ALBERT

Description: Pathogenic variants that disrupt human mitochondrial protein synthesis are associated with a clinically heterogenous group of diseases. Despite an impairment in oxidative phosphorylation being a common phenotype, the underlying molecular pathogenesis is more complex than simply a bioenergetic deficiency. Currently, we have limited mechanistic understanding on the scope by which a primary defect in mitochondrial protein synthesis contributes to organelle dysfunction. Since the proteins encoded in the mitochondrial genome are hydrophobic and need co-translational insertion into a lipid bilayer, responsive quality control mechanisms are required to resolve aberrations that arise with the synthesis of truncated and misfolded proteins. Here, we show that defects in the OXA1L-mediated insertion of MT-ATP6 nascent chains into the mitochondrial inner membrane are rapidly resolved by the AFG3L2 protease complex. Using pathogenic MT-ATP6 variants, we then reveal discrete steps in this quality control mechanism and the differential functional consequences to mitochondrial gene expression. The inherent ability of a given cell type to recognize and resolve impairments in mitochondrial protein synthesis may in part contribute at the molecular level to the wide clinical spectrum of these disorders.

Description: Motivation DNA Methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to exploit Nanopore data for methylation detection. However, current approaches rely on a human-defined threshold to detect the methylation status of a genomic position and are not optimized to detect sites methylated at low frequency. Furthermore, most methods employ either the Nanopore signals or the basecalling errors as the model input and do not take advantage of their combination. Results Here we present DeepMP, a convolutional neural network (CNN)-based model that takes information from Nanopore signals and basecalling errors to detect whether a given motif in a read is methylated or not. Besides, DeepMP introduces a threshold-free position modification calling model sensitive to sites methylated at low frequency across cells. We comprehensively benchmarked DeepMP against state-of-the-art methods on E. coli, human and pUC19 datasets. DeepMP outperforms current approaches at read-based and position-based methylation detection across sites methylated at different frequencies in the three datasets. Availability DeepMP is implemented and freely available under MIT license at https://github.com/pepebonet/DeepMP Supplementary information Supplementary data are available at Bioinformatics online.

Description: Motivation With the advancement of sequencing technologies, genomic data sets are constantly being expanded by high volumes of different data types. One recently introduced data type in genomic science is genomic signals, which are usually short-read coverage measurements over the genome. To understand and evaluate the results of such studies, one needs to understand and analyze the characteristics of the input data. Results SigTools is an R-based genomic signals visualization package developed with two objectives: 1) to facilitate genomic signals exploration in order to uncover insights for later model training, refinement, and development by including distribution and autocorrelation plots. 2) to enable genomic signals interpretation by including correlation, and aggregation plots. In addition, our corresponding web application, SigTools-Shiny, extends the accessibility scope of these modules to people who are more comfortable working with graphical user interfaces instead of command-line tools. Availability SigTools source code, installation guide, and manual is freely available on http://github.com/shohre73.

Description: Here, the corrosion weight-loss method, surface analysis technology, and electrochemical test methods were used to study the corrosion behavior and electrochemical characteristics of experimental samples of Q345R steel in a sterile solution (pH 2.0) and a solution containing T. ferrooxidans. The growth cycle of T. ferrooxidans was determined to be approximately 8 days. The corrosion weight-loss method showed that the corrosion rate of Q345R carbon steel coupons decreased with time in the T. ferrooxidans system and the sterile system; the corrosion rate was approximately two times higher in the T. ferrooxidans system than in the sterile system. The corrosion morphology results showed that the presence of T. ferrooxidans promotes the corrosion of Q345R steel and increases the local corrosion of the matrix material. The electrochemical test results showed that after 5 days of corrosion, the polarization resistance of the T. ferrooxidans system was approximately 50% of that of the sterile system, and the corrosion current density of the T. ferrooxidans system was approximately twice as high as that of the sterile system. Therefore, T. ferrooxidans can accelerate the corrosion of Q345R steel two-fold.

