ALBERT

Description: Seismic waves sensitive to the outermost part of the Earth's liquid core seem to be affected by a stably stratified layer at the core–mantle boundary. Such a layer could have an observable signature in both long-term and short-term variations of the magnetic field of the Earth, which are used to probe the flow at the top of the core. Indeed, with the recent SWARM mission, it seems reasonable to be able to identify waves propagating in the core with period of several months, which may play an important role in the large-scale dynamics. In this paper, we characterize the influence of a stratified layer at the top of the core on deep quasi-geostrophic (Rossby) waves. We compute numerically the quasi-geostrophic eigenmodes of a rapidly rotating spherical shell, with a stably stratified layer near the outer boundary. Two simple models of stratification are taken into account, which are scaled with commonly adopted values of the Brunt–Väisälä frequency in the Earth's core. In the absence of magnetic field, we find that both azimuthal wavelength and frequency of the eigenmodes control their penetration into the stratified layer: the higher the phase speed, the higher the permeability of the stratified layer to the wave motion. We also show that the theory developed by Takehiro & Lister for thermal convection extends to the whole family of Rossby waves in the core. Adding a magnetic field, the penetrative behaviour of the quasi-geostrophic modes (the so-called fast branch) is insensitive to the imposed magnetic field and only weakly sensitive to the precise shape of the stratification. Based on these results, the large-scale and high-frequency modes (1–2 month periods) may be detectable in the geomagnetic data measured at the Earth's surface, especially in the equatorial area where the modes can be trapped.

Description: Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data ( 3DBG ), and a 3D genome browser to visualize and explore 3D genome structures ( 3DGB ). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/ .

Description: Identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available at https://code.google.com/p/seqtu/ . We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.

Description: Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.

Description: A 3-D magnetotelluric (MT) inversion code using unstructured tetrahedral elements has been developed in order to correct the topographic effect by directly incorporating it into computational grids. The electromagnetic field and response functions get distorted at the observation sites of MT surveys because of the undulating surface topography, and without correcting this distortion, the subsurface structure can be misinterpreted. Of the two methods proposed to correct the topographic effect, the method incorporating topography explicitly in the inversion is applicable to a wider range of surveys. For forward problems, it has been shown that the finite element method using unstructured tetrahedral elements is useful for the incorporation of topography. Therefore, this paper shows the applicability of unstructured tetrahedral elements in MT inversion using the newly developed code. The inversion code is capable of using the impedance tensor, the vertical magnetic transfer function (VMTF), and the phase tensor as observational data, and it estimates the subsurface resistivity values and the distortion tensor of each observation site. The forward part of the code was verified using two test models, one incorporating topographic effect and one without, and the verifications showed that the results were almost the same as those of previous works. The developed inversion code was then applied to synthetic data from a MT survey, and was verified as being able to recover the resistivity structure as well as other inversion codes. Finally, to confirm its applicability to the data affected by topography, inversion was performed using the synthetic data of the model that included two overlapping mountains. In each of the cases using the impedance tensor, the VMTF and the phase tensor, by including the topography in the mesh, the subsurface resistivity was determined more proficiently than in the case using the flat-surface mesh. Although the locations of the anomalies were not accurately estimated by the inversion using distorted impedance tensors due to the slightly undervalued gain, these locations were correctly estimated by using undistorted impedance tensors or adding VMTFs in the data. Therefore, it can be concluded that the inversion using the unstructured tetrahedral element effectively prevents the misinterpretation of subsurface resistivity and recovers subsurface resistivity proficiently by representing the topography in the computational mesh.

Description: Separating the contribution of different hematite coercivity grains to the magnetic fabric is a standing problem in rock magnetism because of the common occurrence of thermochemical alterations when measuring the anisotropy of thermal remanence. A technique that eliminates this bias is presented, which is useful when there is a need to separate the fabric of detrital from pigmentary hematite, for example. The method is based on stepwise thermal demagnetization of saturation isothermal remanent magnetizations (IRMs) applied orthogonally on three sister specimens, allowing calculation of the anisotropy tensor from the three components of each demagnetized IRM vector, avoiding the necessity of having to apply IRMs to thermochemically altered specimens. Vector subtraction allows determining the anisotropy tensor for specific unblocking-temperature ranges. The anisotropies of the pigmentary, specular and total hematite of the Mauch Chunk Formation red beds of Pennsylvania have been measured from an oriented block sample and results are compared to previous anisotropy measurements performed using the high-field anisotropy of isothermal remanence technique (hf-AIR), which measures total undifferentiated hematite. Experiments were conducted using non-saturating 1 T and fully saturating 5.5 T fields: both experimental sets seem capable of measuring the orientation of the specularite anisotropy principal axes, but 5.5 T are needed to capture the orientation of the higher coercivity pigmentary grains. The magnitudes of the principal axes, instead, are only faithfully measured using 5.5 T fields and yield somewhat higher anisotropies than those measured by hf-AIR. The fundamental requirement for this technique is homogeneous material among the three sister specimens, which is a significant limitation; homogeneity tests allow assessment of applicability of the method and reliability of the results.

