of the endodermis （known as the bundle sheath） in leaves. Nevertheless, compared with what is known about the role of the SHR-SCR-SCL23 regulatory network in roots, the molecular interactions of SHR, SCR, and SCL23 are much less understood in shoots. Here, we show that SHR forms protein com- plexes with SCL23 to regulate transcription of SCL23 in shoots, similar to the regulation mode of SCR expression. Our results indicate that SHR acts as master regulator to directly activate the expression of SCR and SCL23. In the SHR-SCR-SCL23 network, we found a previously uncharacterized negative feed- back loop whereby SCL23 modulates SHR levels. Through molecular, genetic, physiological, and morpho- logical analyses, we also reveal that the SHR-SCR-SCL23 module plays a key role in the formation of the endodermis （known as the starch sheath） in hypocotyls. Taken together, our results provide new insights into the regulatory role of the SHR-SCR-SCL23 network in the endodermis development in both roots and shoots.

Roles of NAC transcription factors in cotton

Climate deterioration,water shortages,and abiotic stress are the main threats worldwide that seriously affect cotton growth,yield,and fiber quality.Therefore,research on improving cotton yield and tolerance to biotic and abiotic stresses is of great importance.The NAC proteins are crucial and plant-specific transcription factors(TFs)that are involved in cotton growth,development,and stress responses.The comprehensive utilization of cotton NAC TFs in the improvement of cotton varieties through novel biotechnological methods is feasible.Based on cotton genomic data,genome-wide identification and analyses have revealed potential functions of cotton NAC genes.Here,we comprehensively summarize the recent progress in understanding cotton NAC TFs roles in regulating responses to drought,salt,and Verticillium wilt-related stresses,as well as leaf senescence and the development of fibers,xylem,and glands.The detailed regulatory network of NAC proteins in cotton is also elucidated.Cotton NAC TFs directly bind to the promoters of genes associated with ABA biosynthesis and secondary cell-wall formation,participate in several biological processes by interacting with related proteins,and regulate the expression of downstream genes.Studies have shown that the overexpression of NAC TF genes in cotton and other model plants improve their drought or salt tolerance.This review elucidates the latest findings on the functions and regulation of cotton NAC proteins,broadens our understanding of cotton NAC TFs,and lays a fundamental foundation for further molecular breeding research in cotton.

Local Changes in Chromatin Accessibility and Transcriptional Networks Underlying the Nitrate Response in Arabidopsis Roots

Transcriptional regulation,determined by the chromatin structure and regulatory elements interacting at pro-moter regions,is a key step in plant responses to environmental cues.Nitrate(NO3-)is a nutrient signal that regulates the expression of hundreds of genes in Arabidopsis thaliana.Here,we integrate mRNA sequencing,genome-wide RNA polymeraseⅡ(RNPⅡ),chromatin immunoprecipitation sequencing,and DNase Sequencing datasets to establish the relationship between RNPⅡoccupancy and chromatin accessibility in response to NO3-treatments in Arabidopsis roots.Genomic footprinting allowed us to identify in vivo regula-tory elements controlling gene expression in response to NO3-treatments.NO3--modulated transcription factor(TF)footprints are important for a rapid increase in RNPⅡoccupancy and transcript accumulation over time.We mapped key TF regulatory interactions and functionally validated the role of NAP,an NAC-domain containing TF,as a new regulatory factor in NO3-transport.Taken together,our study provides a comprehensive view of transcriptional networks in response to a nutrient signal in Arabidopsis roots.

MINI-EX:Integrative inference of single-cell gene regulatory networks in plants

Multicellular organisms,such as plants,are characterized by highly specialized and tightly regulated cell populations,establishing specific morphological structures and executing distinct functions.Gene regulatory networks(GRNs)describe condition-specific interactions of transcription factors(TFs)regulating the expression of target genes,underpinning these specific functions.As efficient and validated methods to identify cell-type-specific GRNs from single-cell data in plants are lacking,limiting our understanding of the organization of specific cell types in both model species and crops,we developed MINI-EX(Motif-Informed Network Inference based on single-cell EXpression data),an integrative approach to infer cell-type-specific networks in plants.MINI-EX uses single-cell transcriptomic data to define expression-based networks and integrates TF motif information to filter the inferred regulons,resulting in networks with increased accuracy.Next,regulons are assigned to different cell types,leveraging cell-specific expression,and candidate regulators are prioritized using network centrality measures,functional annotations,and expression specificity.This embedded prioritization strategy offers a unique and efficient means to unravel signaling cascades in specific cell types controlling a biological process of interest.We demonstrate the stability of MINI-EX toward input data sets with low number of cells and its robustness toward missing data,and show that it infers state-of-the-art networks with a better performance compared with other related single-cell network tools.MINI-EX successfully identifies key regulators controlling root development in Arabidopsis and rice,leaf development in Arabidopsis,and ear development in maize,enhancing our understanding of cell-type-specific regulation and unraveling the roles of different regulators controlling the development of specific cell types in plants.