Description: As good models for developing techniques, Haloarchaea are using as cell factories to produce a considerable concentration of bioplastics, polyhydroxyalkanoate (PHA), polyhydroxybutyrate (PHB), and polyhydroxyvalerate (PHV). In this study, low-cost carbon sources by Sudan Black staining was applied for screening haloarchaea a hypersaline environment (southern coast of Jeddah, Saudi Arabia). The growth of the selected isolate and PHB-production under different carbon sources, temperature, pH values and NaCl concentrations were investigated. The biopolymer was extracted and quantitatively measured. The biopolymer was qualitatively identified by Fourier-transform infra-red analysis (FTIR) and High Performance Liquid Chromatography (HPLC). The potential Haloarcula sp strain NRS20 (MZ520352) could significantly accumulate PHB under nutrient-limiting conditions using different carbon sources including starch, carboxymethyl cellulose (CMC), sucrose, glucose and glycerol with 23.83%, 14%, 11%, 12% and 8% of PHB/CDW respectively under 25% NaCl (w/v), pH 7, at 37 °C. The results of FTIR pattern indicated that the significant peak at 1709.22 cm−1 confirmed the presence of the ester carbonyl-group (C=O) which is typical of PHB. HPLC analysis indicated that produced PHB was detected at 7.5 min with intensity exceeding the standard PHB at 8.0 min. Few potential species of haloarchaea were reported for economical PHB-production, here, Haloarcula sp strain NRS20 showed high content of PHB, exhibited a promising PHB-producer using inexpensive sources of carbon.

Description: Light and water availability are likely to vary over the lifespan of closed-canopy forest trees with understory trees experiencing greater limitations to growth by light and canopy trees greater limitation due to drought. As drought and shade have opposing effects on isotope discrimination (Δ13C), paired measurement of ring width and Δ13C can potentially be used to differentiate between water and light limitations on tree growth. We tested this approach for Cedrela trees from three tropical forests in Bolivia and Mexico that differ in rainfall and canopy structure. Using lifetime ring width and Δ13C data for trees of up to and over 200 years old, we assessed how controls on tree growth changed from understory to the canopy. Growth and Δ13C are mostly anti-correlated in the understory but this anti-correlation disappeared or weakened when trees reached the canopy, especially at the wettest site. This indicates that understory growth variation is controlled by photosynthetic carbon assimilation (A) due to variation in light levels. Once trees reached the canopy, inter-annual variation in growth and Δ13C at one of the dry sites showed positive correlations, indicating inter-annual variation in growth is driven by variation in water stress affecting stomatal conductance (gs). Paired analysis of ring widths and carbon isotopes provides significant insight to discerning between environmental factors controlling growth over trees’ life; strong light limitations for understory trees in closed-canopy moist forests switched to drought stress for (sub)canopy trees in dry forests. We show that combined isotope and ring width measurements can significantly improve our insights in tree functioning and be used to disentangle limitations due to shade from those due to drought.

Description: Purpose. To investigate indirect radiation-induced changes in airways as precursors to atelectasis post radiation therapy (RT). Methods. Three Wisconsin Miniature Swine (WMS TM ) underwent a research course of 60 Gy in 5 fractions delivered to a targeted airway/vessel in the inferior left lung. The right lung received a max point dose

Description: Energy absorption for AZ31 magnesium Alloy was investigated with Split Hopkinson Pressure Bar using single stress wave so as to avoid multiple stress wave loading. The stress wave amplitude, which was in elastic stress range and propagated along the AZ31 magnesium bar, was reduced with increasing propagating distance, and with increasing stress wave amplitude, the stress wave amplitude reduction along the magnesium bar was increased losing more energy as compared with that of the stress wave with lower amplitude. The drastically decreased stress wave amplitude could be explained based on dislocations movements, which was similar to the established theory of damping for the explanation of the energy loss during cyclic loading. However, it was not the case for LY12 aluminum alloy: the stress wave amplitude changed slightly without drastic energy loss regardless of the variation of stress wave amplitude.