Description: Archaeomagnetic field models cover longer timescales than historical models and may therefore resolve the motion of geomagnetic features on the core–mantle boundary (CMB) in a more meaningful statistical sense. Here we perform a detailed appraisal of archaeomagnetic field models to infer some aspects of the physics of the outer core. We characterize and compare the identification and tracking of reversed flux patches (RFPs) in order to assess the RFPs robustness. We find similar behaviour within a family of models but differences among different families, suggesting that modelling strategy is more influential than data set. Similarities involve recurrent positions of RFPs, but no preferred direction of motion is found. The tracking of normal flux patches shows similar qualitative behaviour confirming that RFPs identification and tracking is not strongly biased by their relative weakness. We also compare the tracking of RFPs with that of the historical field model gufm1 and with seismic anomalies of the lowermost mantle to explore the possibility that RFPs have preferred locations prescribed by lower mantle lateral heterogeneity. The archaeomagnetic field model that most resembles the historical field is interpreted in terms of core dynamics and core–mantle thermal interactions. This model exhibits correlation between RFPs and low seismic shear velocity in co-latitude and a shift in longitude. These results shed light on core processes, in particular we infer toroidal field lines with azimuthal orientation below the CMB and large fluid upwelling structures with a width of about 80° (Africa) and 110° (Pacific) at the top of the core. Finally, similar preferred locations of RFPs in the past 9 and 3 kyr of the same archaeomagnetic field model suggest that a 3 kyr period is sufficiently long to reliably detect mantle control on core dynamics. This allows estimating an upper bound of 220–310 km for the magnetic boundary layer thickness below the CMB.

Description: Post-depositional reductive diagenesis usually results in partial or entire cleansing of the pristine palaeomagnetic signal, therefore, its intensity is important to be assessed for sediments that are in the purpose of retrieving palaeomagnetic information. Grain size, rock magnetic and geochemical studies on the entire core, along with scanning electron microscope observations and X-ray diffraction analyses for representative samples were carried out on a Holocene sediment core retrieved from the deep water part of Huguangyan maar lake (HGY), southeast China. The pristine magnetic mineral assemblage of the studied core is domianted by superparamagnetic (SP) and stable single domain titanomagnetite, and high coercivity minerals are not detectable. Based on down-core variations of the average grain size ( M Z ), total organic carbon (TOC), detrital elements (Al, Ti, Fe and Mn) and the concentration and mineralogy of magnetic minerals, the studied core could be divided into three subsections. The uppermost subsection is the least affected by diagenesis, with detrital titanomagnetite as the dominant magnetic mineral. This is owing to low TOC contents, but high detrital input generated by weak Asian summer monsoon intensity during the late Holocene. The intermediate subsection shows down-core progressively enhanced dissolution of detrital titanomagnetite, and concomitant formation of authigenic pyrite and siderite, which indicates down-core progressively enhanced diagenesis generated by down-core progressive increasing TOC content, but decreasing detrital input as the result of down-core progressively strengthened Asian summer monsoon intensity. The pristine magnetic mineral assemblage has been profoundly modified in the lowermost subsection. At certain positions of the lowermost subsection, detrital titanomagnetite has been even completely dissolved via diagenesis, giving place to authigenic pyrite and siderite. High TOC content, but low detrital input generated from strong Asian summer monsoon intensity during the early Holocene are accountable for intensive diagenesis in the lowermost subsection. Complete erasing of detrital magnetic input signal at certain positions of the lowermost subsection, and considerable formation of authigenic siderite indicate that palaeomagnetic records of the studied core have been significantly compromised. The studied core has relatively higher TOC content, lower detrital matter content, calmer sedimentary environments, and less DO available at its water–sediment interface than the cores retrieved at relatively shallower water depths, which all contribute to its relatively stronger diagenesis. Progressive thickening of the upper two subsections with increasing water depth is owing to progressive increase in sedimentation rate with increasing water depth, which is the key factor in determining the thickness of each diagenetic subsection of cores from HGY. It would be better that lake sediments for palaeomagnetic investigations collected at a water depth shallower than the depth of its thermocline.

Description: Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways.

Description: Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory ‘grammar’ to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ .