动态基因调控网演化分析

动态基因调控网是展现生物体内基因与基因之间相互关系随时间变化而变化的动力学行为的复杂网络.这种相互作用关系可以分为两类:激励和抑制.对动态基因调控网网络演化的研究,可以预测未来时刻生物体内的基因调控关系,从而在疾病预测和诊断、药物开发、生物学实验等领域起到重要的指导和辅助作用.现实世界中,动态基因调控网的网络演化是一个复杂而巨大的系统,当前,对于其演化机制的研究存在只关注静态网络而忽略动态网络和只关注相互作用关系而忽略相互作用类型的缺陷.针对上述问题,提出了一种动态基因调控网演化分析方法(dynamic gene regulatory network evolution analyzing method,简称DGNE),将研究扩展到了动态带符号网络领域.通过该方法包含的基于模体转换概率的连边预测算法(link prediction algorithm based on motif transfer probability,简称MT)和基于隐空间特征的符号判别算法,能够动态地捕捉基因调控网的演化机制,并准确地预测未来时刻基因调控网的连边情况.实验结果表明,DGNE方法在仿真数据集和真实数据集上均有良好的表现.

三类基因振子和它们的基本动力学

蛋白质作为基因调控过程的产物,它的丰度的周期变化处在重要细胞过程的心脏.把基因振子分为3类:松弛型基因振子、规则型基因振子和随机型基因振子.我们分析了它们的基本动力学,显示出它们有不同的动力学性质.例如,松弛振子展示出跳跃动力行为,规则振子展示出规则的极限环,而随机振子展示出连贯共振.这种分类对系统地研究基因振子和它们的群体行为将起着重要的作用.

松弛型基因随机振子的同步和聚类

松弛型基因随机振子是三类基因振子(光滑振子、松弛振子和随机振子)中的一种.具有相抑制耦合细胞通信的这种类基因振子的同步与聚类是一个有趣且令人关注的问题。这里,数值模拟显示出振子之间的相差分布能够展示出单峰、双峰或多峰分布,但依赖于噪声强度和细胞密度。而且,数值地发现存在细胞数目的一个阈值,当细胞数目超过此阈值时,对于任意的噪声强度相差分布函数的峰值性几乎保持不变。这些结果表明抑制耦合的松弛型随机振子具有不同于普通耦合的光滑或松弛振子的同步与聚类机制。

Fluctuation Resonance of Feed Forward Loops in Gene Regulatory Networks

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.

Conditional Mutations in Drosophila

The aim of this study was to obtain unusual mutations called conditional. The mutations manifest in some, not all representatives of a species. Collections of these mutations in chromosomes X, 2, and 3 of Drosophila melanogaster were established. Sex of fly or chromosomal rearrangement was the conditions providing ＂manifestation-non manifestation＂ of these mutations. The mutations differ from the usual by a set of properties. The salient differences in addition to conditional manifestation include： manifestation dependence on the spatial arrangement of chromosomal material in the genome, parental effects （maternal or paternal） of the mutant, capacity for transferring the genome from stable to unstable state. It is suggested that conditional mutations are mutant variants of Drosophila regulatory genes contained by the large Genomic Regulatory Network of Drosophila. Thus, the genes of this category can be detected by using special breeding procedures, mutations of these genes have unusual manifestation.

Peak identification for ChlP-seq data with no controls

Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.

Stochastic Nature in Cellular Processes

The importance of stochasticity in cellular processes is increasingly recognized in both theoretical andexperimental studies.General features of stochasticity in gene regulation and expression are briefly reviewed in thisarticle,which include the main experimental phenomena,classification,quantization and regulation of noises.Thecorrelation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methodsthat can capture effects of intrinsic and extrinsic noise are described.

The Simulation Gene Regulatory Boolean Network based on the Seauential Circuit

Along with the completion of HGP （human genome project）, huge amounts of genetic data constantly emerge. Research suggests that genes are not in independent existence and the expression of a gene will promote or inhibit the expression of another gene; if the expression of a gene makes the biochemical environment of ceils changed, the expression of a series of genes will be affected. In order to get a better understanding of the relationship between genes, all sorts of gene regulatory network models have been established by scientists. In this paper, a variety of gene regulatory networks are first introduced according to the process of this subject research, and then the most basic network （i.e. Boolean network） is emphatically analyzed, and then a new method （i.e. Boolean network based on the theory of circuit） to describe Boolean network is drawn forth. After the shortcomings of the Boolean network proposed in the past are analyzed, a simulation circuit Boolean model is established using EDA technology in order to improve the Boolean network.

