Gene set analysis exploiting the topology of a pathway

Background  

Recently, a great effort in microarray data analysis is directed towards the study of the so-called gene sets. A gene set is defined by genes that are, somehow, functionally related. For example, genes appearing in a known biological pathway naturally define a gene set. The gene sets are usually identified from a priori biological knowledge. Nowadays, many bioinformatics resources store such kind of knowledge (see, for example, the Kyoto Encyclopedia of Genes and Genomes, among others). Although pathways maps carry important information about the structure of correlation among genes that should not be neglected, the currently available multivariate methods for gene set analysis do not fully exploit it.     

GAGE: generally applicable gene set enrichment for pathway analysis

Background  

Gene set analysis (GSA) is a widely used strategy for gene expression data analysis based on pathway knowledge. GSA focuses on sets of related genes and has established major advantages over individual gene analyses, including greater robustness, sensitivity and biological relevance. However, previous GSA methods have limited usage as they cannot handle datasets of different sample sizes or experimental designs.     

介导心肌肥大的一条新的信号通路--Calcineurin通路

心肌肥大是心肌细胞对外界刺激,如工作负荷、神经体液因子及内在心肌蛋白遗传突变一种基本应答。已知胞内Ｃａ＾２＋浓度升高在各种刺激诱导心肌肥大的信号传递中起重要作用,但对Ｃａ＾２＋信号下游的传递机制一直不甚清楚。新近研究证实,由Ｃａ＾２＋活化的钙调神经磷酸酶（ＣａＮ）在心肌肥大的信号传递中起重要作用,基可能是Ｃａ＾２＋信号致肥大基因活化的偶联环节。抑制ＣａＮ活性可阻滞各种因素诱导的心肌肥大发生与发展,     

Iron bioavailability to phytoplankton: an empirical approach

Phytoplankton are often limited by iron in aquatic environments. Here we examine Fe bioavailability to phytoplankton by analyzing iron uptake from various Fe substrates by several species of phytoplankton grown under conditions of Fe limitation and comparing the measured uptake rate constants (Fe uptake rate/ substrate concentration). When unchelated iron, Fe′, buffered by an excess of the chelating agent EDTA is used as the Fe substrate, the uptake rate constants of all the eukaryotic phytoplankton species are tightly correlated and proportional to their respective surface areas (S.A.). The same is true when FeDFB is the substrate, but the corresponding uptake constants are one thousand times smaller than for Fe′. The uptake rate constants for the other substrates we examined fall mostly between the values for Fe′ and FeDFB for the same S.A. These two model substrates thus empirically define a bioavailability envelope with Fe′ at the upper and FeDFB at the lower limit of iron bioavailability. This envelope provides a convenient framework to compare the relative bioavailabilities of various Fe substrates to eukaryotic phytoplankton and the Fe uptake abilities of different phytoplankton species. Compared with eukaryotic species, cyanobacteria have similar uptake constants for Fe′ but lower ones for FeDFB. The unique relationship between the uptake rate constants and the S.A. of phytoplankton species suggests that the uptake rate constant of Fe-limited phytoplankton has reached a universal upper limit and provides insight into the underlying uptake mechanism.     

Plugging space into predator-prey models: an empirical approach

Extrapolating ecological processes from small-scale experimental systems to scales of natural populations usually entails a considerable increase in spatial heterogeneity, which may affect process rates and, ultimately, population dynamics. We demonstrate how information on the heterogeneity of natural populations can be taken into account when scaling up laboratory-derived process functions, using the technique of moment approximation. We apply moment approximation to a benthic crustacean predator-prey system, where a laboratory-derived functional response is made spatial by including correction terms for the variance in prey density and the covariance between prey and predator densities observed in the field. We also show how moment approximation may be used to incorporate spatial information into a dynamic model of the system. While the nonspatial model predicts stable dynamics, its spatial equivalent also produces bounded fluctuations, in agreement with observed dynamics. A detailed analysis shows that predator-prey covariance, but not prey variance, destabilizes the dynamics. We conclude that second-order moment approximation may provide a useful technique for including spatial information in population models. The main advantage of the method is its conceptual value: by providing explicit estimates of variance and covariance effects, it offers the possibility of understanding how heterogeneity affects ecological processes.     

