Improved linkage analysis of Quantitative Trait Loci using bulk segregants unveils a novel determinant of high ethanol tolerance in yeast

Background: Bulk segregant analysis (BSA) coupled to high throughput sequencing is a powerful method to map genomic regions related with phenotypes of interest. It relies on crossing two parents, one inferior and one superior for a trait of interest. Segregants displaying the trait of the superior parent are pooled, the DNA extracted and sequenced. Genomic regions linked to the trait of interest are identified by searching the pool for overrepresented alleles that normally originate from the superior parent. BSA data analysis is non-trivial due to sequencing, alignment and screening errors. Results: To increase the power of the BSA technology and obtain a better distinction between spuriously and truly linked regions, we developed EXPLoRA (EXtraction of over-rePresented aLleles in BSA), an algorithm for BSA data analysis that explicitly models the dependency between neighboring marker sites by exploiting the properties of linkage disequilibrium through a Hidden Markov Model (HMM). Reanalyzing a BSA dataset for high ethanol tolerance in yeast allowed reliably identifying QTLs linked to this phenotype that could not be identified with statistical significance in the original study. Experimental validation of one of the least pronounced linked regions, by identifying its causative gene VPS70, confirmed the potential of our method. Conclusions: EXPLoRA has a performance at least as good as the state-of-the-art and it is robust even at low signal to noise ratio's i.e. when the true linkage signal is diluted by sampling, screening errors or when few segregants are available

Interactive Visualization of Emerging Topics in Multiple Social Media Streams

This paper introduces an interactive news flow visualization that reveals emerging topics in dynamic digital content archives. The presented approach combines several visual metaphors and can be easily adapted to present multi-source social media datasets. In the context of this work, we discuss various methods for improving visual interfaces for accessing aggregated media representations. We combine falling blocks with bar graphs and arcs, but keep these elements clearly separated in different areas of the display. The arc metaphor is adapted and enriched with interactive controls to help users understand the dataset’s underlining meaning. The paper describes the implementation of the prototype and discusses design issues with a particular emphasis on visual metaphors to highlight hidden relations in digital content. We conclude with a summary of the lessons learnt and the integration of the visualization component into the Media Watch on Climate Change (www.ecoresearch.net/climate), a public Web portal that aggregates environmental information from a variety of online sources including news media, blogs and other social media such as Twitter, YouTube and Facebook

Visualizing Contextual and Dynamic Features of Micropost Streams

Visual techniques provide an intuitive way of making sense of the large amounts of microposts available from social media sources, particularly in the case of emerging topics of interest to a global audience, which often raise controversy among key stakeholders. Micropost streams are context-dependent and highly dynamic in nature. We describe a visual analytics platform to handle high-volume micropost streams from multiple social media channels. For each post we extract key contextual features such as location, topic and sentiment, and subsequently render the resulting multi-dimensional information space using a suite of coordinated views that support a variety of complex information seeking behaviors. We also describe three new visualization techniques that extend the original platform to account for the dynamic nature of micro¬post streams through dynamic topography information landscapes, news flow diagrams and longitudinal cross-media analyses

Visualizing Statistical Linked Knowledge for Decision Support

In a global and interconnected economy, decision makers often need to consider information from various domains. A tourism destination manager, for example, has to correlate tourist behavior with financial and environmental indicators to allocate funds for strategic long-term investments. Statistical data underpins a broad range of such cross-domain decision tasks. A variety of statistical datasets are available as Linked Open Data, often incorporated into visual analytics solutions to support decision making. What are the principles, architectures, workflows and implementation design patterns that should be followed for building such visual cross-domain decision support systems. This article introduces a methodology to integrate and visualize cross-domain statistical data sources by applying selected RDF Data Cube (QB) principles. A visual dashboard built according to this methodology is presented and evaluated in the context of two use cases in the tourism and telecommunications domains

Impact ionization induced by terahertz radiation in HgTe quantum wells of critical thickness

We report on the observation of terahertz (THz) radiation induced band-to-band impact ionization in \HgTe quantum well (QW) structures of critical thickness, which are characterized by a nearly linear energy dispersion. The THz electric field drives the carriers initializing electron-hole pair generation. The carrier multiplication is observed for photon energies less than the energy gap under the condition that the product of the radiation angular frequency $\omega$ and momentum relaxation time $\tau_{\text l}$ larger than unity. In this case, the charge carriers acquire high energies solely because of collisions in the presence of a high-frequency electric field. The developed microscopic theory shows that the probability of the light impact ionization is proportional to $\exp(-E_0^2/E^2)$, with the radiation electric field amplitude $E$ and the characteristic field parameter $E_0$. As observed in experiment, it exhibits a strong frequency dependence for $\omega \tau \gg 1$ characterized by the characteristic field $E_0$ linearly increasing with the radiation frequency $\omega$

Giant ratchet magneto-photocurrent in graphene lateral superlattices

We report on the observation of the magnetic quantum ratchet effect in graphene with a lateral dual-grating top gate (DGG) superlattice. We show that the THz ratchet current exhibits sign-alternating magneto-oscillations due to the Shubnikov–de Haas effect. The amplitude of these oscillations is greatly enhanced as compared to the ratchet effect at zero magnetic field. The direction of the current is determined by the lateral asymmetry which can be controlled by variation of gate potentials in DGG. We also study the dependence of the ratchet current on the orientation of the terahertz electric field (for linear polarization) and on the radiation helicity (for circular polarization). Notably, in the latter case, switching from right- to left-circularly polarized radiation results in an inversion of the photocurrent direction. We demonstrate that most of our observations can be well fitted by the drift-diffusion approximation based on the Boltzmann kinetic equation with the Landau quantization fully encoded in the oscillations of the density of states

Current views on the role of Notch signaling and the pathogenesis of human leukemia

The Notch signaling pathway is highly conserved from Drosophila to humans and plays an important role in the regulation of cellular proliferation, differentiation and apoptosis

Characterization of caspase‐2 inhibitors based on specific sites of caspase‐2‐mediated proteolysis

Since the discovery of the caspase-2 (Casp2)-mediated ∆tau314 cleavage product and its associated impact on tauopathies such as Alzheimer's disease, the design of selective Casp2 inhibitors has become a focus in medicinal chemistry research. In the search for new lead structures with respect to Casp2 selectivity and drug-likeness, we have taken an approach by looking more closely at the specific sites of Casp2-mediated proteolysis. Using seven selected protein cleavage sequences, we synthesized a peptide series of 53 novel molecules and studied them using in vitro pharmacology, molecular modeling, and crystallography. Regarding Casp2 selectivity, AcITV(Dab)D-CHO (23) and AcITV(Dap)D-CHO (26) demonstrated the best selectivity (1–6-fold), although these trends were only moderate. However, some analogous tetrapeptides, most notably AcDKVD-CHO (45), showed significantly increased Casp3 selectivities (>100-fold). Tetra- and tripeptides display decreased or no Casp2 affinity, supporting the assumption that a motif of five amino acids is required for efficient Casp2 inhibition. Overall, the results provide a reasonable basis for the development of both selective Casp2 and Casp3 inhibitors