生物信息学中基因数据可视化

科学可视化技术是进行生物数据挖掘的重要手段。本文综合介绍了主要的基因数据可视化技术 :各种基因调控网、层次树显示、信息壁技术。

Role ofthe IncRNA-p53 regulatory network in cancer

Advances in functional genomics have led to discovery of a large group of previous uncharacterized long non-coding RNAs （IncRNAs）. Emerging evidence indicates that IncRNAs may serve as master gene regulators through various mechanisms. Dysregulation of IncRNAs is often associated with a variety of human diseases including cancer. Of significant interest, recent studies suggest that IncRNAs participate in the p53 tumor suppressor regulatory network. In this review, we discuss how IncRNAs serve as p53 regulators or p53 effectors. Further characterization of these p53-associated IncRNAs in cancer will provide a better understanding of lncRNA- mediated gene regulation in the p53 pathway. As a result, IncRNAs may prove to be valuable biomarkers for cancer diagnosis or poten- tial targets for cancer therapy.

Causes and consequences of the Cambrian explosion

The Cambrian explosion has long been a basic research frontier that concerns many scientific fields. Here we discuss the cause-effect links of the Cambrian explosion on the basis of first appearances of animal phyla in the fossil record, divergence time, environmental changes, Gene Regulatory Networks, and ecological feedbacks. The first appearances of phyla in the fos- sil record are obviously diachronous but relatively abrupt, concentrated in the first three stages of the Cambrian period （541- 514 Ma）. The actual divergence time may be deep or shallow. Since the gene regulatory networks （GRNs） that control the de- velopment of metazoans were in place before the divergence, the establishment of GRNs is necessary but insufficient for the Cambrian explosion. Thus the Cambrian explosion required environmental triggers. Nutrient availability, oxygenation, and change of seawater composition were potential environmental triggers. The nutrient input, e.g., the phosphorus enrichment in the environment, would cause excess primary production, but it is not directly linked with diversity or disparity. Further in- crease of oxygen level and change of seawater composition during the Ediacaran-Cambrian transition were probably crucial environmental factors that caused the Cambrian explosion, but more detailed geochemical data are required. Many researchers prefer that the Cambrian explosion is an ecological phenomenon, that is, the unprecedented ecological success of ruetazoans during the Early Cambrian, but ecological effects need diverse and abundant animals. Therefore, the establishment of the eco- logical complexity among animals, and between animals and environments, is a consequence rather than a cause of the Cam- brian explosion. It is no doubt that positive ecological feedbacks could facilitate the increase of biodiversity. In a word, the Cambrian explosion happened when environmental changes crossed critical thresholds, led to the initial formation of the meta- zoan-doruinated ecosystem through a series of knock-on ecological processes, i.e., ＂ecological snowball＂ effects.

The effect of transposable elements on phenotypic variation： insights from plants to humans

Transposable elements(TEs), originally discovered in maize as controlling elements, are the main components of most eukaryotic genomes. TEs have been regarded as deleterious genomic parasites due to their ability to undergo massive amplification. However, TEs can regulate gene expression and alter phenotypes. Also, emerging findings demonstrate that TEs can establish and rewire gene regulatory networks by genetic and epigenetic mechanisms. In this review, we summarize the key roles of TEs in fine-tuning the regulation of gene expression leading to phenotypic plasticity in plants and humans, and the implications for adaption and natural selection.

