On parametric stability of gene networks controlling ontogenetic processes

The problem of evaluating the parametric stability of three models of pro- and eukaryotic gene networks controlling ontogenetic processes has been defined and solved. Experimental plans of testing gene networks for parametric stability based on the method of generalized threshold models were developed and realized as a software application. We examined the "sensitivity" of the functioning modes to random variations of the parameters in the three model systems: the system of developmental control of phage lambda, the subsystem of morphogenetic control of Arabidopsis thaliana flower, and the gene subnetwork controlling early ontogeny in Drosophila melanogaster. The parametric stability was quantitatively assessed for these models.     

On Parametric Stability of Gene Networks Controlling Ontogenetic Processes

The problem of evaluation of parametric stability of three models of pro- and eukaryotic gene networks controlling ontogenetic processes has been defined and solved. Experimental schemes of testing gene networks for parametric stability based on the method of generalized threshold models were developed and realized as a software application. We studied the sensitivity of the functioning modes to random variations of the parameters in three model systems: phage development control system, Arabidopsis thaliana flower morphogenesis control subsystem, and gene subnetwork controlling early ontogeny of Drosophila melanogaster. The parametric stability was quantitatively assessed for these models.     

Modeling real eukaryotic control gene subnetworks based on generalized threshold models]

Mathematical and computational means are developed that take into consideration the specifics of control processes at the molecular level and allow one to obtain both qualitative and quantitative patterns of gene network dynamics. Using the method of generalized threshold models, models are constructed for the Arabidopsis thaliana flower morphogenesis control subsystem and gene subnetwork controlling the Drosophila melanogaster early ontogeny. The dynamics of these systems are investigated: kinetic curves are computed for molecular components (RNA, proteins), possible modes of functioning and steady states of the nets are revealed and biologically interpreted. The models are shown to be adequate to the real processes. The effectiveness of the generalized threshold model method is evaluated in the analysis of the actual eukaryotic gene networks.     

Modeling of Actual Eukaryotic Control Gene Subnetworks Based on the Method of Generalized Threshold Models

Mathematical and computational means are developed that take into consideration the specifics of control processes at the molecular level and allow one to obtain both qualitative and quantitative patterns of gene network dynamics. Using the method of generalized threshold models, models are constructed for the Arabidopsis thalianaflower morphogenesis control subsystem and gene subnetwork controlling the Drosophila melanogasterearly ontogeny. The dynamics of these systems are investigated: kinetic curves are computed for molecular components (RNA, proteins), possible modes of functioning and steady states of the nets are revealed and biologically interpreted. The models are shown to be adequate to the real processes. The effectiveness of the generalized threshold model method is evaluated in the analysis of the actual eukaryotic gene networks.     

Phase sensitivity analysis of circadian rhythm entrainment

As a biological clock, circadian rhythms evolve to accomplish a stable (robust) entrainment to environmental cycles, of which light is the most obvious. The mechanism of photic entrainment is not known, but two models of entrainment have been proposed based on whether light has a continuous (parametric) or discrete (nonparametric) effect on the circadian pacemaker. A novel sensitivity analysis is developed to study the circadian entrainment in silico based on a limit cycle approach and applied to a model of Drosophila circadian rhythm. The comparative analyses of complete and skeleton photoperiods suggest a trade-off between the contribution of period modulation (parametric effect) and phase shift (nonparametric effect) in Drosophila circadian entrainment. The results also give suggestions for an experimental study to (in)validate the two models of entrainment.     

Drosophila, an emerging model for cardiac disease

A variety of studies that are currently underway may validate the fruit fly as an in vivo model for analyzing genes involved in cardiac function. Many mutations in conserved genetic pathways have been found, including those controlling development and physiology. Because homologous genes control early developmental events as well as functional components of the Drosophila and vertebrate hearts, the fly is the simplest existing model system that can be used to assay genes involved in human congenital heart disease (CHD). The wide variety of genetic tools available to Drosophila researchers offers many technical advantages for rapidly screening through large numbers of candidate genes. Thus, an important future and long-term direction is likely to be the use of Drosophila as a vehicle for analyzing polygenic traits as an aid in human genetics. One can anticipate a time in the not too distant future when mutant lines exist for every gene in vertebrate systems, such as mice and zebrafish. However, one of the enduring problems that will not easily be addressed by such resources will be the tracking of complex traits defined by polygenic variants. For this level of genetic analysis, simple genetic model systems including yeast, Caenorhabditis elegans, and Drosophila melanogaster will undoubtedly play a crucial ongoing role. Of them, Drosophila will be critical for examining gene networks involved in organogenesis and is clearly the system of choice for studying cardiac development, function and aging, since among the simple genetic models it is the only one with a fluid pumping heart.     