Description: An innovative method of combustion–calcination of a nitrate–ethanol solution to produce magnetic Co0.5Ni0.5Fe2O4 nanoparticles was developed. The calcination temperature and the volume of ethanol were two pivotal elements that determine the properties of the Co0.5Ni0.5Fe2O4 nanoparticles in this study. When the volume of ethanol used was increased from 20 ml to 40 ml, the crystallinity of the Co0.5Ni0.5Fe2O4 nanoparticles increased; further increase of the volume of ethanol decreased the crystallinity. The smallest nanoparticle was obtained using 20 ml ethanol. As the calcination temperature increased from 400 °C to 700 °C, the saturation magnetization of the Co0.5Ni0.5Fe2O4 nanoparticles increased from 12.8 emu g−1 to 30.8 emu g−1. Co0.5Ni0.5Fe2O4 nanoparticles fabricated using 20 ml ethanol at 400 °C were used to study the removal of methyl blue (MB) by adsorption. Experimental data revealed that the adsorption was best described by pseudo-second kinetics. The adsorption isotherm applied the Temkin model, which indicated the presence of a single and multilayer associative mechanism in the adsorption of MB on the Co0.5Ni0.5Fe2O4 nanoparticles. The effect of pH and recycling on the adsorption was measured. At pH values ≥5, the adsorption was high. After eight cycles of use and recycling, the relative removal rate of MB by the Co0.5Ni0.5Fe2O4 nanoparticles was 75% of the initial adsorption value.

Description: Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

Description: Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.

Description: Motivation Alignment-free (AF) distance/similarity functions are a key tool for sequence analysis. Experimental studies on real datasets abound and, to some extent, there are also studies regarding their control of false positive rate (Type I error). However, assessment of their power, i.e., their ability to identify true similarity, has been limited to some members of the D2 family. The corresponding experimental studies have concentrated on short sequences, a scenario no longer adequate for current applications, where sequence lengths may vary considerably. Such a State of the Art is methodologically problematic, since information regarding a key feature such as power is either missing or limited. Results By concentrating on a representative set of word-frequency based AF functions, we perform the first coherent and uniform evaluation of the power, involving also Type I error for completeness. Two Alternative models of important genomic features (CIS Regulatory Modules and Horizontal Gene Transfer), a wide range of sequence lengths from a few thousand to millions, and different values of k have been used. As a result, we provide a characterization of those AF functions that is novel and informative. Indeed, we identify weak and strong points of each function considered, which may be used as a guide to choose one for analysis tasks. Remarkably, of the fifteen functions that we have considered, only four stand out, with small differences between small and short sequence length scenarios. Finally, in order to encourage the use of our methodology for validation of future AF functions, the Big Data platform supporting it is public. Availability The software is available at: https://github.com/pipp8/power_statistics Supplementary information Supplementary data are available at Bioinformatics online.

Description: As humans populated the world, they adapted to many varying environmental factors, including climate, diet, and pathogens. Because many of these adaptations were mediated by multiple non-coding variants with small effects on gene regulation, it has been difficult to link genomic signals of selection to specific genes, and to describe the regulatory response to selection. To overcome this challenge, we adapted PrediXcan, a machine learning method for imputing gene regulation from genotype data, to analyze low-coverage ancient human DNA (aDNA). First, we used simulated genomes to benchmark strategies for adapting PrediXcan to increase robustness to incomplete data. Applying the resulting models to 490 ancient Eurasians, we found that genes with the strongest divergent regulation among ancient populations with hunter-gatherer, pastoralist, and agricultural lifestyles are enriched for metabolic and immune functions. Next, we explored the contribution of divergent gene regulation to two traits with strong evidence of recent adaptation: dietary metabolism and skin pigmentation. We found enrichment for divergent regulation among genes proposed to be involved in diet-related local adaptation, and the predicted effects on regulation often suggest explanations for known signals of selection, e.g. at FADS1, GPX1, and LEPR. In contrast, skin pigmentation genes show little regulatory change over a 38,000-year time series of 2999 ancient Europeans, suggesting that adaptation mainly involved large-effect coding variants. This work demonstrates that combining aDNA with present-day genomes is informative about the biological differences among ancient populations, the role of gene regulation in adaptation, and the relationship between genetic diversity and complex traits.