Transposable elements play an important role during cotton genome evolution and fiber cell development

Transposable elements(TEs)usually occupy largest fractions of plant genome and are also the most variable part of the structure.Although traditionally it is hallmarked as"junk and selfish DNA",today more and more evidence points out TE’s participation in gene regulations including gene mutation,duplication,movement and novel gene creation via genetic and epigenetic mechanisms.The recently sequenced genomes of diploid cottons Gossypium arboreum(AA)and Gossypium raimondii(DD)together with their allotetraploid progeny Gossypium hirsutum(At At Dt Dt)provides a unique opportunity to compare genome variations in the Gossypium genus and to analyze the functions of TEs during its evolution.TEs accounted for 57%,68.5%and67.2%,respectively in DD,AA and At At Dt Dt genomes.The 1,694 Mb A-genome was found to harbor more LTR(long terminal repeat)-type retrotransposons that made cardinal contributions to the twofold increase in its genome size after evolution from the 775.2 Mb D-genome.Although the 2,173 Mb At At Dt Dt genome showed similar TE content to the A-genome,the total numbers of LTR-gypsy and LTR-copia type TEs varied significantly between these two genomes.Considering their roles on rewiring gene regulatory networks,we believe that TEs may somehow be involved in cotton fiber cell development.Indeed,the insertion or deletion of different TEs in the upstream region of two important transcription factor genes in At or Dt subgenomes resulted in qualitative differences in target gene expression.We suggest that our findings may open a window for improving cotton agronomic traits by editing TE activities.

Regulation network and expression profiles of Epstein-Barr virus-encoded microRNAs and their potential target host genes in nasopharyngeal carcinomas

Epstein-Barr virus(EBV)is associated with nasopharyngeal carcinoma(NPC)tumorigenesis.However,the mechanism(s)connecting EBV infection and NPC remain unclear.Recently,a new class of EBV microRNAs(miRNAs)has been described.To determine how EBV miRNAs control the expression of host genes,and to understand their potential role in NPC tumorigenesis,we profiled the expression of 44 mature EBV miRNAs and potential host genes in NPC and non-tumor nasopharyngeal epithelial tissues.We found that 40 EBV miRNAs from the BART transcript were highly expressed in NPC.Analysis of potential BART miRNA target genes revealed that 3140 genes and several important pathways might be involved in the carcinogenesis of NPC.A total of 105 genes with potential EBV miRNA binding sites were significantly downregulated,suggesting that EBV miRNAs may regulate these genes and contribute to NPC carcinogenesis.An EBV miRNA and host gene regulation network was generated to provide useful clues for validating of EBV miRNA functions in NPC tumorigenesis.

microRNAs in a multicellular green alga Volvox carteri

microRNAs(miRNAs)have emerged as key components in the eukaryotic gene regulatory network.We and others have previously identified many miRNAs in a unicellular green alga,Chlamydomonas reinhardtii.To investigate whether miRNA-mediated gene regulation is a general mechanism in green algae and how miRNAs have been evolved in the green algal lineage,we examined small RNAs in Volvox carteri,a multicellular species in the same family with Chlamydomonas reinhardtii.We identified 174 miRNAs in Volvox,with many of them being highly enriched in gonidia or somatic cells.The targets of the miRNAs were predicted and many of them were subjected to miRNA-mediated cleavage in vivo,suggesting that miRNAs play regulatory roles in the biology of green algae.Our catalog of miRNAs and their targets provides a resource for further studies on the evolution,biological functions,and genomic properties of miRNAs in green algae.

Single cell atlas of developing mouse dental germs reveals populations of CD24^(+)and Plac8^(+)odontogenic cells

The spatiotemporal relationships in high-resolution during odontogenesis remain poorly understood.We report a cell lineage and atlas of developing mouse teeth.We performed a large-scale(92,688 cells)single cell RNA sequencing,tracing the cell trajectories during odontogenesis from embryonic days 10.5 to 16.5.Combined with an assay for transposase-accessible chromatin with high-throughput sequencing,our results suggest that mesenchymal cells show the specific transcriptome profiles to distinguish the tooth types.Subsequently,we identified key gene regulatory networks in teeth and bone formation and uncovered spatiotemporal patterns of odontogenic mesenchymal cells.CD24^(+)and Plac8^(+)cells from the mesenchyme at the bell stage were distributed in the upper half and preodontoblast layer of the dental papilla,respectively,which could individually induce nonodontogenic epithelia to form tooth-like structures.Specifically,the Plac8^(+)tissue we discovered is the smallest piece with the most homogenous cells that could induce tooth regeneration to date.Our work reveals previously unknown heterogeneity and spatiotemporal patterns of tooth germs that may lead to tooth regeneration for regenerative dentistry.

