Assessing telomeric DNA content in pediatric cancers using whole-genome sequencing data

Background

Telomeres are the protective arrays of tandem TTAGGG sequence and associated proteins at the termini of chromosomes. Telomeres shorten at each cell division due to the end-replication problem and are maintained above a critical threshold in malignant cancer cells to prevent cellular senescence or apoptosis. With the recent advances in massive parallel sequencing, assessing telomere content in the context of other cancer genomic aberrations becomes an attractive possibility. We present the first comprehensive analysis of telomeric DNA content change in tumors using whole-genome sequencing data from 235 pediatric cancers.

Results

To measure telomeric DNA content, we counted telomeric reads containing TTAGGGx4 or CCCTAAx4 and normalized to the average genomic coverage. Changes in telomeric DNA content in tumor genomes were clustered using a Bayesian Information Criterion to determine loss, no change, or gain. Using this approach, we found that the pattern of telomeric DNA alteration varies dramatically across the landscape of pediatric malignancies: telomere gain was found in 32% of solid tumors, 4% of brain tumors and 0% of hematopoietic malignancies. The results were validated by three independent experimental approaches and reveal significant association of telomere gain with the frequency of somatic sequence mutations and structural variations.

Conclusions

Telomere DNA content measurement using whole-genome sequencing data is a reliable approach that can generate useful insights into the landscape of the cancer genome. Measuring the change in telomeric DNA during malignant progression is likely to be a useful metric when considering telomeres in the context of the whole genome.     

Clinical features and predictors for disease natural progression in adults with Pompe disease: a nationwide prospective observational study

Background

Due partly to physicians’ unawareness, many adults with Pompe disease are diagnosed with great delay. Besides, it is not well known which factors influence the rate of disease progression, and thus disease outcome. We delineated the specific clinical features of Pompe disease in adults, and mapped out the distribution and severity of muscle weakness, and the sequence of involvement of the individual muscle groups. Furthermore, we defined the natural disease course and identified prognostic factors for disease progression.

Methods

We conducted a single-center, prospective, observational study. Muscle strength (manual muscle testing, and hand-held dynamometry), muscle function (quick motor function test), and pulmonary function (forced vital capacity in sitting and supine positions) were assessed every 3–6 months and analyzed using repeated-measures ANOVA.

Results

Between October 2004 and August 2009, 94 patients aged between 25 and 75 years were included in the study. Although skeletal muscle weakness was typically distributed in a limb-girdle pattern, many patients had unfamiliar features such as ptosis (23%), bulbar weakness (28%), and scapular winging (33%). During follow-up (average 1.6 years, range 0.5-4.2 years), skeletal muscle strength deteriorated significantly (mean declines of ?1.3% point/year for manual muscle testing and of ?2.6% points/year for hand-held dynamometry; both p<0.001). Longer disease duration (>15 years) and pulmonary involvement (forced vital capacity in sitting position <80%) at study entry predicted faster decline. On average, forced vital capacity in supine position deteriorated by 1.3% points per year (p=0.02). Decline in pulmonary function was consistent across subgroups. Ten percent of patients declined unexpectedly fast.

Conclusions

Recognizing patterns of common and less familiar characteristics in adults with Pompe disease facilitates timely diagnosis. Longer disease duration and reduced pulmonary function stand out as predictors of rapid disease progression, and aid in deciding whether to initiate enzyme replacement therapy, or when.

     

Coarse-grained molecular simulation of diffusion and reaction kinetics in a crowded virtual cytoplasm

We present a general-purpose model for biomolecular simulations at the molecular level that incorporates stochasticity, spatial dependence, and volume exclusion, using diffusing and reacting particles with physical dimensions. To validate the model, we first established the formal relationship between the microscopic model parameters (timestep, move length, and reaction probabilities) and the macroscopic coefficients for diffusion and reaction rate. We then compared simulation results with Smoluchowski theory for diffusion-limited irreversible reactions and the best available approximation for diffusion-influenced reversible reactions. To simulate the volumetric effects of a crowded intracellular environment, we created a virtual cytoplasm composed of a heterogeneous population of particles diffusing at rates appropriate to their size. The particle-size distribution was estimated from the relative abundance, mass, and stoichiometries of protein complexes using an experimentally derived proteome catalog from Escherichia coli K12. Simulated diffusion constants exhibited anomalous behavior as a function of time and crowding. Although significant, the volumetric impact of crowding on diffusion cannot fully account for retarded protein mobility in vivo, suggesting that other biophysical factors are at play. The simulated effect of crowding on barnase-barstar dimerization, an experimentally characterized example of a bimolecular association reaction, reveals a biphasic time course, indicating that crowding exerts different effects over different timescales. These observations illustrate that quantitative realism in biosimulation will depend to some extent on mesoscale phenomena that are not currently well understood.     

