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This paper shows high-fidelity fluid–structure interaction (FSI) studies applied to the research wind turbine of the WINSENT (Wind Science and Engineering in Complex Terrain) project. In this project, two research wind turbines are going to be erected in the south of Germany in the WindForS complex-terrain test field. The FSI is obtained by coupling the CFD URANS–DES code FLOWer and the multiphysics FEM solver Kratos Multiphysics, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modeling approaches strongly differ with respect to computational resources, and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single-blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low-velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the damage equivalent loading (DEL) is discussed, showing that flexibility reduces the DEL in the case of turbulent inflow, acting as a damper that breaks larger cycles into smaller ones.

In this work, a modular coupling approach for particle methods with the FEM (finite element method) is presented. The proposed coupled strategy takes advantage from the ability of particle methods of dealing with large displacements and deformations, especially when solving complex fluid–structure and solid–structure interaction problems. The coupling between the FEM and particle methods is done using a co-simulation approach implemented in the open-source Kratos Multiphysics framework. The particle methods considered in this work are the DEM (discrete element method) and the PFEM (particle finite element method). The Lagrangian description of the PFEM is well suited for modeling fluids undergoing large deformations and free-surface motions, and the DEM can be used to simulate rocks, debris and other solid objects. To accelerate the convergence of the coupled strategy, a block Gauss–Seidel algorithm with Aitken relaxation is used. Several numerical examples, with an emphasis on natural hazards, are presented to test and validate the proposed coupled method.

BackgroundPioneering research has shown that high-throughput epigenomics assays such as ChlP-seq and ATAC-seq are applicable to patient-derived breast tumor samples. A host of public data has been accumulated since then, which are potentially of high value for basic research as well as personalized medicine. Such data sets constitute encyclopedias of biological knowledge. However, their impact has so far been limited by access obstacles, especially with regard to extraction and visualization of small portions of data that could potentially answer specific questions arising in a research context.ResultsWe developed the breast cancer epigenomics track hub (BC hub), a resource intended to make it easy for occasional users to find, access and view data of their interest. The BC hub harbors ChIP-seq, ATAC-seq and copy number data from breast tumors, normal breast cells, patient-derived xenografts and breast cancer cell lines in a genome browsable track format. The tracks can be accessed via hyperlinks that automatically configure customized views for different interest groups. Here, we present a detailed description of the resource and informative use cases illustrating its potential in answering specific biological questions.ConclusionsWe show that track hubs constitute a powerful way of bringing epigenomics data to the user who could benefit from them. The examples presented highlight the added-value of joint visualization of breast cancer data from different sources. The proof-of-concept provided here exemplifies and underscores the importance of efforts to make biological data FAIR (findable, accessible, interoperable and reusable), and may serve as an encouragement of similar bottom-up initiatives in other research fields. The BC hub is freely accessible at https://bchub.epfl.ch.

This paper shows high-fidelity Fluid Structure Interaction (FSI) studies applied on the research wind turbine of the WINSENT project. In this project, two research wind turbines are going to be erected in the South of Germany in the WindForS complex terrain test field. The FSI is obtained by coupling the CFD URANS/DES code FLOWer and the multiphysics FEM solver Kratos, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modelling approaches strongly differ with respect to computational resources and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both a flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the Damage Equivalent Loading (DEL) is discussed, showing that flexibility is reducing the DEL in case of turbulent inflow, acting as a damper breaking larger cycles into smaller ones.

Background Positional weight matrix (PWM) is a de facto standard model to describe transcription factor (TF) DNA binding specificities. PWMs inferred from in vivo or in vitro data are stored in many databases and used in a plethora of biological applications. This calls for comprehensive benchmarking of public PWM models with large experimental reference sets. Results Here we report results from all-against-all benchmarking of PWM models for DNA binding sites of human TFs on a large compilation of in vitro (HT-SELEX, PBM) and in vivo (ChIP-seq) binding data. We observe that the best performing PWM for a given TF often belongs to another TF, usually from the same family. Occasionally, binding specificity is correlated with the structural class of the DNA binding domain, indicated by good cross-family performance measures. Benchmarking-based selection of family-representative motifs is more effective than motif clustering-based approaches. Overall, there is good agreement between in vitro and in vivo performance measures. However, for some in vivo experiments, the best performing PWM is assigned to an unrelated TF, indicating a binding mode involving protein-protein cooperativity. Conclusions In an all-against-all setting, we compute more than 18 million performance measure values for different PWM-experiment combinations and offer these results as a public resource to the research community. The benchmarking protocols are provided via a web interface and as docker images. The methods and results from this study may help others make better use of public TF specificity models, as well as public TF binding data sets.

A steady-state fluid–structure interaction analysis on an elasto-flexible membrane blade is presented. The membrane blade geometry is designed based on the NASA-Ames Phase VI model. Form-finding is used to compute the pre-stressed membrane’s initial equilibrium shape directly on the Computer-Aided Design model using isogeometric analysis. To study the effects and potential advantages of such a membrane blade concept, a co-simulation framework is used to couple fluid and structure solvers. The resulting pressure, thrust, and torque coefficient distributions are presented and compared to the reference configuration. The membrane’s deflection increases the blade’s camber, which results in a change in the thrust and torque radial distributions. The larger decrease of the axial momentum at the wake of the flexible configuration indicates that it has a larger capacity to extract energy from the flow than its rigid counterpart.

Contrasting monolithically solved numerical analyses, partitioned coupled simulations confer the substantial advantages of software modularity, employing the best numerical techniques for each domain and readiness to extend the coupling to other physics and emerging numerical techniques. However, an additional interface problem is created and must be solved without significantly deteriorating solution accuracy. This application-oriented study examines non-conforming partitioned dynamic FEM-FEM simulations under approaches of varying complexity illustrating their ranges of applicability as well as key advantages and disadvantages. After presenting the pertinent aspects of popular coupling technologies, two numerical examples of different complexities are considered. Although the efficiently simple Gauss–Seidel approach is suitable for partitioned systems of dissimilar stiffnesses, such as structure and fluid/soil interaction, stability and accuracy deteriorate as domain compliances align rendering it unsuitable for partitioned structural analysis. Contrasting this, the more robust FETI-based method maintains stability over all stiffness ratios and demonstrates excellent agreement with equivalent monolithic structural responses in terms of displacements and stresses.

The Mass Genome Annotation (MGA) repository is a resource designed to store published next generation sequencing data and other genome annotation data (such as gene start sites, SNPs, etc.) in a completely standardised format. Each sample has undergone local processing in order the meet the strict MGA format requirements. The original data source, the reformatting procedure and the biological characteristics of the samples are described in an accompanying documentation file manually edited by data curators. 10 model organisms are currently represented: Homo sapiens, Mus musculus, Danio rerio, Drosophila melanogaster, Apis mellifera, Caenorhabditis elegans, Arabidopsis thaliana, Zea mays, Saccharomyces cerevisiae and Schizosaccharomyces pombe. As of today, the resource contains over 24 000 samples. In conjunction with other tools developed by our group (the ChIP-Seq and SSA servers), it allows users to carry out a great variety of analysis task with MGA samples, such as making aggregation plots and heat maps for selected genomic regions, finding peak regions, generating custom tracks for visualizing genomic features in a UCSC genome browser window, or downloading chromatin data in a table format suitable for local processing with more advanced statistical analysis software such as R. Home page: http://ccg.vital-it.ch/mga/.

The Eukaryotic Promoter Database (EPD), available online at https://epd.epfl.ch, provides accurate transcription start site (TSS) information for promoters of 15 model organisms plus corresponding functional genomics data that can be viewed in a genome browser, queried or analyzed via web interfaces, or exported in standard formats (FASTA, BED, CSV) for subsequent analysis with other tools. Recent work has focused on the improvement of the EPD promoter viewers, which use the UCSC Genome Browser as visualization platform. Thousands of high-resolution tracks for CAGE, ChIP-seq and similar data have been generated and organized into public track hubs. Customized, reproducible promoter views, combining EPD-supplied tracks with native UCSC Genome Browser tracks, can be accessed from the organism summary pages or from individual promoter entries. Moreover, thanks to recent improvements and stabilization of ncRNA gene catalogs, we were able to release promoter collections for certain classes of ncRNAs from human and mouse. Furthermore, we developed automatic computational protocols to assign orphan TSS peaks to downstream genes based on paired-end (RAMPAGE) TSS mapping data, which enabled us to add nearly 9000 new entries to the human promoter collection. Since our last article in this journal, EPD was extended to five more model organisms: rhesus monkey, rat, dog, chicken and Plasmodium falciparum.

Precise nucleosome organization at eukaryotic promoters is thought to be generated by multiple chromatin remodeler (CR) enzymes and to affect transcription initiation. Using an integrated analysis of chromatin remodeler binding and nucleosome displacement activity following rapid remodeler depletion, we investigate the interplay between these enzymes and their impact on transcription in budding yeast. We show that many promoters are acted upon by multiple CRs that operate either cooperatively or in opposition to position the key transcription start site-associated +1 nucleosome. Functional assays suggest that +1 nucleosome positioning often reflects a trade-off between maximizing RNA Polymerase II recruitment and minimizing transcription initiation at incorrect sites. Finally, we show that nucleosome movement following CR inactivation usually results from the activity of another CR and that in the absence of any remodeling activity +1 nucleosomes maintain their positions. Our results provide a detailed picture of fundamental mechanisms linking promoter nucleosome architecture to transcription initiation.

Parkinson disease (PD) is characterized by a pivotal progressive loss of substantia nigra dopaminergic neurons and aggregation of α-synuclein protein encoded by the SNCA gene. Genome-wide association studies identified almost 100 sequence variants linked to PD in SNCA. However, the consequences of this genetic variability are rather unclear. Herein, our analysis on selective single nucleotide polymorphisms (SNPs) which are highly associated with the PD susceptibility revealed that several SNP sites attribute to the nucleosomes and overlay with bivalent regions poised to adopt either active or repressed chromatin states. We also identified large number of transcription factor (TF) binding sites associated with these variants. In addition, we located two docking sites in the intron-1 methylation prone region of SNCA which are required for the putative interactions with DNMT1. Taken together, our analysis reflects an additional layer of epigenomic contribution for the regulation of the SNCA gene in PD.

SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/.

Summary We present SPar-K (Signal Partitioning with K-means), a method to search for archetypical chromatin architectures by partitioning a set of genomic regions characterized by chromatin signal profiles around ChIP-seq peaks and other kinds of functional sites. This method efficiently deals with problems of data heterogeneity, limited misalignment of anchor points and unknown orientation of asymmetric patterns. Availability and implementation SPar-K is a C++ program available on GitHub https://github.com/romaingroux/SPar-K and Docker Hub https://hub.docker.com/r/rgroux/spar-k. Supplementary information Supplementary data are available at Bioinformatics online.

Summary Transcription factors regulate gene expression by binding to specific short DNA sequences of 5–20 bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or transcription factor binding site model from a public database. Availability and implementation The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. Supplementary information Supplementary data are available at Bioinformatics online.

SummaryGenome-wide studies on the genetic basis of gene expression and the structural properties of chromatin have considerably advanced our understanding of the function of the human genome. However, it remains unclear how structure relates to function and, in this work, we aim at bridging both by assembling a dataset that combines the activity of regulatory elements (e.g. enhancers and promoters), expression of genes and genetic variations of 317 individuals and across two cell types. We show that the regulatory activity is structured within 12,583 Cis Regulatory Domains (CRDs) that are cell type specific and highly reflective of the local (i.e. Topologically Associating Domains) and global (i.e. A/B nuclear compartments) nuclear organization of the chromatin. These CRDs essentially delimit the sets of active regulatory elements involved in the transcription of most genes, thereby capturing complex regulatory networks in which the effects of regulatory variants are propagated and combined to finally mediate expression Quantitative Trait Loci. Overall, our analysis reveals the complexity and specificity of cis and trans regulatory networks and their perturbation by genetic variation.

Normal T cell repertoire selection and evolution in antigen-specific responses is poorly understood. We have recently described an MHC class I-restricted response characterized by an overwhelming expansion of CD8 cells expressing a Vbeta10 TCR, thus allowing the identification of antigen-selected cells directly ex vivo. Our present strategy to follow the overall TCR repertoire selection was to monitor the expression of a particular TCR alpha chain (Valpha8) on antigen-selected Vbeta10(+) cells by four-color flow cytometry. We demonstrate that while there is substantial variation among the responder mice in Valpha8 usage, the repertoires of individual animals remain relatively stable over long periods of time (>1 year), with or without repeated antigenic challenge. Thus if any evolution of this response occurs upon re-exposure to antigen, it would appear not to skew the TCR repertoire established during the primary response.

The Eukaryotic Promoter Database (EPD), available online at http://epd.vital-it.ch, is a collection of experimentally defined eukaryotic POL II promoters which has been maintained for more than 25 years. A promoter is represented by a single position in the genome, typically the major transcription start site (TSS). EPD primarily serves biologists interested in analysing the motif content, chromatin structure or DNA methylation status of co-regulated promoter subsets. Initially, promoter evidence came from TSS mapping experiments targeted at single genes and published in journal articles. Today, the TSS positions provided by EPD are inferred from next-generation sequencing data distributed in electronic form. Traditionally, EPD has been a high-quality database with low coverage. The focus of recent efforts has been to reach complete gene coverage for important model organisms. To this end, we introduced a new section called EPDnew, which is automatically assembled from multiple, carefully selected input datasets. As another novelty, we started to use chromatin signatures in addition to mRNA 5'tags to locate promoters of weekly expressed genes. Regarding user interfaces, we introduced a new promoter viewer which enables users to explore promoter-defining experimental evidence in a UCSC genome browser window.

Motivation: We have witnessed an enormous increase in ChIP-Seq data for histone modifications in the past few years. Discovering significant patterns in these data is an important problem for understanding biological mechanisms. Results: We propose probabilistic partitioning methods to discover significant patterns in ChIP-Seq data. Our methods take into account signal magnitude, shape, strand orientation and shifts. We compare our methods with some current methods and demonstrate significant improvements, especially with sparse data. Besides pattern discovery and classification, probabilistic partitioning can serve other purposes in ChIP-Seq data analysis. Specifically, we exemplify its merits in the context of peak finding and partitioning of nucleosome positioning patterns in human promoters. Availability and implementation: The software and code are available in the supplementary material. Contact: Philipp.Bucher@isb-sib.ch Supplementary information: Supplementary Data are available at Bioinformatics online.

We present an update of the Eukaryotic Promoter Database EPD (http://epd.vital-it.ch), more specifically on the EPDnew division, which contains comprehensive organisms-specific transcription start site (TSS) collections automatically derived from next generation sequencing (NGS) data. Thanks to the abundant release of new high-throughput transcript mapping data (CAGE, TSS-seq, GRO-cap) the database could be extended to plant and fungal species. We further report on the expansion of the mass genome annotation (MGA) repository containing promoter-relevant chromatin profiling data and on improvements for the EPD entry viewers. Finally, we present a new data access tool, ChIP-Extract, which enables computational biologists to extract diverse types of promoter-associated data in numerical table formats that are readily imported into statistical analysis platforms such as R.

Resolving the DNA-binding specificities of transcription factors (TFs) is of critical value for understanding gene regulation. Here, we present a novel, semiautomated protein-DNA interaction characterization technology, selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq). SMiLE-seq is neither limited by DNA bait length nor biased toward strong affinity binders; it probes the DNA-binding properties of TFs over a wide affinity range in a fast and cost-effective fashion. We validated SMiLE-seq by analyzing 58 full-length human, mouse, and Drosophila TFs from distinct structural classes. All tested TFs yielded DNA-binding models with predictive power comparable to or greater than that of other in vitro assays. De novo motif discovery on all JUN-FOS heterodimers and several nuclear receptor-TF complexes provided novel insights into partner-specific heterodimer DNA-binding preferences. We also successfully analyzed the DNA-binding properties of uncharacterized human C2H2 zinc-finger proteins and validated several using ChIP-exo.

