ALBERT

Description: Motivation: RNA-seq technology has been widely adopted as an attractive alternative to microarray-based methods to study global gene expression. However, robust statistical tools to analyze these complex datasets are still lacking. By grouping genes with similar expression profiles across treatments, cluster analysis provides insight into gene functions and networks, and hence is an important technique for RNA-seq data analysis. Results: In this manuscript, we derive clustering algorithms based on appropriate probability models for RNA-seq data. An expectation-maximization algorithm and another two stochastic versions of expectation-maximization algorithms are described. In addition, a strategy for initialization based on likelihood is proposed to improve the clustering algorithms. Moreover, we present a model-based hybrid-hierarchical clustering method to generate a tree structure that allows visualization of relationships among clusters as well as flexibility of choosing the number of clusters. Results from both simulation studies and analysis of a maize RNA-seq dataset show that our proposed methods provide better clustering results than alternative methods such as the K-means algorithm and hierarchical clustering methods that are not based on probability models. Availability and implementation: An R package, MBCluster.Seq, has been developed to implement our proposed algorithms. This R package provides fast computation and is publicly available at http://www.r-project.org . Contact: sy@swufe.edu.cn ; pliu@iastate.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: Wind is an important regulator of coastal erosion and accretion processes that have significant ecological and engineering implications. Nevertheless, previous studies have mainly focused on storm−generated changes in the bed level. This paper aims to improve the understanding of wind−induced erosion–accretion cycles on intertidal flats under normal (non−stormy) weather conditions using data that relates to the wave climate, near−bed 3D flow velocity, suspended sediment concentration, and bed−level changes on a mudflat at the Yangtze Delta front. The following parameters were calculated at 10−minute intervals over 10 days: the wind wave orbital velocity (Û δ ), bed shear stress from combined current–wave action, erosion flux, deposition flux, and predicted bed−level change. The time series of measured and predicted bed−level changes both show tidal cycles and a 10−day cycle. We attribute the tidal cycles of bed−level changes to tidal dynamics, but we attribute the 10−day cycle of bed−level changes to the interaction between wind speed/direction and neap−spring cyclicity. We conclude that winds can significantly affect bed−level changes in mudflats even during non−stormy weather and under macro−mesotidal conditions and that the bed−level changes can be predicted well using current–wave–sediment combined models. This article is protected by copyright. All rights reserved.

Description: Using data taken as part of the Bluedisk project, we study the connection between neutral hydrogen (H i ) in the environment of spiral galaxies and that in the galaxies themselves. We measure the total H i mass present in the environment in a statistical way by studying the distribution of noise peaks in the H i data cubes obtained for 40 galaxies observed with Westerbork Synthesis Radio Telescope. We find that galaxies whose H i mass fraction is high relative to standard scaling relations have an excess H i mass in the surrounding environment as well. Gas in the environment consists of gas clumps which are individually below the detection limit of our H i data. These clumps may be hosted by small satellite galaxies and/or be the high-density peaks of a more diffuse gas distribution in the intergalactic medium. We interpret this result as an indication for a picture in which the ${\rm H}\,{\small {I}}$ -rich central galaxies accrete gas from an extended gas reservoir present in their environment.

Description: We report new imaging polarimetry observations of the Galactic compact H ii region K3-50 using CanariCam at the Gran Telescopio Canarias. We use a standard polarimetric analysis technique, first outlined by Aitken, to decompose the observed polarization images centred at 8.7, 10.3, and 12.5 μm into the emissive and absorptive components from silicate grains that are aligned with the local magnetic field. These components reveal the spatially resolved magnetic field structures across the mid-infrared emission area of K3-50. We examine these structures and show that they are consistent with previously observed features and physical models of K3-50, such as the molecular torus and the ionized outflow. We propose a 3D geometry for all the structures seen at different wavelengths. We also compute relevant physical quantities in order to estimate the associated magnetic field strengths that would be implied under various physical assumptions. We compare these results with magnetohydrodynamic simulations of protostar formation that predict the magnetic field strength and configuration. We find that the magnetic field may be dynamically important in the innermost 0.2 pc of the molecular torus, but that the torus is more likely to be rotationally supported against gravity outside this radius. Similarly, magnetic fields are unlikely to dominate the global physics of the ionized outflow, but they may be important in helping confine the flow near the cavity wall in some locations. Ours is the first application of the Aitken technique to spatially resolved magnetic field structures in multiple layers along the line of sight, effectively a method of ‘polarization tomography’.

