Methanotrophy below pH 1 by a new Verrucomicrobia species

Mud volcanoes, mudpots and fumaroles are remarkable geological features characterized by the emission of gas, water and/or semi-liquid mud matrices with significant methane fluxes to the atmosphere (10(-1) to 10(3) t y(-1)). Environmental conditions in these areas vary from ambient temperature and neutral pH to high temperatures and low pH. Although there are strong indications for biological methane consumption in mud volcanoes, no methanotrophic bacteria are known that would thrive in the hostile conditions of fumaroles (temperatures up to 70 degrees C and pH down to 1.8). The first step in aerobic methane oxidation is performed by a soluble or membrane-bound methane mono-oxygenase. Here we report that pmoA (encoding the beta-subunit of membrane-bound methane mono-oxygenase) clone libraries, made by using DNA extracted from the Solfatara volcano mudpot and surrounding bare soil near the fumaroles, showed clusters of novel and distant pmoA genes. After methanotrophic enrichment at 50 degrees C and pH 2.0 the most distant cluster, sharing less than 50% identity with any other described pmoA gene, was represented in the culture. Finally we isolated an acidiphilic methanotrophic bacterium Acidimethylosilex fumarolicum SolV belonging to the Planctomycetes/Verrucomicrobia/Chlamydiae superphylum, 'outside' the subphyla of the Alpha- and Gammaproteobacteria containing the established methanotrophs. This bacterium grows under oxygen limitation on methane as the sole source of energy, down to pH 0.8--far below the pH optimum of any previously described methanotroph. A. fumarolicum SolV has three different pmoA genes, with two that are very similar to sequences retrieved from the mudpot. Highly homologous environmental 16S rRNA gene sequences from Yellowstone Park show that this new type of methanotrophic bacteria may be a common inhabitant of extreme environments. This is the first time that a representative of the widely distributed Verrucomicrobia phylum, of which most members remain uncultivated, is coupled to a geochemically relevant reaction.     

Variants modulating the expression of a chromosome domain encompassing PLAG1 influence bovine stature

We report mapping of a quantitative trait locus (QTL) with a major effect on bovine stature to a ～780-kb interval using a Hidden Markov Model-based approach that simultaneously exploits linkage and linkage disequilibrium. We re-sequenced the interval in six sires with known QTL genotype and identified 13 clustered candidate quantitative trait nucleotides (QTNs) out of >9,572 discovered variants. We eliminated five candidate QTNs by studying the phenotypic effect of a recombinant haplotype identified in a breed diversity panel. We show that the QTL influences fetal expression of seven of the nine genes mapping to the ～780-kb interval. We further show that two of the eight candidate QTNs, mapping to the PLAG1-CHCHD7 intergenic region, influence bidirectional promoter strength and affect binding of nuclear factors. By performing expression QTL analyses, we identified a splice site variant in CHCHD7 and exploited this naturally occurring null allele to exclude CHCHD7 as single causative gene.     

Stochastic Multivariate Mixture Covariance Model

Stochastic covariance models have been explored in recent research to model the interdependence of assets in financial time series. The approach uses a single stochastic model to capture such interdependence. However, it may be inappropriate to assume a single coherence structure at all time t. In this paper, we propose the use of a mixture of stochastic covariance models to generalize the approach and offer greater flexibility in real data applications. Parameter estimation is performed by Bayesian analysis with Markov chain Monte Carlo sampling schemes. We conduct a simulation study on three different model setups and evaluate the performance of estimation and model selection. We also apply our modeling methods to high‐frequency stock data from Hong Kong. Model selection favors a mixture rather than non‐mixture model. In a real data study, we demonstrate that the mixture model is able to identify structural changes in market risk, as evidenced by a drastic change in mixture proportions over time. Copyright © 2016 John Wiley & Sons, Ltd.     

Evidence for complete denitrification in a benthic foraminifer

Benthic foraminifera are unicellular eukaryotes found abundantly in many types of marine sediments. Many species survive and possibly reproduce in anoxic habitats, but sustainable anaerobic metabolism has not been previously described. Here we demonstrate that the foraminifer Globobulimina pseudospinescens accumulates intracellular nitrate stores and that these can be respired to dinitrogen gas. The amounts of nitrate detected are estimated to be sufficient to support respiration for over a month. In a Swedish fjord sediment where G. pseudospinescens is the dominant foraminifer, the intracellular nitrate pool in this species accounted for 20% of the large, cell-bound, nitrate pool present in an oxygen-free zone. Similarly high nitrate concentrations were also detected in foraminifera Nonionella cf. stella and a Stainforthia species, the two dominant benthic taxa occurring within the oxygen minimum zone of the continental shelf off Chile. Given the high abundance of foraminifera in anoxic marine environments, these new findings suggest that foraminifera may play an important role in global nitrogen cycling and indicate that our understanding of the complexity of the marine nitrogen cycle is far from complete.     

A novel forecasting model for the Baltic dry index utilizing optimal squeezing

Marine transport has grown rapidly as the result of globalization and sustainable world growth rates. Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian compressed regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the BDI with considerable success.     

Associationism without associative links: Thomas Brown and the associationist project

There are two roles that association played in 18th–19th century associationism. The first dominates modern understanding of the history of the concept: association is a causal link posited to explain why ideas come in the sequence they do. The second has been ignored: association is merely regularity in the trains of thought, and the target of explanation. The view of association as regularity arose in several forms throughout the tradition, but Thomas Brown (1778–1820) makes the distinction explicit. He argues that there is no associative link, and association is mere sequence. I trace this view of association through the tradition, and consider its implications: Brown's views, in particular, motivate a rethinking of the associationist tradition in psychology. Associationism was a project united by a shared explanandum phenomenon, rather than a theory united by a shared theoretical posit.     

Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells

Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ～100?picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10?megabases. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.     

Deep Geothermal:The‘Moon Landing’ Mission in the Unconventional Energy and Minerals Space

Deep geothermal from the hot crystalline basement has remained an unsolved frontier for the geothermal industry for the past 30 years. This poses the challenge for developing a new un-conventional geom...     

A threshold factor multivariate stochastic volatility model

A new multivariate stochastic volatility model is developed in this paper. The main feature of this model is to allow threshold asymmetry in a factor covariance structure. The new model provides a parsimonious characterization of volatility and correlation asymmetry in response to market news. Statistical inferences are drawn from Markov chain Monte Carlo methods. We introduce news impact analysis to analyze volatility asymmetry with a factor structure. This analysis helps us to study different responses of volatility to historical market information in a multivariate volatility framework. Our model is successful when applied to an extensive empirical study of twenty stocks. Copyright © 2009 John Wiley & Sons, Ltd.