Towards precise reconstruction of gene regulatory networks by data integration

Background: More and more high-throughput datasets are available from multiple levels of measuring gene regulations. The reverse engineering of gene regulatory networks from these data offers a valuable research paradigm to decipher regulatory mechanisms. So far, numerous methods have been developed for reconstructing gene regulatory networks. Results: In this paper, we provide a review of bioinformatics methods for inferring gene regulatory network from omics data. To achieve the precision reconstruction of gene regulatory networks, an intuitive alternative is to integrate these available resources in a rational framework. We also provide computational perspectives in the endeavors of inferring gene regulatory networks from heterogeneous data. We highlight the importance of multi-omics data integration with prior knowledge in gene regulatory network inferences. Conclusions: We provide computational perspectives of inferring gene regulatory networks from multiple omics data and present theoretical analyses of existing challenges and possible solutions. We emphasize on prior knowledge and data integration in network inferences owing to their abilities of identifying regulatory causality.     

Developmental control of cell division patterns in the shoot apex

The shoot apical meristem is a group of rapidly dividing cells that generate all aerial parts of the plant. It is a highly organised structure, which can be divided into functionally distinct domains, characterised by specific proliferation rates of the individual cells. Genetic studies have enabled the identification of regulators of meristem function. These factors are involved in the formation and maintenance of the meristem, as well as in the formation of the primordia. Somehow, they must also govern cell proliferation rates within the shoot apex. Possible links between meristem regulators and the cell cycle machinery will be discussed. In order to analyse the role of cell proliferation in development, cell cycle gene expression has been perturbed using transgenic approaches and mutation. The effect of these alterations on growth and development at the shoot apex will be presented. Together, these studies give a first insight into the regulatory networks controlling the cell cycle and into the significance of cell proliferation in plant development.     

Algebraic connectivity may explain the evolution of gene regulatory networks

Gene expression is a result of the interplay between the structure, type, kinetics, and specificity of gene regulatory interactions, whose diversity gives rise to the variety of life forms. As the dynamic behavior of gene regulatory networks depends on their structure, here we attempt to determine structural reasons which, despite the similarities in global network properties, may explain the large differences in organismal complexity. We demonstrate that the algebraic connectivity, the smallest non-trivial eigenvalue of the Laplacian, of the directed gene regulatory networks decreases with the increase of organismal complexity, and may therefore explain the difference between the variety of analyzed regulatory networks. In addition, our results point out that, for the species considered in this study, evolution favours decreasing concentration of strategically positioned feed forward loops, so that the network as a whole can increase the specificity towards changing environments. Moreover, contrary to the existing results, we show that the average degree, the length of the longest cascade, and the average cascade length of gene regulatory networks cannot recover the evolutionary relationships between organisms. Whereas the dynamical properties of special subnetworks are relatively well understood, there is still limited knowledge about the evolutionary reasons for the already identified design principles pertaining to these special subnetworks, underlying the global quantitative features of gene regulatory networks of different organisms. The behavior of the algebraic connectivity, which we show valid on gene regulatory networks extracted from curated databases, can serve as an additional evolutionary principle of organism-specific regulatory networks.     

批次和流加培养中国仓鼠卵巢工程细胞的细胞周期相关基因转录谱分析

以表达人重组尿激酶原中国仓鼠卵巢 (CHO) 工程细胞系11G-S为研究对象,运用基因芯片技术比较了CHO工程细胞在批次及流加培养不同生长阶段基因表达水平的差异,在此基础上采用Genmapp软件,同时结合已知的细胞周期信号通路图,着重分析了批次及流加培养CHO工程细胞的细胞周期调控基因转录谱差异。在基因芯片涉及的19 191个目标基因中,批次和流加培养不同生长阶段CHO工程细胞的下调表达的基因数量多于上调表达基因数目;两种培养模式下的基因差异表达有着明显的不同,尤其是在细胞生长的衰退期,流加培养CHO工程细胞中下调表达的基因数量明显多于批次培养。有关调控细胞周期关键基因的转录谱分析表明,CHO工程细胞主要是通过下调表达CDKs、Cyclin及CKI家族中的Cdk6、Cdk2、Cdc2a、Ccne1、Ccne2基因及上调表达Smad4基因,来达到调控细胞增殖及维持自身活力的目的。     

Modeling and simulation of genetic regulatory systems: a literature review.

In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between DNA, RNA, proteins, and small molecules. As most genetic regulatory networks of interest involve many components connected through interlocking positive and negative feedback loops, an intuitive understanding of their dynamics is hard to obtain. As a consequence, formal methods and computer tools for the modeling and simulation of genetic regulatory networks will be indispensable. This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equations, stochastic equations, and rule-based formalisms. In addition, the paper discusses how these formalisms have been used in the simulation of the behavior of actual regulatory systems.