In recent years, the availability of reduced representation library (RRL) methods has catalysed an expansion of genome-scale studies to characterize both model and non-model organisms. Most of these methods rely on the use of restriction enzymes to obtain DNA sequences at a genome-wide level. These approaches have been widely used to sequence thousands of markers across individuals for many organisms at a reasonable cost, revolutionizing the field of population genomics. However, there are still some limitations associated with these methods, in particular the high molecular weight DNA required as starting material, the reduced number of common loci among investigated samples, and the short length of the sequenced site-associated DNA. Here, we present MobiSeq, a RRL protocol exploiting simple laboratory techniques, that generates genomic data based on PCR targeted enrichment of transposable elements and the sequencing of the associated flanking region. We validate its performance across 103 DNA extracts derived from three mammalian species: grey wolf (Canis lupus), red deer complex (Cervus sp.) and brown rat (Rattus norvegicus). MobiSeq enables the sequencing of hundreds of thousands loci across the genome and performs SNP discovery with relatively low rates of clonality. Given the ease and flexibility of MobiSeq protocol, the method has the potential to be implemented for marker discovery and population genomics across a wide range of organisms—enabling the exploration of diverse evolutionary and conservation questions.

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems are key immune mechanisms helping prokaryotic species fend off RNA and DNA viruses. CRISPR/Cas9 has broad applications in basic research and biotechnology and has been widely used across eukaryotic species for genome engineering and functional analysis of genes. The recently developed CRISPR/Cas13 systems target RNA rather than DNA and thus offer new potential for transcriptome engineering and combatting RNA viruses. Here, we used CRISPR/LshCas13a to stably engineer Arabidopsis thaliana for interference against the RNA genome of Turnip mosaic virus (TuMV). Our data demonstrate that CRISPR RNAs (crRNAs) guiding Cas13a to the sequences encoding helper component proteinase silencing suppressor (HC-Pro) or GFP target 2 (GFP-T2) provide better interference compared to crRNAs targeting other regions of the TuMV RNA genome. This work demonstrates the exciting potential of CRISPR/Cas13 to be used as an antiviral strategy to obstruct RNA viruses, and encourages the search for more robust and effective Cas13 variants or CRISPR systems that can target RNA.

In mammalian cells, transcribed enhancers (TrEns) play important roles in the initiation of gene expression and maintenance of gene expression levels in a spatiotemporal manner. One of the most challenging questions is how the genomic characteristics of enhancers relate to enhancer activities. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers’ DNA code in a more systematic way. To address this problem, we developed a novel computational framework, Transcribed Enhancer Landscape Search (TELS), aimed at identifying predictive cell type/tissue-specific motif signatures of TrEns. As a case study, we used TELS to compile a comprehensive catalogue of motif signatures for all known TrEns identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that combinations of different short motifs characterize in an optimized manner cell type/tissue-specific TrEns. Our study is the first to report combinations of motifs that maximize classification performance of TrEns exclusively transcribed in one cell type/tissue from TrEns exclusively transcribed in different cell types/tissues. Moreover, we also report 31 motif signatures predictive of enhancers’ broad activity. TELS codes and material are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

In this paper, we accurately model the impact of aggregate hardware impairments (HWIs) in communication systems as improper Gaussian signals (IGS), which can describe the asymmetric characteristics of different HWI sources. The proposed model encourages us to adopt IGS scheme for transmission that represents a general signaling scheme compared with the conventional scheme, proper Gaussian signaling (PGS). Firstly, we express the achievable rate of multiple-input and multiple-output (MIMO) system suffering from various HWIs employing PGS and IGS schemes, when the aggregate effect of HWI is modeled as IGS. Moreover, we tune the transmit IGS statistical characteristics to maximize the achievable rate for HWI-SIMO system with two receiver combining schemes. Then, we propose an adaptive scheme to switch between maximal IGS and PGS schemes under certain conditions to improve the system performance with least computational/optimization overhead. Finally, we validate the analytic expressions through numerical and simulation results and quantify the gain reaped from adopting IGS scheme compared with PGS scheme.

It is well known that moving magnetic textures may pump spin and charge currents along the direction of motion, a phenomenon called electronic pumping. Here, the electronic pumping arising from the steady motion of ferromagnetic skyrmions is investigated by solving the time evolution of the Schrödinger equation implemented on a tight-binding model with the statistical physics of the many-body problem. In contrast with rigid one-dimensional magnetic textures, we show that steadily moving magnetic skyrmions are able to pump large dc currents. This ability arises from their nontrivial magnetic topology, i.e., the coexistence of the spin-motive force and the topological Hall effect. Based on an adiabatic scattering theory, we compute the pumped current and demonstrate that it scales with the reflection coefficient of the conduction electrons against the skyrmion. In other words, in the semiclassical limit, reducing the size of the skyrmion and the width of the nanowire enhances this effect, making it scalable. We propose that such a phenomenon can be exploited in the context of racetrack devices, where the electronic pumping enhances the collective motion of the train of skyrmions.