Description: Multiple sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). It is characterized by the infiltration of autoreactive immune cells into the CNS, which target the myelin sheath, leading to the loss of neuronal function. Although it is accepted that MS is a multifactorial disorder with both genetic and environmental factors influencing its development and course, the molecular pathogenesis of MS has not yet been fully elucidated. Here, we studied the longitudinal gene expression profiles of whole-blood RNA from a cohort of 195 MS patients and 66 healthy controls. We analyzed these transcriptomes at both the individual transcript and the biological pathway level. We found 62 transcripts to be significantly up-regulated in MS patients; the expression of 11 of these genes was counter-regulated by interferon treatment, suggesting partial restoration of a ‘healthy’ gene expression profile. Global pathway analyses linked the proteasome and Wnt signaling to MS disease processes. Since genotypes from a subset of individuals were available, we were able to identify expression quantitative trait loci (eQTL), a number of which involved two genes of the MS gene signature. However, all these eQTL were also present in healthy controls. This study highlights the challenge posed by analyzing transcripts from whole blood and how these can be mitigated by using large, well-characterized cohorts of patients with longitudinal follow-up and multi-modality measurements.

Description: Thousands of novel transcripts have been identified using deep transcriptome sequencing. This discovery of large and ‘hidden’ transcriptome rejuvenates the demand for methods that can rapidly distinguish between coding and noncoding RNA. Here, we present a novel alignment-free method, Coding Potential Assessment Tool (CPAT), which rapidly recognizes coding and noncoding transcripts from a large pool of candidates. To this end, CPAT uses a logistic regression model built with four sequence features: open reading frame size, open reading frame coverage, Fickett TESTCODE statistic and hexamer usage bias. CPAT software outperformed (sensitivity: 0.96, specificity: 0.97) other state-of-the-art alignment-based software such as Coding-Potential Calculator (sensitivity: 0.99, specificity: 0.74) and Phylo Codon Substitution Frequencies (sensitivity: 0.90, specificity: 0.63). In addition to high accuracy, CPAT is approximately four orders of magnitude faster than Coding-Potential Calculator and Phylo Codon Substitution Frequencies, enabling its users to process thousands of transcripts within seconds. The software accepts input sequences in either FASTA- or BED-formatted data files. We also developed a web interface for CPAT that allows users to submit sequences and receive the prediction results almost instantly.

Description: Field studies suggested that the biogeochemical settings and community structures are substantial different between the central Northern South China Sea (NSCS) and the upstream Kuroshio Current (KC). In particular, the water column of KC is characterized by substantially lower nutrients and productivity but higher Trichodesmium abundance and nitrogen fixation compared to the NSCS. The mechanism driving the difference of the two marine ecosystems, however, remains inadequately understood. Here, a one-dimensional biogeochemical model was developed to simulate the long-term variability of lower-trophic planktonic ecosystem for two pelagic stations in the NSCS and the KC near the Luzon Strait. The physical model included the vertical mixing driven by air-sea interaction and the Ekman pumping induced by wind stress curl. The biological model was constructed by modifying a nitrogen-based NPZD model with the incorporation of phosphorus cycle and diazotroph nitrogen fixation. After validation by several field datasets, the model was used to study the impact of long-term physical forcing on ecosystem variability in the two distinct stations. Our results suggested that nutrient transport above nitracline during summer was largely controlled by vertical turbulent mixing, while Ekman pumping was important for nutrient transport below the nitracline. Our results also indicated that diazotroph community structure and N 2 fixation in the NSCS and the KC could be strongly influenced by physical processes through the impacts on vertical nutrient fluxes. The disadvantage of diazotroph in the NSCS in compared to the KC during the summer could be attributed to its high nitrate fluxes from subsurface leading to outcompete of diazotrophs by faster growing non-diazotroph phytoplankton. This article is protected by copyright. All rights reserved.

