ALBERT

Description: RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA–protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html .

Description: This is the second of three papers investigating properties of titanohematite-bearing quartzo-feldspathic rocks that create a significant remanent magnetic anomaly in the Modum District, South Norway. The first paper provided initial magnetic results, mineralogical characterization and evidence for the presence of lamellar magnetism. In this paper, knowledge of lamellar magnetic properties is explored through experiments where ilmenite lamellae were magnetized below 57 K, and interact magnetically along interfaces with the titanohematite host. Samples with known NRM directions were placed in specific orientations in an MPMS then cooled in zero field to 5 K, where hysteresis loops were measured in fields up to 5 Tesla. This assured that results were ultimately related to the natural lamellar magnetism produced during cooling ~1 billion years ago. In a second set of experiments the same oriented samples, were subjected to a +5 Tesla (T) field then field cooled to 5 K before hysteresis experiments. The first experiments consistently produced asymmetric shifted hysteresis loops with two loop separations, one in a positive field and one in a negative field. Without exception, when the NRM was oriented toward the negative field end of the MPMS, the bimodal loop showed a dominant loop separation in a positive field. By contrast, when the NRM was oriented toward the positive field end of the MPMS, the bimodal loop showed a dominant loop separation in a negative field. Both observations are consistent with antiferromagnetic coupling between the hard magnetization of ilmenite and the more easily shifted lamellar magnetism of the hematite. The bimodal nature of the loops indicates that the NRMs are vector sums of natural lamellar moments, which are oriented both positively and negatively, and that these opposite moments control the orientations of ilmenite magnetizations when cooling through 57 K. Here, extreme exchange biases up to 1.68 T were measured. The second set of experiments produced asymmetric shifted hysteresis loops with one opening always in the negative field. These observations indicate that the +5 T field applied at room temperature rotated the hematite lamellar magnetism in a positive direction, so that upon cooling all the ilmenite lamellae acquired negative magnetic moments, thus causing unimodal negatively shifted loops. Here, the largest exchange bias among the unimodal loops was only 0.7 T. These results will be used in paper III to build a better understanding of lamellar magnetism at the atomic layer scale.

Description: A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.

Description: Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm . Contact: peddada@niehs.nih.gov

Description: The temperature dependence of magnetic susceptibility ( –T curves) and magnetization ( M–T curves) has been used as a routine rock magnetic tool to characterize the magnetic mineralogy and magnetic granulometry of Chinese loess/palaeosols. However, palaeoclimatic interpretation of these thermomagnetic analyses remains controversial. In the present study, total organic carbon (TOC), thermomagnetic and low-temperature magnetic experiments on Mid-Late Pleistocene loess/palaeosols in Central Asia and the Chinese Loess Plateau (CLP) have been conducted. We found that the M ( T ) cooling curves at room temperature were mostly lower than the corresponding heating curves, whereas for the ( T ) analyses the cooling curves at room temperature were always much higher than the heating curves. Low-temperature magnetic measurements demonstrated that a large amount of superparamagnetic ferrimagnetic particles were produced during the thermal treatment and resulted in the aforementioned differences. This finding further indicated that the use of the M–T curves to estimate the relative content of maghemite in the loess/palaeosols from the CLP was problematic. In addition, a positive correlation exists between the TOC and the frequency-dependent susceptibility ( FD ) in the CLP, suggesting that stronger pedogenesis would result in the simultaneous increase in the content of both maghemite and organic matter. Consequently, the parameters 1 (representing the relative content of pedogenic maghemite), 2 ([ ph – ] + 1 ) and ph (related to the organic matter concentration), which can be calculated from the –T analyses, can potentially be used as new indicators of pedogenesis and palaeoclimate in Central Asia and the CLP.