Description: Motivation Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences between the importance of genes, which may not fit the real-world situation. Different genes have different mutation probabilities, and the vital genes associated with basic life activities have less fault tolerance to mutation. Equally treating all genes may bias the results of differential network inference. Thus, it is necessary to consider the importance of genes in the models of differential network inference. Results Based on the Gaussian graphical model with adaptive gene importance regularization, we develop a novel importance-penalized joint graphical Lasso method, IPJGL, for differential network inference. The presented method is validated by the simulation experiments as well as the real datasets. Furthermore, to precisely evaluate the results of differential network inference, we propose a new metric named APC2 for the differential levels of gene pairs. We apply IPJGL to analyze the TCGA colorectal and breast cancer datasets and find some candidate cancer genes with significant survival analysis results, including SOST for colorectal cancer and RBBP8 for breast cancer. We also conduct further analysis based on the interactions in the Reactome database and confirm the utility of our method. Availability R source code of importance-penalized joint graphical lasso is freely available at https://github.com/Wu-Lab/IPJGL. Supplementary information Supplementary materials are available at Bioinformatics online.

Description: The role of uric acid during primate evolution has remained elusive ever since it was discovered over 100 years ago that humans have unusually high levels of the small molecule in our serum. It has been difficult to generate a neutral or adaptive explanation in part because the uricase enzyme evolved to become a pseudogene in apes thus masking typical signals of sequence evolution. Adding to the difficulty is a lack of clarity on the functional role of uric acid in apes. One popular hypothesis proposes that uric acid is a potent antioxidant that increased in concentration to compensate for the lack of vitamin C synthesis in primate species ∼65 million years ago (Mya). Here, we have expanded on our previous work with resurrected ancient uricase proteins to better resolve the reshaping of uricase enzymatic activity prior to ape evolution. Our results suggest that the pivotal death-knell to uricase activity occurred between 20-30 Mya despite small sequential modifications to its catalytic efficiency for the tens of millions of years since primates lost their ability to synthesize vitamin C, and thus the two appear uncorrelated. We also use this opportunity to demonstrate how molecular evolution can contribute to biomedicine by presenting ancient uricases to human immune cells that assay for innate reactivity against foreign antigens. A highly stable and highly catalytic ancient uricase is shown to elicit a lower immune response in more human haplotypes than other uricases currently in therapeutic development.

Description: Background Almost half of aromatase inhibitor (AI)-treated breast cancer patients experience AI-associated musculoskeletal symptoms (AIMSS); 20-30% discontinue treatment because of severe symptoms. We hypothesized that we could identify predictors of pain reduction in AIMSS intervention trials by combining data from previously conducted trials. Methods We pooled patient-level data from 3 randomized trials testing interventions (omega-3 fatty acids, acupuncture, and duloxetine) for AIMSS that had similar eligibility criteria and the same patient-reported outcome measures. Only patients with baseline Brief Pain Inventory (BPI) average pain score of ≥ 4 of 10 were included. The primary outcome examined was 2-point reduction in average pain from baseline to week 12. Variable cut-point selection and logistic regression were used. Risk models were built by summing the number of factors statistically significantly associated with pain reduction. Analyses were stratified by study and adjusted for treatment arm. Results For the 583 analyzed patients, the four factors statistically significantly associated with pain reduction were FACT Functional Well-Being 〉24 and Physical Well-Being 〉14 (higher scores reflect better function), and WOMAC

Description: Sn63Pb37/SAC305 mixed solder joint is inevitably in the electronic device requiring high reliability, such as health care, aerospace etc. However, the usage history of mixed solder joint is relatively short and as such their interfacial behaviour and reliability in service has not been completely figure out. Herein, the evolution of microstructures in fully mixed Sn63Pb37/SAC305 BGA solder joints during high-temperature storage were systematically studied. After reflow soldering process, the Pb-rich phases uniformly distributed in the fully mixed joint. During the thermal aging test, the size of Pb-rich phases gradually coarsened. The intermetallic compound (IMC) layers thickness at the two-side interface (upper interface: between the pad on substrate and solder; lower interface: between the pad on PCB and solder) were also increased. Moreover, the growth kinetics models of two-side IMC layer were successfully established according to the Arrhenius equation. IMC layer grows faster at higher temperature, because of higher diffusion coefficient. With the increasing of aging time, the fracture position partially moved from the interface between Ni layer and IMC layer into IMC internal. These results may provide support for the reliable applications of mixed Sn63Pb37/SAC305 solder joints.