Genetic modifiers of tauopathy in Drosophila

In Alzheimer's disease and related disorders, the microtubule-associated protein Tau is abnormally hyperphosphorylated and aggregated into neurofibrillary tangles. Mutations in the tau gene cause familial frontotemporal dementia. To investigate the molecular mechanisms responsible for Tau-induced neurodegeneration, we conducted a genetic modifier screen in a Drosophila model of tauopathy. Kinases and phosphatases comprised the major class of modifiers recovered, and several candidate Tau kinases were similarly shown to enhance Tau toxicity in vivo. Despite some clinical and pathological similarities among neurodegenerative disorders, a direct comparison of modifiers between different Drosophila disease models revealed that the genetic pathways controlling Tau and polyglutamine toxicity are largely distinct. Our results demonstrate that kinases and phosphatases control Tau-induced neurodegeneration and have important implications for the development of therapies in Alzheimer's disease and related disorders.     

Genetic control of meiosis in Drozophila

By the beginning of 2000, more than 80 genes specifically controlling meiosis and meiotic recombination in Drosophila melanogaster have been described. Meiosis in Drosophila is different from the classical model. In females, these differences concern cytological features of prophase I, which have no principal genetic significance. Drosophila males lack lateral synapsis of chromosomes, recombination and chiasmata, and their chromosomes segregate in meiosis I following the "touch-and-go" principle. Meiotic genes in Drosophila can be classified according to their functions as affecting prerequisites for recombination and crossing over, controlling chromosome segregation in meiosis I separately in males and females and controlling sister-chromatid segregation in meiosis II in both sexes. Some meiotic genes are pleiotropic. There are meiotic genes controlling mitosis, and vice versa. Some genes for DNA repair in somatic cells are also involved in meiosis. Meiotic genes in Drosophila are compared with their counterparts in other organisms.     

Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraction in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average.     

Computational models for neurogenic gene expression in the Drosophila embryo

The early Drosophila embryo is emerging as a premiere model system for the computational analysis of gene regulation in development because most of the genes, and many of the associated regulatory DNAs, that control segmentation and gastrulation are known. The comprehensive elucidation of Drosophila gene networks provides an unprecedented opportunity to apply quantitative models to metazoan enhancers that govern complex patterns of gene expression during development. Models based on the fractional occupancy of defined DNA binding sites have been used to describe the regulation of the lac operon in E. coli and the lysis/lysogeny switch of phage lambda. Here, we apply similar models to enhancers regulated by the Dorsal gradient in the ventral neurogenic ectoderm (vNE) of the early Drosophila embryo. Quantitative models based on the fractional occupancy of Dorsal, Twist, and Snail binding sites raise the possibility that cooperative interactions among these regulatory proteins mediate subtle differences in the vNE expression patterns. Variations in cooperativity may be attributed to differences in the detailed linkage of Dorsal, Twist, and Snail binding sites in vNE enhancers. We propose that binding site occupancy is the key rate-limiting step for establishing localized patterns of gene expression in the early Drosophila embryo.     

A model with asymptotically stable dynamics for the network of Drosophila gap genes

A model of the expression of gap genes during the early development of Drosophila embryo has been studied. The parameter values for the model have been obtained by fitting the solutions to experimental patterns under an additional assumption of the asymptotic stability of solutions at large times. The patterns at the beginning of gastrulation in these solutions are very close to the actual attractor in the model. It is shown that these solutions have a better stability, or robustness, to perturbations of concentrations and parameter values in the model.     

