Heritable clustering and pathway discovery in breast cancer integrating epigenetic and phenotypic data

Background  

In order to recapitulate tumor progression pathways using epigenetic data, we developed novel clustering and pathway reconstruction algorithms, collectively referred to as heritable clustering. This approach generates a progression model of altered DNA methylation from tumor tissues diagnosed at different developmental stages. The samples act as surrogates for natural progression in breast cancer and allow the algorithm to uncover distinct epigenotypes that describe the molecular events underlying this process. Furthermore, our likelihood-based clustering algorithm has great flexibility, allowing for incomplete epigenotype or clinical phenotype data and also permitting dependencies among variables.     

Local adaptation along smooth ecological gradients causes phylogeographic breaks and phenotypic clustering

Coalescent theory has provided a basis for evolutionary biologists to build sophisticated methods for inferring population history from variation in genetic markers, but these methods leave out a major conceptual cornerstone of modern evolutionary theory: natural selection. I provide the first quantitative analysis of the effects of selection on genealogical patterns in a continuously distributed population in which the selective optimum for a trait linked to the marker varies gradually and continuously across the landscape. Simulations show that relatively weak selection for local adaptation can lead to strong phylogeographic structure, in which highly divergent genealogical groups (i.e., clades) are geographically localized and differentially adapted, and dramatically increased standing variation (e.g., coalescence time) compared to neutral expectations. This pattern becomes more likely with increasing population size and with decreasing dispersal distances, mutation rates, and mutation sizes. Under some conditions, the system alternates between a nearly neutral behavior and a behavior in which highly divergent clades are locally adapted. Natural selection on markers commonly used in phylogeographic studies (such as mitochondrial DNA) presents a major challenge to the inference of biogeographic history but also provides exciting opportunities to study how selection affects both between- and within-species biodiversity.     

Dynamic model-based clustering for time-course gene expression data

Microarray technology has produced a huge body of time-course gene expression data. Such gene expression data has proved useful in genomic disease diagnosis and genomic drug design. The challenge is how to uncover useful information in such data. Cluster analysis has played an important role in analyzing gene expression data. Many distance/correlation- and static model-based clustering techniques have been applied to time-course expression data. However, these techniques are unable to account for the dynamics of such data. It is the dynamics that characterize the data and that should be considered in cluster analysis so as to obtain high quality clustering. This paper proposes a dynamic model-based clustering method for time-course gene expression data. The proposed method regards a time-course gene expression dataset as a set of time series, generated by a number of stochastic processes. Each stochastic process defines a cluster and is described by an autoregressive model. A relocation-iteration algorithm is proposed to identity the model parameters and posterior probabilities are employed to assign each gene to an appropriate cluster. A bootstrapping method and an average adjusted Rand index (AARI) are employed to measure the quality of clustering. Computational experiments are performed on a synthetic and three real time-course gene expression datasets to investigate the proposed method. The results show that our method allows the better quality clustering than other clustering methods (e.g. k-means) for time-course gene expression data, and thus it is a useful and powerful tool for analyzing time-course gene expression data.     