UCNEbase (http://ccg.vital-it.ch/UCNEbase) is a free, web-accessible information resource on the evolution and genomic organization of ultra-conserved non-coding elements (UCNEs). It currently covers 4351 such elements in 18 different species. The majority of UCNEs are supposed to be transcriptional regulators of key developmental genes. As most of them occur as clusters near potential target genes, the database is organized along two hierarchical levels: individual UCNEs and ultra-conserved genomic regulatory blocks (UGRBs). UCNEbase introduces a coherent nomenclature for UCNEs reflecting their respective associations with likely target genes. Orthologous and paralogous UCNEs share components of their names and are systematically cross-linked. Detailed synteny maps between the human and other genomes are provided for all UGRBs. UCNEbase is managed by a relational database system and can be accessed by a variety of web-based query pages. As it relies on the UCSC genome browser as visualization platform, a large part of its data content is also available as browser viewable custom track files. UCNEbase is potentially useful to any computational, experimental or evolutionary biologist interested in conserved non-coding DNA elements in vertebrates.

Regulation of mRNA stability by RNA-protein interactions contributes significantly to quantitative aspects of gene expression. We have identified potential mRNA targets of the AU-rich element binding protein AUF1. Myc-tagged AUF1 p42 was induced in mouse NIH/3T3 cells and RNA-protein complexes isolated using anti-myc tag antibody beads. Bound mRNAs were analyzed with Affymetrix microarrays. We have identified 508 potential target mRNAs that were at least 3-fold enriched compared to control cells without myc-AUF1. 22.3% of the enriched mRNAs had an AU-rich cluster in the ARED Organism database, against 16.3% of non-enriched control mRNAs. The enrichment towards AU-rich elements was also visible by AREScore with an average value of 5.2 in the enriched mRNAs versus 4.2 in the control group. Yet, numerous mRNAs were enriched without a high ARE score. The enrichment of tetrameric and pentameric sequences suggests a broad AUF1 p42-binding spectrum at short U-rich sequences flanked by A or G. Still, some enriched mRNAs were highly unstable, as those of TNFSF11 (known as RANKL), KLF10, HES1, CCNT2, SMAD6, and BCL6. We have mapped some of the instability determinants. HES1 mRNA appeared to have a coding region determinant. Detailed analysis of the RANKL and BCL6 3’UTR revealed for both that full instability required two elements, which are conserved in evolution. In RANKL mRNA both elements are AU-rich and separated by 30 bases, while in BCL6 mRNA one is AU-rich and 60 bases from a non AU-rich element that potentially forms a stem-loop structure., PLoS ONE, 13 (11), ISSN:1932-6203

Applications of optimal matching analysis in the social sciences are typically based on sequences of specific social statuses that model the residential, family, or occupational trajectories of individuals. Despite the broadly recognized interdependence of these statuses, few attempts have been made to systematize the ways in which optimal matching analysis should be applied multidimensionally—that is, in an approach that takes into account multiple trajectories simultaneously. Based on methods pioneered in the field of bioinformatics, this paper proposes a method of multichannel sequence analysis (MCSA) that simultaneously extends the usual optimal matching analysis (OMA) to multiple life spheres. Using data from the Swiss household panel (SHP), we examine the types of trajectories obtained using MCSA. We also consider a random data set and find that MCSA offers an alternative to the sole use of ex-post sum of distance matrices by locally aligning distinct life trajectories simultaneously. Moreover, MCSA reduces the complexity of the typologies it allows to produce, without making them less informative. It is more robust to noise in the data, and it provides more reliable alignments than two independent OMA.

Nucleosome depletion at transcription start sites (TSS) has been documented genome-wide in multiple eukaryotic organisms. However, the mechanisms that mediate this nucleosome depletion and its functional impact on transcription remain largely unknown. We have studied these issues at human MHC class II (MHCII) genes. Activation-induced nucleosome free regions (NFR) encompassing the TSS were observed at all MHCII genes. Nucleosome depletion was exceptionally strong, attaining over 250-fold, at the promoter of the prototypical HLA-DRA gene. The NFR was induced primarily by the transcription factor complex that assembles on the conserved promoter-proximal enhancer situated upstream of the TSS. Functional analyses performed in the context of native chromatin demonstrated that displacing the NFR without altering the sequence of the core promoter induced a shift in the position of the TSS. The NFR thus appears to play a critical role in transcription initiation because it directs correct TSS positioning in vivo. Our results provide support for a novel mechanism in transcription initiation whereby the position of the TSS is controlled by nucleosome eviction rather than by promoter sequence.