Character analysis: an empirical approach applied to advanced snakes

Fifty characters of extant advanced snakes were selected for phyletic analysis, with the primary aim of determining evolutionary paths of the venomous taxa. The characters chosen showed roughly equivalent variation. States of characters were distinguished with reference to range of variation at species and generic levels. The heterogeneous, widespread and abundant family Colubridae was designated as representing the ancestral group. Direction of change in states was then determined by reference to colubrid conditions. Criteria used for judgement of direction were (1) uniqueness, (2) relative abundance, (3) correlation of derived states, (4) morphological specialization, (5) ecological specialization, (6) geographic restriction, (7) closely related taxa, and (8) correlation of applicable criteria. Two other criteria, (9) genetic structure and (10) fossil record, were not applicable.
Characters used as examples of the approach are number of palatine teeth and the pattern of the head shields. In the latter, the derivative states are correlated with particular modes of life (aquatic, fossorial and terrestrial). The familial level taxa show rather different frequency distributions in respect to the four states of this character, with one derived state unique to the viperids.
The second character, number of palatine teeth, was divided into classes by using a span covering most intraspecific variation. The resulting classes were lumped into four states emphasizing the classes of low numbers of teeth. The extreme derived states are correlated in the colubrids with distinctive modes of life (burrowing and digging) and with functional morphological specializations. The distribution of the states shows a trend toward low numbers of teeth in all the venomous families.     

Multilocus analysis of variation using a large empirical data set: phenylpropanoid pathway genes in Arabidopsis thaliana

Detecting the signature of adaptation on nucleotide variation is often difficult in species that like Arabidopsis thaliana might have a complex demographic history. Recent re-sequencing surveys in this species provided genome-wide information that would mainly reflect its demographic history. We have used a large empirical data set (LED) as well as multilocus coalescent simulations to analyse sequence variation at loci involved in the phenylpropanoid pathway of this species. We surveyed and examined DNA sequence variation at nine of these loci (about 19.7 kb) in 23 accessions of A. thaliana and one accession of its closely related species Arabidopsis lyrata . Nucleotide variation was lower at nonsynonymous sites than at silent sites in all loci, indicating generalized functional constraint at the protein level. No association between variation and position in the metabolic pathway was detected. When the data were contrasted against the standard neutral model, significant deviations for silent variation were detected with Tajima's D , Fu's F_S and Fay and Wu's H multilocus test statistics. These deviations were in the same direction than in previous large-scale multilocus analyses, suggesting a genome-wide effect. When the nine-locus data set was contrasted against the large empirical data set, the level (Watterson's θ) and pattern of variation (Tajima's D ) detected in these loci did not deviate either at the single-locus or multilocus level from the corresponding empirical distributions. These results would support an important role of the demographic history of A. thaliana in shaping nucleotide variation at the nine studied phenylpropanoid loci. The potential and limitations of the empirical distribution approach are discussed.     

Core set approach to reduce uncertainty of gene trees

Background  

A genealogy based on gene sequences within a species plays an essential role in the estimation of the character, structure, and evolutionary history of that species. Because intraspecific sequences are more closely related than interspecific ones, detailed information on the evolutionary process may be available by determining all the node sequences of trees and provide insight into functional constraints and adaptations. However, strong evolutionary correlations on a few lineages make this determination difficult as a whole, and the maximum parsimony (MP) method frequently allows a number of topologies with a same total branching length.     

Brassinosteroid signal transduction: clarifying the pathway from ligand perception to gene expression

Recent genetic screens for novel components of brassinosteroid signaling have revealed proteins with cell surface, cytoplasmic, and nuclear localization that function as either positive activators or negative regulators of the brassinosteroid response. Initial microarray experiments have expanded the number of known brassinosteroid-regulated genes, providing a useful resource for better understanding terminal events in signal transduction.     