Dynamic clustering of IP3 receptors by IP3

The versatility of Ca2+ as an intracellular messenger stems largely from the impressive, but complex, spatiotemporal organization of the Ca2+ signals. For example, the latter when initiated by IP3 (inositol 1,4,5-trisphosphate) in many cells manifest hierarchical recruitment of elementary Ca2+ release events ('blips' and then 'puffs') en route to global regenerative Ca2+ waves as the cellular IP3 concentration rises. The spacing of IP3Rs (IP3 receptors) and their regulation by Ca2+ are key determinants of these spatially organized Ca2+ signals, but neither is adequately understood. IP3Rs have been proposed to be pre-assembled into clusters, but their composition, geometry and whether clustering affects IP3R behaviour are unknown. Using patch-clamp recording from the outer nuclear envelope of DT40 cells expressing rat IP3R1 or IP3R3, we have recently shown that low concentrations of IP3 cause IP3Rs to aggregate rapidly and reversibly into small clusters of approximately four IP3Rs. At resting cytosolic Ca2+ concentrations, clustered IP3Rs open independently, but with lower open probability, shorter open duration and lesser IP3-sensitivity than lone IP3Rs. This inhibitory influence of clustering on IP3R is reversed when the [Ca2+]i (cytosolic free Ca2+ concentration) increases. The gating of clustered IP3Rs exposed to increased [Ca2+]i is coupled: they are more likely to open and close together, and their simultaneous openings are prolonged. Dynamic clustering of IP3Rs by IP3 thus exposes them to local Ca2+ rises and increases their propensity for a CICR (Ca2+-induced Ca2+ rise), thereby facilitating hierarchical recruitment of the elementary events that underlie all IP3-evoked Ca2+ signals.     

Dynamic phenotypic plasticity for root growth in Polygonum: a comparative study

Species differences in patterns of phenotypic plasticity may be an important aspect of adaptive diversity. Plasticity for functionally important root traits was studied in inbred field lineages of Polygonum persicaria and P. cespitosum (Polygonaceae). Replicate seedlings were grown in plexiglass rhizotrons under a range of constant and temporally variable moisture treatments. Plasticity was determined for final whole-plant biomass, root biomass allocation, and absolute and proportional root length. The dynamic aspect of root plasticity was examined by digitizing weekly tracings of the proportional deployment of each plant's root system to different vertical soil layers. Plants of both species expressed significant functionally adaptive phenotypic plasticity in the relative allocation, length, and vertical deployment of root systems in response to contrasting moisture conditions. Plasticity patterns in these closely related species were in general qualitatively similar, but for most traits differed in the magnitude and/or the timing of the plastic response. Dynamic changes in root deployment were more marked as well as faster in P. persicaria. Species differences in patterns of individual plasticity were generally consistent with the broader ecological distribution of P. persicaria in diverse as well as temporally variable moisture habitats.     

Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

Background  

Commonly employed clustering methods for analysis of gene expression data do not directly incorporate phenotypic data about the samples. Furthermore, clustering of samples with known phenotypes is typically performed in an informal fashion. The inability of clustering algorithms to incorporate biological data in the grouping process can limit proper interpretation of the data and its underlying biology.     

Biological equilibrium in ecosystems 2. Parameters of ecosystems

In this paper the Theory of Biological Equilibrium (TBE), as the theoretical basis of the Canonical Hypothesis, is used to compute a set of theoretical parameters of natural ecosystems. These parameters are the individuals: species (I/S); the commonness: rarity (C/U) ration as well as the expected density (d _e) and total area (TA) of ecosystems. Results of sampling with nested quadrates are checked against theoretical values. Deviations from expected values of 5 to 10% occur in samples with Natural Biological Equilibrium (NBE); in disturbed and transitional sites a compensation mechanism is found which results in simulated NBE.     

Biological equilibrium in ecosystems 3. Classification of ecosystems

The Theory of Biological Equilibrium (TBE) is applied to the classification of ecosystems. It is shown that one of the basic factors, the habitat-type, governs the distribution of species through the subfactors climate and substrate in accordance with the Theory of Tolerance. Groups of species can be distinguished which show a very similar distribution, and combinations of species in these groups form the kengroups of classification units, or associations. Because the habitat-type of associations is often fragmented, the classification procedures can be applied to explaint the natural extinction of species, as well as the probability of species extinction through man's actions upon biocenoses.     