Description: In this study, high-density polyethylene (HDPE) surfaces were treated with plasma to enhance the adhesion of a water-based paint. A custom-built cold atmospheric pressure plasma jet (CAPPJ) device using a neon transformer as its power source was developed and used in the surface treatment. The jet nozzle of the device was made from polytetrafluoroethylene with two bare stainless-steel electrodes positioned laterally through the nozzle and opposite each other with a 1 mm gap. Gas was allowed to pass through the nozzle, exiting through a 1 mm diameter hole where a plasma jet is ejected through the arc from the electrodes. The effect of plasma treatment on HDPE surfaces was determined. Air and nitrogen were used as the process gases and exposure times were also varied. Hydrophilicity of the surface increased with longer plasma exposure with a corresponding 50% increase in surface free energy compared to the untreated surface. From Fourier transform infrared and x-ray photoelectron spectroscopy analysis, it was seen that plasma treatment introduced oxygen containing functionalities onto the surface. Increase in adhesion of a water-based paint was observed for plasma-treated HDPE sheets.

Description: Background To observe a long-term prognosis in late-onset multiple acyl-coenzyme-A dehydrogenation deficiency(MADD) patients and to determine whether riboflavin should be administrated in the long-term and high-dosage manner. Methods We studied the clinical, pathological and genetic features of 110 patients with late-onset MADD in a single neuromuscular center. The plasma riboflavin levels and a long-term follow-up were performed. Results Fluctuating proximal muscle weakness, exercise intolerance and dramatic responsiveness to riboflavin treatment were essential clinical features for all 110 MADD patients. Among them, we identified 106 cases with ETFDH variants, 1 case with FLAD1 variants and 3 cases without causal variants. On muscle pathology, fibers with cracks, atypical ragged red fibers(aRRFs) and diffuse decrease of SDH activity were the distinctive features of these MADD patients. The plasma riboflavin levels before treatment were significantly decreased in these patients as compared to healthy controls. Among 48 MADD patients with a follow-up of 6.1 years on average, 31 patients were free of muscle weakness recurrence, while 17 patients had episodes of slight muscle weakness upon riboflavin withdrawal, but recovered after retaking a small-dose of riboflavin for a short-term. Multivariate Cox regression analysis showed vegetarian diet and masseter weakness were independent risk factors for muscle weakness recurrence. Conclusion Fibers with cracks, aRRFs and diffuse decreased SDH activity distinguish MADD from other genotypes of lipid storage myopathy. For late-onset MADD, increased fatty acid oxidation and reduced riboflavin levels can induce episodes of muscle symptoms, which can be treated by short-term and small-dose of riboflavin therapy.

Description: Motivation Reverse engineering of gene regulatory networks (GRNs) has long been an attractive research topic in system biology. Computational prediction of gene regulatory interactions has remained a challenging problem due to the complexity of gene expression and scarce information resources. The high-throughput spatial gene expression data, like in situ hybridization images that exhibit temporal and spatial expression patterns, has provided abundant and reliable information for the inference of GRNs. However, computational tools for analyzing the spatial gene expression data are highly underdeveloped. Results In this study, we develop a new method for identifying gene regulatory interactions from gene expression images, called ConGRI. The method is featured by a contrastive learning scheme and deep Siamese convolutional neural network architecture, which automatically learns high-level feature embeddings for the expression images and then feeds the embeddings to an artificial neural network to determine whether or not the interaction exists. We apply the method to a Drosophila embryogenesis dataset and identify GRNs of eye development and mesoderm development. Experimental results show that ConGRI outperforms previous traditional and deep learning methods by a large margin, which achieves accuracies of 76.7% and 68.7% for the GRNs of early eye development and mesoderm development, respectively. It also reveals some master regulators for Drosophila eye development. Availabilityand implementation https://github.com/lugimzheng/ConGRI. Supplementary information Supplementary data are available at Bioinformatics online.