An empirical Bayes approach to inferring large-scale gene association networks

MOTIVATION: Genetic networks are often described statistically using graphical models (e.g. Bayesian networks). However, inferring the network structure offers a serious challenge in microarray analysis where the sample size is small compared to the number of considered genes. This renders many standard algorithms for graphical models inapplicable, and inferring genetic networks an 'ill-posed' inverse problem. METHODS: We introduce a novel framework for small-sample inference of graphical models from gene expression data. Specifically, we focus on the so-called graphical Gaussian models (GGMs) that are now frequently used to describe gene association networks and to detect conditionally dependent genes. Our new approach is based on (1) improved (regularized) small-sample point estimates of partial correlation, (2) an exact test of edge inclusion with adaptive estimation of the degree of freedom and (3) a heuristic network search based on false discovery rate multiple testing. Steps (2) and (3) correspond to an empirical Bayes estimate of the network topology. RESULTS: Using computer simulations, we investigate the sensitivity (power) and specificity (true negative rate) of the proposed framework to estimate GGMs from microarray data. This shows that it is possible to recover the true network topology with high accuracy even for small-sample datasets. Subsequently, we analyze gene expression data from a breast cancer tumor study and illustrate our approach by inferring a corresponding large-scale gene association network for 3883 genes.     

Fisheries for small pelagic species: an empirical approach to management targets

Summary Long-term management targets based on MSY, F_max or F_0.1 are inappropriate for small pelagic fish because of the possibility of stock collapse owing to a stock-recruit relationship at low biomasses. Better reference points such as F_med and F_high that take account of stock and recruit data cannot be used in developing fishery situations because they are too demanding of data. A simple model was fitted to medium-term (about 10 year) periods in exploited small pelagic fisheries, relating change in stock biomass to exploitation rate. Data from 28 stocks and 11 species were used. The fitted model was used to estimate likelihood of stock decrease at different exploitation rates. The pelagic stocks included in the model appeared to be in equilibrium for an exploitation rate F/Z=0.4, which may be used as a guideline for the appropriate exploitation of pelagic stocks.     

EmPLiCS: an empirical approach for structure-based design of natural peptide drugs

The computer implementation of a peptide drug-design strategy has been developed. The system is named EmPLiCS (Empirical Peptide Ligand Construction System) according to the strategy of the system, which searches for peptide-ligand structures by referring to empirical rules that are derived from known protein 3D structures. The system was tested on several known peptide-protein complexes. The results demonstrated the ability of this system to detect key residues of peptides that are crucial for interaction with their specific proteins. The system also showed the ability to detect the main chain trace of these peptides. Some of the main chain atoms were detected even though the complete primary structures were not reproduced, suggesting that main chain structure is important in peptide-protein recognition. The results of the present study demonstrated that the empirical rules-based system can generate significant information for use in the design of natural peptide drugs.     

GAzer: gene set analyzer

Gene Set Analyzer (GAzer) is a web-based integrated gene set analysis tool covering previously reported parametric and non-parametric models. Based on a simulation test for the reported algorithms, we classified and implemented three main statistical methods consisting of the z-statistic, gene permutation and sample permutation for ten gene set categories including Gene Ontology (GO) for human, mouse, rat and yeast. This tool identifies significantly altered gene sets scored by z-statistics and P-values from the z-test or permutation test and provides q-values and Bonferroni P-values to correct multiple hypothesis testing. GAzer allows users to observe changes in expression of each gene in a gene set or to see the significance of the gene sets containing a gene(s) of interest, thus allowing interactive data analysis both at the gene and gene set level. Moreover, GAzer offers extensive annotation for each gene. AVAILABILITY: The GAzer gene set analyzer is freely available at http://integromics.kobic.re.kr/GAzer/. SUPPLEMENTARY INFORMATION: This can be found on the web page (http://integromics.kobic.re.kr/GAzer/supplement.jsp).     

反效信号传导通路与氧化应激诱导的基因表达

细胞存活与凋亡受生长因子活化的ＥＲＫ与应激活化的ＪＮＫ－ｐ３８信号传导通路二者的动态平衡所控制,ＪＮＫ－ｐ３８通路的持续活化及ＥＲＫ通路的共济失活是细胞凋亡的关键所在。Ｈ２Ｏ２参与多种细胞类型的信号传导,并可诱导早期应答基因的表达。转录因子的激活与抗氧化酶合成有一定的因果关系,但中间环节尚待进一步阐明。