Description: Dilated cardiomyopathy (DCM) is a leading cause of heart failure. In families with autosomal-dominant DCM, heterozygous missense mutations were identified in RNA-binding motif protein 20 ( RBM20 ), a spliceosome protein induced during early cardiogenesis. Dermal fibroblasts from two unrelated patients harboring an RBM20 R636S missense mutation were reprogrammed to human induced pluripotent stem cells (hiPSCs) and differentiated to beating cardiomyocytes (CMs). Stage-specific transcriptome profiling identified differentially expressed genes ranging from angiogenesis regulator to embryonic heart transcription factor as initial molecular aberrations. Furthermore, gene expression analysis for RBM20- dependent splice variants affected sarcomeric ( TTN and LDB3 ) and calcium (Ca 2+ ) handling ( CAMK2D and CACNA1C ) genes. Indeed, RBM20 hiPSC-CMs exhibited increased sarcomeric length ( RBM20 : 1.747 ± 0.238 µm versus control: 1.404 ± 0.194 µm; P 〈 0.0001) and decreased sarcomeric width ( RBM20 : 0.791 ± 0.609 µm versus control: 0.943 ± 0.166 µm; P 〈 0.0001). Additionally, CMs showed defective Ca 2+ handling machinery with prolonged Ca 2+ levels in the cytoplasm as measured by greater area under the curve ( RBM20 : 814.718 ± 94.343 AU versus control: 206.941 ± 22.417 AU; P 〈 0.05) and higher Ca 2+ spike amplitude ( RBM20 : 35.281 ± 4.060 AU versus control:18.484 ± 1.518 AU; P 〈 0.05). β-adrenergic stress induced with 10 µ m norepinephrine demonstrated increased susceptibility to sarcomeric disorganization ( RBM20 : 86 ± 10.5% versus control: 40 ± 7%; P 〈 0.001). This study features the first hiPSC model of RBM20 familial DCM. By monitoring human cardiac disease according to stage-specific cardiogenesis, this study demonstrates RBM20 familial DCM is a developmental disorder initiated by molecular defects that pattern maladaptive cellular mechanisms of pathological cardiac remodeling. Indeed, hiPSC-CMs recapitulate RBM20 familial DCM phenotype in a dish and establish a tool to dissect disease-relevant defects in RBM20 splicing as a global regulator of heart function.

Description: This paper is concerned with travelling wave solutions of periodic monostable differential equations on a two-dimensional lattice. The existence, stability and uniqueness of supercritical travelling wave solutions are obtained by comparison principle.

Description: N 6 -methyladenosine (m 6 A) is a prevalent RNA methylation modification involved in the regulation of degradation, subcellular localization, splicing and local conformation changes of RNA transcripts. High-throughput experiments have demonstrated that only a small fraction of the m 6 A consensus motifs in mammalian transcriptomes are modified. Therefore, accurate identification of RNA m 6 A sites becomes emergently important. For the above purpose, here a computational predictor of mammalian m 6 A site named SRAMP is established. To depict the sequence context around m 6 A sites, SRAMP combines three random forest classifiers that exploit the positional nucleotide sequence pattern, the K-nearest neighbor information and the position-independent nucleotide pair spectrum features, respectively. SRAMP uses either genomic sequences or cDNA sequences as its input. With either kind of input sequence, SRAMP achieves competitive performance in both cross-validation tests and rigorous independent benchmarking tests. Analyses of the informative features and overrepresented rules extracted from the random forest classifiers demonstrate that nucleotide usage preferences at the distal positions, in addition to those at the proximal positions, contribute to the classification. As a public prediction server, SRAMP is freely available at http://www.cuilab.cn/sramp/ .