Description: The European Variation Archive (EVA; https://www.ebi.ac.uk/eva/) is a resource for sharing all types of genetic variation data (SNPs, indels, and structural variants) for all species. The EVA was created in 2014 to provide FAIR access to genetic variation data and has since grown to be a primary resource for genomic variants hosting 〉3 billion records. The EVA and dbSNP have established a compatible global system to assign unique identifiers to all submitted genetic variants. The EVA is active within the Global Alliance of Genomics and Health (GA4GH), maintaining, contributing and implementing standards such as VCF, Refget and Variant Representation Specification (VRS). In this article, we describe the submission and permanent accessioning services along with the different ways the data can be retrieved by the scientific community.

Description: The influence of deep cryogenic treatment on the erosive wear performance of Stainless Steel-316L (SS-316L) used in hydropower plants is studied. For this purpose, several SS-316L samples were held at deep cryogenic temperatures (−196 °C) for different soaking periods (12, 24, 36 h). The erosive wear tests were conducted on a self-fabricated slurry erosion test rig and the same was evaluated by weighing the cumulative mass loss (CML) of samples for every 30 min post erosion. From experimental analysis, it was found that the erosive wear was found to be minimum and the hardness reaches to maximum value after 24 h of the soaking period which could be attributed to the significant microstructural changes such as the transformation of γ-austenite phase into (δ-ferrite+α′-martensite) along with precipitation of numerous carbides after deep cryogenic treatments.

Description: Performance of MOF-derived micrometer porous Fe2O3 as the oxidizer in Zr-fuelled thermite is compared with commercial nano-sized Fe2O3 by characterizing thermal and combustion behavior of Fe2O3/Zr mixture via differential scanning calorimetry, optical emission measurement as well as composition and morphology analysis on condensed combustion products. Results show that thermal behaviors of Fe2O3/Zr with a slow heating rate have little difference regardless of the kind of Fe2O3. However, MOF-derived micrometer porous Fe2O3 show an obvious superiority in enhancing combustion of Fe2O3/Zr heated by a high rate. Combustion reactions of Fe2O3/Zr under high heating rates are probably rate-controlled by condensed reaction. The better performance of MOF-derived Fe2O3 is attributed to its larger contact area with Zr particle in that micrometer porous Fe2O3 particles are easily broken into primitive nano-sized particles, which effectively avoid the agglomeration of oxidizer. The MOF-derived Fe2O3 particles obtained at calcination temperature of 550 °C enable the best combustion performance of Fe2O3/Zr thermite. This should be because the crystallinity and porous structure of 550 °C-Fe2O3 are more favorable for the mass transfer process during high-rate combustion.

Description: Point vortex systems that include vortices with constant coordinate functions are largely unexplored, even though they have reasonable physical interpretations in the geophysical context. Here, we investigate the dynamical aspects of the restricted three-vortex problem when one of the point vortices is assumed to be fixed at a location in the plane. The motion of the passive tracer is explored from a rotating frame of reference within which the free vortex with non-zero circulation remains stationary. By using basic dynamical system theory, it is shown that the vortex motion is always bounded, and any configuration of the three vortices must go through at least one collinear state. The present analysis reveals that any non-relative equilibrium solution of the vortex system either has periodic inter-vortex distances or it will asymptotically converge to a relative equilibrium configuration. The initial conditions required for different types of motion are explained in detail by exploiting the Hamiltonian structure of the problem. The underlying effects of a fixed vortex on the motion of vortices are also explored.

Description: The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely ‘matching variants’ (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and Caenorhabditis elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease.

Description: In this study, a femtosecond laser with a repetition frequency of 0–400 kHz was used to join soda lime glass and 304 stainless steel. The effects of single-pulse power, repetition frequency, welding speed, and defocusing on the weld quality were investigated. The joining mechanism and fracture surface morphologies were studied using scanning electron microscopy and x-ray diffraction analysis. The results show that no new phases were formed between the glass and stainless steel, and that the joining mechanism consisted mainly of mechanical mixing between the two materials. Using a suitable combination of process parameters, a good weld with a strength of 8.79 MPa was obtained. The weld strength was influenced mainly by the amount of glass that adhered to the stainless steel, the bonding strength between the glass base material and the remelted glass, and the wetting of the stainless steel by the molten glass.