The effects of fire, local environment and time on ant assemblages in fens and forests

We investigated the effects of the abiotic environment, plant community composition and disturbance by fire on ant assemblages in two distinct habitat types in the Siskiyou Mountains in northern California and southern Oregon, USA. Sampling over 2 years in burned and unburned Darlingtonia fens and their adjacent upland forests, we found that the effects of disturbance by fire depended on habitat type. In forests, fire intensity predicted richness in ant assemblages in both years after the fire, and plant community composition predicted richness 2 years after the fire. No factors were associated with richness in the species‐poor fen ant assemblages. Species‐specific responses to both habitat type and disturbance by fire were idiosyncratic. Assemblage composition depended on habitat type, but not disturbance by fire, and the composition of each assemblage between years was more dissimilar in burned than unburned sites.     

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulæ for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.     

Bayesian inference in ecology

Bayesian inference is an important statistical tool that is increasingly being used by ecologists. In a Bayesian analysis, information available before a study is conducted is summarized in a quantitative model or hypothesis: the prior probability distribution. Bayes’ Theorem uses the prior probability distribution and the likelihood of the data to generate a posterior probability distribution. Posterior probability distributions are an epistemological alternative to P‐values and provide a direct measure of the degree of belief that can be placed on models, hypotheses, or parameter estimates. Moreover, Bayesian information‐theoretic methods provide robust measures of the probability of alternative models, and multiple models can be averaged into a single model that reflects uncertainty in model construction and selection. These methods are demonstrated through a simple worked example. Ecologists are using Bayesian inference in studies that range from predicting single‐species population dynamics to understanding ecosystem processes. Not all ecologists, however, appreciate the philosophical underpinnings of Bayesian inference. In particular, Bayesians and frequentists differ in their definition of probability and in their treatment of model parameters as random variables or estimates of true values. These assumptions must be addressed explicitly before deciding whether or not to use Bayesian methods to analyse ecological data.     

Diversity of rotifers from northeastern U.S.A. bogs with new species records for North America and New England

In order to assess the effects of pollution on recruitment of brown trout (Salmo trutta f. fario L.) exposure experiments with brown trout early life stages were performed in two differently contaminated small streams near Stuttgart, southwest Germany, and in a control situation in the laboratory. Pollution in the more polluted stream is mainly due to effluents of municipal sewage treatment plants and to the influx of surface waters from areas of intense agriculture activity. Additionally, the water carries high particle loads, especially after rainfall events. Water quality of the less polluted stream is occasionally influenced by agriculture activity in the vicinity. For the exposure of trout early life stages incubators were used, which allowed frequent examinations without serious disturbance of the exposed organisms and thus the development could be monitored over time. Compared to the less polluted stream and the control, in the more polluted stream high mortality rates, the lowest hatching success, and lowest values for growth occurred. In the less polluted stream, mortality rates were comparably low in prehatching stages, but high in hatchlings and juveniles due to heavy infestations with protozoic ectoparasites Chilodonella cyprini (Moroff, 1902) and Ichthyobodo necator (Henneguy, 1883). However, pollution-related effects were not detected in this stream. Differences in developmental rates between the different treatments were correlated with different water temperatures in the two streams and the control. For the more polluted stream, previous studies have indicated embryotoxic potentials mediated by pollutants. The present study indicates that in this steam, additionally, fine solids which infiltrate stream gravels may seriously affect development of brown trout early life stages.     

Assembly rules for New England ant assemblages

Community assembly rules specify patterns of species co-occurrence and morphology dictated by interspecific competition. We collected data on the occurrence of ground-foraging ant species in 22 ombrotrophic bogs and adjacent forest plots of New England to test two general assembly rules: reduced co-occurrence of species among communities, and even spacing of body sizes of species within communities. We used null models to generate random communities unstructured by competition and evaluated patterns at regional and local spatial scales. At the regional scale, species co-occurrence in forests, but not bogs, was less than expected by chance, whereas, at the local scale, co-occurrence in both habitats was not different from random. At the regional scale, spacing of body size distributions was random (in bogs) or aggregated (in forests). At the local scale, body size patterns were weakly segregated in bogs, but random or weakly aggregated in forests. In bogs, size ratio constancy was accompanied by greater generic diversity than expected. Although assembly rules were originally developed for vertebrate communities, they successfully explained some patterns in New England ant assemblages. However, the patterns were contingent on spatial scale, and were distinctly different for bog and forest communities, despite their close proximity and the presence of many shared species in both assemblages. The harsh physical conditions of bogs may act as a habitat filter that alters community assembly rules.