CNEReg Interprets Ruminant-specific Conserved Non-coding Elements by Developmental Gene Regulatory Network

The genetic information coded in DNA leads to trait innovation via a gene regulatory network(GRN)in development.Here,we developed a conserved non-coding element interpretation method to integrate multi-omics data into gene regulatory network(CNEReg)to investigate the ruminant multi-chambered stomach innovation.We generated paired expression and chromatin accessibility data during rumen and esophagus development in sheep,and revealed 1601 active ruminantspecific conserved non-coding elements(active-RSCNEs).To interpret the function of these activeRSCNEs,we defined toolkit transcription factors(TTFs)and modeled their regulation on rumenspecific genes via batteries of active-RSCNEs during development.Our developmental GRN revealed 18 TTFs and 313 active-RSCNEs regulating 7 rumen functional modules.Notably,6 TTFs(OTX1,SOX21,HOXC8,SOX2,TP63,and PPARG),as well as 16 active-RSCNEs,functionally distinguished the rumen from the esophagus.Our study provides a systematic approach to understanding how gene regulation evolves and shapes complex traits by putting evo-devo concepts into practice with developmental multi-omics data.

Differential signaling regulatory networks governing hormone refractory prostate cancers

To understand the organization of the biological networks that might potentially govern the pathogenesis of hormone refractory prostate cancer （HRPC）, we investigated the transcriptional circuitry and signaling in androgen-dependent 22Rvl and MDA PCa 2b cells, androgen- and estrogen-dependent LNCaP cells, and androgen-independent DU 145 and PC-3 prostate cancer （PCa） cell lines. We used microarray analyses, quantitative real-time PCR, pathway prediction analyses, and determination of Transcription Factor Binding Site （TFBS） signatures to dissect HRPC regulatory networks. We generated graphical representations of global topology and local network motifs that might be important in prostate carcinogenesis. Many important putative biomarker ＇target hubs＇ were identified in the current study including AP-1, NF-KB, EGFR, ERK1/2, JNK, p38 MAPK, TGF beta, VEGF, PDGF, CD44, Akt, PI3K, NOTCH1, CASP1, MMP2 and AR. Our results suggest that complex cellular events including autoregulation, feedback loops and cross-talk might govern progression from early lesion to clinically diagnosed PCa, as well as metastatic potential of pre-existent high-grade prostate intraepithelial neoplasia （HG-PIN） and/or advancement to HRPC. The identification of TFBS signatures for TCF/LEF, SOX9 and ELK1 in the regulatory elements suggests additional biomarkers for the potential development of chemopreventive/therapeutic strategies against PCa. Taken together, in this study, we have identified putative biomarker ＇target hubs＇ in the architecture of PCa signaling networks, and investigated TFBS signatures that might enhance our understanding of key regulatory nodes in the progression and pathogenesis of HRPC.

Regulatory network established by transcription factors transmits drought stress signals in plant

Plants are sessile organisms that evolve with a flexible signal transduction system in order to rapidly respond to environmental changes.Drought,a common abiotic stress,affects multiple plant developmental processes especially growth.In response to drought stress,an intricate hierarchical regulatory network is established in plant to survive from the extreme environment.The transcriptional regulation carried out by transcription factors(TFs)is the most important step for the establishment of the network.In this review,we summarized almost all the TFs that have been reported to participate in drought tolerance(DT)in plant.Totally 466 TFs from 86 plant species that mostly belong to 11 families are collected here.This demonstrates that TFs in these 11 families are the main transcriptional regulators of plant DT.The regulatory network is built by direct protein-protein interaction or mutual regulation of TFs.TFs receive upstream signals possibly via post-transcriptional regulation and output signals to downstream targets via direct binding to their promoters to regulate gene expression.

ModuleNet:An R package on regulatory network building

Many researchers have used microarray gene expression data to investigate gene regulatory networks in specific life stages. In these analyses,Bayesian network was widely applied to regulatory network building from expression profiles because of its solid mathematical foundation and its robust analysis ability in noisy data. However,the building of Bayesian network is time consuming and the searching space is really large. Considering the biological feature of transcription factors (TFs) and targets (TGs),the regulatory network is possible to be separated into core TFs networks and the interactions from TFs to TGs. We developed an R package named ModuleNet which used Bayesian network model to the inner TFs network building and genetic algorithm on TF-TG interactions prediction. With determined number of transcription factors,the searching space and time requirements of ModuleNet is linear increasing according to the number of targets. After application to yeast cell-cycle expression profile,the results demonstrated the prediction accuracy of ModuleNet. Furthermore,significantly enriched Gene Ontology (GO) terms with similar expression behaviors were detected automatically by ModuleNet from expression profile,and the relationships from TFs to GO terms were figured out. The source code is available by asking for the author.

植物WRKY转录因子家族研究进展

WRKY转录因子是植物中最大的转录调控因子家族之一,是调控植物许多生物过程信号网络的组成部分。WKRY转录因子具有多种生物学功能,在植物的生长发育和衰老、非生物和生物胁迫等过程中发挥着重要的作用。在DNA水平上,WRKY转录因子可与靶基因启动子中的W-box TTGAC(C/T)结合,通过自调节或交叉调节激活或抑制下游基因的表达调控其反应。在蛋白水平上,WRKY转录因子可以与多种蛋白相互作用,包括MAP激酶、组蛋白去乙酰化酶、抗性R蛋白、多种转录因子等,调节植物的生长发育或各种应激反应。对WRKY转录因子的结构特征、生物学功能、调控机制和网络等方面进行了综述,有助于更加全面了解其在植物中的作用。