一类含间隙分布时滞的种群增长模型的稳定性

本文首先利用间隙分布时滞函数来建立更为符合实际的种群增长模型,然后运用两种不同的方法,对其平衡位置的局部稳定性进行了全面的讨论,得出了局部渐近稳定的充分必要条件,在参数平面上划分出了稳定和不稳地的区域。     

Simultaneous identification of robust synergistic subnetwork markers for effective cancer prognosis

Background

Accurate prediction of cancer prognosis based on gene expression data is generally difficult, and identifying robust prognostic markers for cancer remains a challenging problem. Recent studies have shown that modular markers, such as pathway markers and subnetwork markers, can provide better snapshots of the underlying biological mechanisms by incorporating additional biological information, thereby leading to more accurate cancer classification.

Results

In this paper, we propose a novel method for simultaneously identifying robust synergistic subnetwork markers that can accurately predict cancer prognosis. The proposed method utilizes an efficient message-passing algorithm called affinity propagation, based on which we identify groups – or subnetworks – of discriminative and synergistic genes, whose protein products are closely located in the protein-protein interaction (PPI) network. Unlike other existing subnetwork marker identification methods, our proposed method can simultaneously identify multiple nonoverlapping subnetwork markers that can synergistically predict cancer prognosis.

Conclusions

Evaluation results based on multiple breast cancer datasets demonstrate that the proposed message-passing approach can identify robust subnetwork markers in the human PPI network, which have higher discriminative power and better reproducibility compared to those identified by previous methods. The identified subnetwork makers can lead to better cancer classifiers with improved overall performance and consistency across independent cancer datasets.

     

利用果蝇心力衰竭模型筛选果蝇第2号染色体缺失系

果蝇心脏一直以来都是研究心血管发育的极好模型,许多控制心脏分化和特化的调控基因和信号途径从果蝇到哺乳动物都是保守的.由于近年心力衰竭的发病率不断升高,我们最近又建立了果蝇心力衰竭模型用于大规模筛选和鉴定心力衰竭的相关基因.在这个模型中,适龄的成体果蝇被整齐排列在导电的载玻片上,通过电极短暂刺激30s,使果蝇的心跳频率由正常的3Hz增加到6Hz,停止后检测果蝇心率恢复情况,不能恢复正常心跳频率或出现纤维性震颤的果蝇视为心力衰竭.该模型可以在短期内大规模筛选到与心力衰竭相关的基因.利用此心力衰竭模型,我们筛选了164个果蝇2号染色体缺失系,获得33个候选缺失系.这些候选缺失系的心衰率要么与野生型品系相比差异显著,要么与tinman或panier突变系相比差异显著,提示这些缺失系中可能含有与心力衰竭相关的调控基因.     

Drosophila: a "model" model system to study neurodegeneration

The fruit fly, Drosophila melanogaster, is a powerful model genetic organism that has been used since the turn of the previous century in the study of complex biological problems. In the last decade, numerous researchers have focused their attention on understanding neurodegenerative diseases by utilizing this model system. Numerous Drosophila mutants have been isolated that profoundly affect neural viability and integrity of the nervous system with age. Additionally, many transgenic strains have been developed as models of human disease conditions. We review the existing Drosophila neurodegenerative mutants and transgenic disease models, and discuss the role of the fruit fly in therapeutic development for neurodegenerative diseases.     

Structural analysis of the Drosophila rpA1 gene, a member of the eucaryotic ''A'' type ribosomal protein family.

The expression of ribosomal protein (r-protein) genes is uniquely regulated at the translational level during early development of Drosophila. Here we report results of a detailed analysis of the r-protein rpA1 gene. A cloned DNA sequence coding for rpA1 has been identified by hybrid-selected translation and amino acid composition analysis. The rpA1 gene was localized to polytene chromosome band 53CD. The nucleotide sequence of the rpA1 gene and its cDNA have been determined. rpA1 is a single copy gene and sequence comparison between the gene and its cDNA indicates that this r-protein gene is intronless. Allelic restriction site polymorphisms outside of the gene were observed, while the coding sequence is well conserved between two Drosophila strains. The protein has unusual domains rich in Ala and charged residues. The rpA1 is homologous to the "A" family of eucaryotic acidic r-proteins which are known to play a key role in the initiation and elongation steps of protein synthesis.