We discuss the role of the metal-ligand (M-L) interfaces in the chemistry of ligand protected, atomically precise noble metal clusters, a new and expanding family of nanosystems, in solution as well as in gas phase. A few possible mechanisms in which the structure and dynamics of M-L interfaces could trigger intercluster exchange reactions are presented first. How interparticle chemistry can be a potential mechanism of Ostwald ripening, a well-known particle coarsening process, is also discussed. Reaction of Ag59(2,5-DCBT)32 (DCBT = dichlorobenzenethiol) with 2,4-DCBT leading to the formation of Ag44(2,4-DCBT)30 is presented, demonstrating the influence of the ligand structure in ligand-induced chemical transformations of clusters. We also discuss structural isomerism of clusters such as Ag44(SR)30 (-SR = alkyl/aryl thiolate) in gas phase wherein the occurrence of isomerism is attributed to the structural rearrangements in the M-L bonding network. Interfacial bonding between Au25(SR)18 clusters leading to the formation of cluster dimers and trimers is also discussed. Finally, we show that desorption of phosphine and hydride ligands on a silver cluster, [Ag18(TPP)10H16]2+ (TPP = triphenylphosphine) in gas phase, lead to the formation of a naked silver cluster of precise nuclearity, such as Ag17+. We demonstrate that the nature of the M-L interfaces, i.e., the oxidation state of metal atoms, structure of the ligand, M-L bonding network, etc., play key roles in the chemical reactivity of clusters. The structure, dynamics and chemical reactivity of nanosystems in general are to be explored together to obtain new insights into their emerging science.

The outstanding performance of deep neural networks (DNNs), for the visual recognition task in particular, has been demonstrated on several large-scale benchmarks. This performance has immensely strengthened the line of research that aims to understand and analyze the driving reasons behind the effectiveness of these networks. One important aspect of this analysis has recently gained much attention, namely the reaction of a DNN to noisy input. This has spawned research on developing adversarial input attacks as well as training strategies that make DNNs more robust against these attacks. To this end, we derive in this paper exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network (Affine, ReLU, Affine) subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the interclass confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks.

Matrix approaches are useful for linking ecosystem services to habitats that underpin their delivery. Matrix applications in marine ecosystem services research have been primarily qualitative, focusing on ‘habitat presence’ without including other attributes that effect service potential. We developed an evidence-based matrix approach of Ecosystem Service Potential (ESP) for New Zealand benthic marine habitats, and used two marine reserves to demonstrate that integrating information on the spatial extent and quality of habitats improved ESP evaluation. The two case studies identified substantial spatio-temporal variability in ESP: within one reserve, specific ESP showed an approximately 1.5-fold increase in the 29 years following protection. A comparison of two reserves found that the spatial extent of habitats contributing to the medicinal resources and waste-water treatment were 5 and 53 times greater respectively in one relative to the other. Integrating habitat area and quality with the ESP matrix improves on previous marine matrix-based approaches, providing a better indication of service potential. The matrix approach helps to communicate the non-market value of supporting and regulating services and can be used by resource managers to identify and track the potential for benefits derived from benthic marine habitats within existing, or new, marine protected areas.

Objectives \nCorals, the building blocks of reef ecosystems, have been severely threatened by climate change. Coral bleaching, the loss of the coral’s endosymbiotic algae, occurs as a consequence of increasing ocean temperature. To understand mechanisms of stress tolerance in symbiotic cnidarians, the sea anemone Exaiptasia pallida from different regions was heat stressed. The three strains originated from the Red Sea, Hawaii and North Carolina, each with different temperature profiles, enabling a comparative study of local adaptation strategies. \nData description \nWhole transcriptome and proteome data were collected from all anemones at control and stress condition. As part of the analysis of this large, multi-omic data, we wrote a script that creates a tabular datasheet that summarized the transcriptomic and proteomic changes for every gene. It facilitates the search of individual genes, or a group of genes, their up- or downregulation during stress and whether this change in expression was statistically significant. Furthermore, it enables examining if changes in RNA correspond to those in proteins. The datasheet can be used for future comparisons, as well as search and development of biomarkers.

Enzymes originating from hostile environments offer exceptional stability under industrial conditions and are therefore highly in demand. Using single-cell genome data, we identified the alcohol dehydrogenase gene, adh/a1a, from the Atlantis II Deep Red Sea brine pool. ADH/A1a is highly active at elevated temperatures and high salt concentrations (optima at 70 °C and 4 M KCl), and withstands organic solvents. The polyextremophilic ADH/A1a exhibits a broad substrate scope including aliphatic and aromatic alcohols and is able to reduce cinnamyl-methyl-ketone and raspberry ketone in the reverse reaction, making it a possible candidate for the production of chiral compounds. Here, we report the affiliation of ADH/A1a to a rare enzyme family of microbial cinnamyl-alcohol dehydrogenases and explain unique structural features for halo- and thermoadaptation.