Dynamic regulation of IP3 receptor clustering and activity by IP3

Inositol 1,4,5-trisphosphate receptors (IP₃Rs) are intracellular Ca²⁺ channels. Their regulation by both IP₃ and Ca²⁺ allows interactions between IP₃Rs to generate a hierarchy of intracellular Ca²⁺ release events. These can progress from openings of single IP₃R, through near-synchronous opening of a few IP₃Rs within a cluster to much larger signals that give rise to regenerative Ca²⁺ waves that can invade the entire cell. We have used patch-clamp recording from excised nuclear membranes of DT40 cells expressing only IP₃R3 and shown that low concentrations of IP₃ rapidly and reversibly cause IP₃Rs to assemble into small clusters. In addition to bringing IP₃Rs close enough to allow Ca²⁺ released by one IP₃R to regulate the activity of its neighbors, clustering also retunes the regulation of IP₃Rs by IP₃ and Ca²⁺. At resting cytosolic [Ca²⁺], lone IP₃R are more sensitive to IP₃ and the mean channel open time (~10ms) is twice as long as for clustered IP₃R. When the cytosolic free [Ca²⁺] is increased to 1µM, to mimic the conditions that might prevail when an IP₃R within a cluster opens, clustered IP₃R are no longer inhibited and their gating becomes coupled. IP₃, by dynamically regulating IP₃R clustering, both positions IP₃R for optimal interactions between them and it serves to exaggerate the effects of Ca²⁺ within a cluster. During the course of these studies, we have observed that nuclear IP₃R stably express one of two single channel K ⁺ conductances (γ_K ~120 or 200pS). Here we demonstrate that for both states of the IP₃R, the effects of IP₃ on clustering are indistinguishable. These observations reinforce our conclusion that IP₃ dynamically regulates assembly of IP₃Rs into clusters that underlie the hierarchical recruitment of elementary Ca²⁺ release events.     

Primate visual signals in noisy environments

Most animals and plants need to send signals and rely on some sort of response. For an active receptor of signals, virtually all the signal transmissions that litter the environment, bar those that are functional at any given moment, can be described as 'noise'. I concentrate here on some primate examples where loud calls combine with 'loud' colouring and patterns, to suggest that increasing the intensity of signals can help overcome the problem of 'noise'. I also present evidence that certain ecological conditions favour use of the visual channel. I use some examples, drawn from African guenons, to suggest that visual patterns broadcast on this channel have evolved and have, effectively, been elaborated to conform with certain optical principles. These optical properties minimize ambiguity and enhance species-specific (or at least population-specific) distinctiveness. The abilities of ancestral forest primates to discriminate between functional signals and visual 'noise' may have played an important part in providing the basis for our own hominin ancestors' visual proficiencies.     

Dynamic properties of complex adaptive ecosystems: implications for the sustainability of service provision

Predicting environmental change and its impacts on ecosystem goods and services at local to global scales remains a significant challenge for the international scientific community. This is due largely to the fact that the Earth is made up of open, coupled, complex, interactive and non-linear dynamic systems that are inherently unpredictable. Uncertainties over interactions and feedbacks between natural and human drivers of environmental change (operating at different spatial and temporal scales) can compound intrinsic intractable difficulties faced by plural societies aiming at sustainable management of ecosystems. Social-Ecological Systems (SES) theory addresses these strongly coupled and complex characteristics of social and ecological systems. It can provide a useful framework for articulating contrasting drivers and pressures on ecosystems and associated service provision, spanning different temporalities and provenances. Here, system vulnerabilities (defined as exposure to threats affecting ability of an SES to cope in delivering relevant functions), can arise from both endogenous and exogenous factors across multiple time-scales. Vulnerabilities may also take contrasting forms, ranging from transient shocks or disruptions, through to chronic or enduring pressures. Recognising these diverse conditions, four distinct dynamic properties emerge (resilience, stability, durability and robustness), under which it is possible to maintain system function and, hence, achieve sustainability.     