Description: Previous magnetotelluric (MT) studies of the high-temperature Coso geothermal system in California identified a subvertical feature of low resistivity (2–5 Ohm m) and appreciable lateral extent (〉1 km) in the producing zone of the East Flank field. However, these models could not reproduce gross 3-D effects in the recorded data. We perform 3-D full-tensor inversion and retrieve a resistivity model that out-performs previous 2-D and 3-D off-diagonal models in terms of its fit to the complete 3-D MT data set as well as the degree of modelling bias. Inclusion of secondary Z xx and Z yy data components leads to a robust east-dip (60) to the previously identified conductive East Flank reservoir feature, which correlates strongly with recently mapped surface faults, downhole well temperatures, 3-D seismic reflection data, and local microseismicity. We perform synthetic forward modelling to test the best-fit dip of this conductor using the response at a nearby MT station. We interpret the dipping conductor as a fractured and fluidized compartment, which is structurally controlled by an unmapped blind East Flank fault zone.

Description: Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.

Description: Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish ( Danio rerio ), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet ( www.inetbio.org/danionet ), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.

Description: The magnetic susceptibility measured in alternating field can in general be resolved into a component that is in-phase with the applied field and a component that is out-of-phase. While in non-conductive diamagnetic, paramagnetic and many ferromagnetic materials the phase is effectively zero, in some ferromagnetic minerals, such as pyrrhotite, hematite, titanomagnetite or small magnetically viscous grains of magnetite, it is clearly non-zero. The anisotropy of out-of-phase susceptibility (opAMS) can then be used as a tool for the direct determination of the magnetic subfabrics of the minerals with non-zero phase. The error in determination of out-of-phase susceptibility non-linearly increases with decreasing phase angle. This may result in imprecise determination of the opAMS in specimens with very low phase angle. The degree of opAMS is higher than that of ipAMS, which may in contrast result in slightly increasing precision n the opAMS determination. It is highly recommended to inspect the results of the statistical tests of each specimen and to exclude the specimens whose opAMS is determined with insufficient precision from further processing. In rocks, whose magnetism is dominated by the mineral with non-zero out-of-phase susceptibility, the principal directions of the opAMS and ipAMS are virtually coaxial, while the degree of opAMS is higher than that of ipAMS. In some specific cases, the opAMS provides us with similar data to those provided by anisotropies of low-field dependent susceptibility and frequency-dependent susceptibility. The advantage of the opAMS compared to the other two anisotropies is its simultaneous measurement with the ipAMS during one measuring process, while the other two anisotropies require the AMS measurements in several fields or at least at two operating frequencies.

Description: The spectral complex conductivity of a water-bearing sand during interaction with carbon dioxide (CO 2 ) is influenced by multiple, simultaneous processes. These processes include partial saturation due to the replacement of conductive pore water with CO 2 and chemical interaction of the reactive CO 2 with the bulk fluid and the grain-water interface. We present a laboratory study on the spectral induced polarization of water-bearing sands during exposure to and flow-through by CO 2 . Conductivity spectra were measured successfully at pressures up to 30 MPa and 80 °C during active flow and at steady-state conditions concentrating on the frequency range between 0.0014 and 100 Hz. The frequency range between 0.1 and 100 Hz turned out to be most indicative for potential monitoring applications. The presented data show that the impact of CO 2 on the electrolytic conductivity may be covered by a model for pore-water conductivity, which depends on salinity, pressure and temperature and has been derived from earlier investigations of the pore-water phase. The new data covering the three-phase system CO 2 -brine-sand further show that chemical interaction causes a reduction of surface conductivity by almost 20 per cent, which could be related to the low pH-value in the acidic environment due to CO 2 dissolution and the dissociation of carbonic acid. The quantification of the total CO 2 effect may be used as a correction during monitoring of a sequestration in terms of saturation. We show that this leads to a correct reconstruction of fluid saturation from electrical measurements. In addition, an indicator for changes of the inner surface area, which is related to mineral dissolution or precipitation processes, can be computed from the imaginary part of conductivity. The low frequency range between 0.0014 and 0.1 Hz shows additional characteristics, which deviate from the behaviour at higher frequencies. A Debye decomposition approach is applied to isolate the feature dominating the data at low frequencies. We conclude from our study that electrical conductivity is not only a highly sensitive indicator for CO 2 saturation in pore space. When it is measured in its full spectral and complex form it contains additional information on the chemical state of the system, which holds the potential of getting access to both saturation and interface properties with one monitoring method.