Description: Summary Eukaryotic gene expression requires coordination among hundreds of transcriptional regulators. To characterize a specific transcriptional regulator, identifying how it shares genomic-binding profiles with others can generate important insights into its action. As genomic data such as ChIP-Seq are being rapidly generated from individual labs, there is a demand for timely integration and analysis of these new data. We have developed an R package, GPSmatch (Genomic-binding Profile Similarity match), for calculating the Jaccard index to compare ChIP-Seq peaks from one experiment to the peaks of other ChIP-Seq experiments stored in a user-supplied customizable database. GPSmatch also evaluates the statistical significance of the calculated Jaccard index using a nonparametric Monte Carlo procedure. We show that GPSmatch is suitable for identifying transcriptional regulators that share similar genomic-binding profiles, which may unravel potential mechanistic actions of gene regulation. Availability The software is freely available at https://github.com/Bao-Lab/GPSmatch.

Description: Quantifying inter-specific variations of tree resilience to drought and revealing the underlying mechanisms are of great importance to the understanding of forest functionality particularly in water-limited regions. So far, comprehensive studies incorporating investigations in inter-specific variations of long-term growth patterns of trees and the underlying physiological mechanisms are very limited. Here, in a semi-arid site of northern China, tree radial growth rate, inter-annual tree-ring growth responses to climate variability, as well as physiological characteristics pertinent to xylem hydraulics, carbon assimilation and drought tolerance were analyzed in seven pine species growing in a common environment. Considerable inter-specific variations in radial growth rate, growth response to drought and physiological characteristics were observed among the studied species. Differently, the studied species exhibited similar degrees of resistance to drought-induced branch xylem embolism with water potential corresponding to 50% loss hydraulic conductivity ranged from −2.31 to −2.96 MPa. We found that higher branch hydraulic efficiency is related to greater leaf photosynthetic capacity, smaller hydraulic safety margin and lower woody density (P  0.05). Rather, species with higher hydraulic conductivity and photosynthetic capacity was more sensitive to drought stress and tended to show weaker growth resistance to extreme drought events as quantified by tree-ring analyses, which is at least partially due to a trade-off between hydraulic efficiency and safety across species. This study thus demonstrates the importance of drought resilience rather than instantaneous water and carbon flux capacity in determining tree growth in water-limited environments.

Description: The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb; www.guidetopharmacology.org) is an open-access, expert-curated database of molecular interactions between ligands and their targets. We describe expansion in content over nine database releases made during the last two years, which has focussed on three main areas of infection. The COVID-19 pandemic continues to have a major impact on health worldwide. GtoPdb has sought to support the wider research community to understand the pharmacology of emerging drug targets for SARS-CoV-2 as well as potential targets in the host to block viral entry and reduce the adverse effects of infection in patients with COVID-19. We describe how the database rapidly evolved to include a new family of Coronavirus proteins. Malaria remains a global threat to half the population of the world. Our database content continues to be enhanced through our collaboration with Medicines for Malaria Venture (MMV) on the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY (www.guidetomalariapharmacology.org). Antibiotic resistance is also a growing threat to global health. In response, we have extended our coverage of antibacterials in partnership with AntibioticDB.

Description: Motivation Discover is an algorithm developed to identify mutually exclusive genomic events. Its main contribution is a statistical analysis based on the Poisson-Binomial (PB) distribution to take into account the mutation rate of genes and samples. Discover is very effective for identifying mutually exclusive mutations at the expense of speed in large datasets: the Poisson-Binomial is computationally costly to estimate, and checking all the potential mutually exclusive alterations requires millions of tests. Results We have implemented a new version of the package called Rediscover that implements exact and approximate computations of the PB. Rediscover exact implementation is slightly faster than Discover for large and medium-sized datasets. The approximation is 100 to 1,000 times faster for them making it possible to get results in less than a minute with a standard desktop. The memory footprint is also smaller in Rediscover. The new package is available at CRAN and provides some functions to integrate its usage with other R packages such as maftools and TCGAbiolinks. Availability Rediscover is available at CRAN (https://cran.r-project.org/web/packages/Rediscover/index.html). Supplementary information Supplementary data are available at Bioinformatics online.