Genes and regulatory networks involved in persistence of Mycobacterium tuberculosis

The causative agent of tuberculosis,Mycobacterium tuberculosis,is one of the most successful of human pathogens.It can evade the host immune response and establish a persistent infection or enter a dormant state within the host which can be reactivated if the host becomes immuno-compromised.Both of these features are major obstacles to tuberculosis eradication.Dormancy and reactivation of M.tuberculosis are tightly coordinated dynamic processes involving numerous genes and their products.Molecular mechanisms underlying M.tuberculosis persistence may provide an opportunity for the discovery of effective drug targets for tuberculosis control.Here,we review the genes required for M.tuberculosis persistence and propose a regulatory network for the action of these genes using text mining.This should provide fresh insights into the persistence mechanisms of M.tuberculosis and suggest candidates for new drug targets and immune intervention.

Screening and regulatory network analysis of survival-related genes of patients with colorectal cancer

The purpose of this study was to screen key survival-related genes from patients with colorectal cancer and explore signal transduction network of the involved genes.In a previous study,survival-related genes of patients with colorectal cancer were selected by colorectal cancer-related expression data GSE17538 using the Significance Analysis of Microarrays(SAM3.01)software,and 235 genes related to the survival of patients with colorectal cancer were obtained.Therefore,the following screening and analysis were conducted on these 235 genes in this study.First,the enrichment analysis of transcription factor binding sites was conducted on the 235 genes.Genes with more than seven transcription factor binding sites were screened.Then,these genes and upregulated genes in colorectal cancer were intersected.Finally,survival analysis and regulatory network analysis were conducted on the screened genes.This allowed clarification of the relationship between these genes and the survival of patients with colorectal cancer and the signaling network involving these genes in the cell signal transduction network of colorectal cancer.Through the above analysis,six upregulated genes in colorectal cancer related to the survival of colorectal cancer patients and highly regulated by transcription factors were selected,namely STX2,PODXL,KLK6,GRB10,EHBP1 and CREB5.These genes are involved in signal regulatory networks related to colorectal cancer metastasis-related signaling pathways.Therefore,the survival of patients with colorectal cancer is closely correlated with colorectal cancer metastasis.The six survival-related genes affect the survival of patients by regulating colorectal cancer metastasis-associated signaling pathways.

Topological origin of global attractors in gene regulatory networks

Fixed-point attractors with global stability manifest themselves in a number of gene regulatory networks. This property indicates the stability of regulatory networks against small state perturbations and is closely related to other complex dynamics. In this paper, we aim to reveal the core modules in regulatory networks that determine their global attractors and the relationship between these core modules and other motifs. This work has been done via three steps. Firstly, inspired by the signal transmission in the regulation process, we extract the model of chain-like network from regulation networks. We propose a module of "ideal transmission chain(ITC)", which is proved sufficient and necessary(under certain condition) to form a global fixed-point in the context of chain-like network. Secondly, by examining two well-studied regulatory networks(i.e., the cell-cycle regulatory networks of Budding yeast and Fission yeast), we identify the ideal modules in true regulation networks and demonstrate that the modules have a superior contribution to network stability(quantified by the relative size of the biggest attraction basin). Thirdly, in these two regulation networks, we find that the double negative feedback loops, which are the key motifs of forming bistability in regulation, are connected to these core modules with high network stability. These results have shed new light on the connection between the topological feature and the dynamic property of regulatory networks.

MODELING GENETIC REGULATORY NETWORKS:A DELAY DISCRETE DYNAMICAL MODEL APPROACH

Modeling genetic regulatory networks is an important research topic in genomic research and computationM systems biology. This paper considers the problem of constructing a genetic regula- tory network （GRN） using the discrete dynamic system （DDS） model approach. Although considerable research has been devoted to building GRNs, many of the works did not consider the time-delay effect. Here, the authors propose a time-delay DDS model composed of linear difference equations to represent temporal interactions among significantly expressed genes. The authors also introduce interpolation scheme and re-sampling method for equalizing the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed genetic network using linear multiple regression matches with the original data very well. Simulation results are given to demonstrate the effectiveness of the proposed method and model.