Cyanobacteria in mangrove ecosystems

Mangroves are subject to the effects of tides and fluctuations in environmental conditions, which may reach extreme conditions. These ecosystems are severely threatened by human activities despite their ecological importance. Although mangroves are characterized by a highly specialized but low plant diversity in comparison to most other tropical ecosystems, they support a diverse microbial community. Adapted microorganisms in soil, water, and on plant surfaces perform fundamental roles in nutrient cycling, especially nitrogen and phosphorus. Cyanobacteria contribute to carbon and nitrogen fixation and their cells act as phosphorus storages in ecosystems with extreme or oligotrophic environmental conditions such as those found in mangroves. As the high plant productivity in mangroves is only possible due to interactions with microorganisms, cyanobacteria may contribute to these ecosystems by providing fixed nitrogen, carbon, and herbivory-defense molecules, xenobiotic biosorption and bioremediation, and secreting plant growth-promoting substances. In addition to water, cyanobacterial colonies have been detected on sediments, rocks, decaying wood, underground and aerial roots, trunks, and leaves. Some mangrove cyanobacteria were also found in association to algae or seagrasses. Few studies on mangrove cyanobacteria are available, but together they have reported a substantial number of species in these ecosystems. However, the cyanobacterial diversity in this biome has been traditionally underestimated. Though mangrove communities generally host cyanobacterial taxa commonly found in marine environments, unique microhabitats found in mangroves potentially harbor several undescribed cyanobacterial taxa. The relevance of cyanobacteria for mangrove conservation is highlighted in their use for the recovery of degraded mangroves as biostimulants or in bioremediation.     

Recovery in complex ecosystems

Current ecosystem theory has a deceptively simple representation of recovery. In actual practice,recovery is affected by the frequency and extent of disturbances and by the spatial heterogeneity of the ecological system. Environmental changes may pass through thresholds causing recovery to a different plant and animal community. The sheer complexity of the system combined with unanticipated synergistic effects can make recovery trajectories difficult or impossible to predict. New theoretical constructs,based on stochastic nonlinear theory, will be needed to guide research and applications. This revised version was published online in July 2006 with corrections to the Cover Date.     

Glyphosate in northern ecosystems

Glyphosate is the main nonselective, systemic herbicide used against a wide range of weeds. Its worldwide use has expanded because of extensive use of certain agricultural practices such as no-till cropping, and widespread application of glyphosate-resistant genetically modified crops. Glyphosate has a reputation of being nontoxic to animals and rapidly inactivated in soils. However, recent evidence has cast doubts on its safety. Glyphosate may be retained and transported in soils, and there may be cascading effects on nontarget organisms. These processes may be especially detrimental in northern ecosystems because they are characterized by long biologically inactive winters and short growing seasons. In this opinion article, we discuss the potential ecological, environmental and agricultural risks of intensive glyphosate use in boreal regions.     

Junk-food in marine ecosystems

The abundance and availability of food are critical determininants of reproductive success and population dynamics of marine top predators. However, recent work has indicated that the quality of the food may also be critically important for some marine predators. The 'junkfood hypothesis' was originally suggested as a potential explanation for a dramatic population decline of Stellers sea lions Eumetopias jubatus in the Gulf of Alaska. According to the hypothesis, a dietary switch to prey of low energy content led to detrimental effects on the population of sea lions. A number of observations indicate that the hypothesis is relevant for several population parameters. Recent work on piscivorous seabirds has provided substantial evidence indicating the relevance of this hypothesis in food webs in e.g. the North Pacific, the North Sea and the Baltic Sea. The emergence of 'junk-food' in these systems may be coupled to large scale changes in climatological and oceanographic forcing, although predation, fishing and competition provide additional plausible hypotheses. It may be possible to predict which kinds of animals will be particularly sensitive to food quality; these seem to be species with limited ability to carry food loads, with energetically-expensive foraging behaviour, and with digestive anatomy evolved to minimize mass at the cost of digestive efficiency. This review suggests that the junk-food hypothesis is a highly relevant factor in relation to sustaining ecosystem resilience, and is an important consideration in ecosystem management. Sustaining healthy populations of marine top-predators requires an understanding of the role of food quality, in addition to food abundance and availability.