Description: The advantages of high entropy alloy with good comprehensive properties provide a potential opportunity to explore and develop new alloys suitable for human implantation. In this experiment, TiTaNbZrMo high entropy alloy was designed and prepared by alloy design and first principle. The calculation results predict that the phase composition of each high entropy alloy is BCC structure, and the designed high entropy alloy has structural stability; the non-equal atomic ratio TiNbTaZrMo high-entropy alloy has higher ductility than the equal atomic ratio TiNbTaZrMo high-entropy alloy; the B/G, Poisson’s ratio υ and (C 12-C 44) values of Ti30(NbTaZr)60Mo10 alloy are the largest, indicating that the toughness of this alloy is the best, and the Young’s modulus value is the smallest. The experimental results show that the yield strength of Ti30(NbTaZr)60Mo10 alloy is 1132 MPa, the plastic strain is 33%, and the wear resistance and corrosion resistance are good. The potential of Ti30(NbTaZr)60Mo10 in biological field is proved by calculation and experimental test, which provides an important basis for its industrial application in biomedical alloy.

Description: Reactive oxygen species (ROS) generate oxidized bases and single-strand breaks (SSBs), which are fixed by base excision repair (BER) and SSB repair (SSBR), respectively. Although excision and repair of damaged bases have been extensively studied, the function of the sliding clamp, proliferating cell nuclear antigen (PCNA), including loading/unloading, remains unclear. We report that, in addition to PCNA loading by replication factor complex C (RFC), timely PCNA unloading by the ATPase family AAA domain-containing protein 5 (ATAD5)-RFC–like complex is important for the repair of ROS-induced SSBs. We found that PCNA was loaded at hydrogen peroxide (H2O2)-generated direct SSBs after the 3′-terminus was converted to the hydroxyl moiety by end-processing enzymes. However, PCNA loading rarely occurred during BER of oxidized or alkylated bases. ATAD5-depleted cells were sensitive to acute H2O2 treatment but not methyl methanesulfonate treatment. Unexpectedly, when PCNA remained on DNA as a result of ATAD5 depletion, H2O2-induced repair DNA synthesis increased in cancerous and normal cells. Based on higher H2O2-induced DNA breakage and SSBR protein enrichment by ATAD5 depletion, we propose that extended repair DNA synthesis increases the likelihood of DNA polymerase stalling, shown by increased PCNA monoubiquitination, and consequently, harmful nick structures are more frequent.

Description: Summary Whole genome assembly (WGA) of bacterial genomes with short reads is a quite common task as DNA sequencing has become cheaper with the advances of its technology. The process of assembling a genome has no absolute golden standard and it requires to perform a sequence of steps each of which can involve combinations of many different tools. However, the quality of the final assembly is always strongly related to the quality of the input data. With this in mind we built WGA-LP, a package that connects state-of-the-art programs for microbial analysis and novel scripts to check and improve the quality of both samples and resulting assemblies. WGA-LP, with its conservative decontamination approach, has shown to be capable of creating high quality assemblies even in the case of contaminated reads. Availability and implementation WGA-LP is available on GitHub (https://github.com/redsnic/WGA-LP) and Docker Hub (https://hub.docker.com/r/redsnic/wgalp). The web app for node visualization is hosted by shinyapps.io (https://redsnic.shinyapps.io/ContigCoverageVisualizer/). Supplementary information Supplementary data are available at Bioinformatics online.

Description: Eukaryotic genome and methylome encode DNA fragments’ propensity to form nucleosome particles. Although the mechanical properties of DNA possibly orchestrate such encoding, the definite link between ‘omics’ and DNA energetics has remained elusive. Here, we bridge the divide by examining the sequence-dependent energetics of highly bent DNA. Molecular dynamics simulations of 42 intact DNA minicircles reveal that each DNA minicircle undergoes inside-out conformational transitions with the most likely configuration uniquely prescribed by the nucleotide sequence and methylation of DNA. The minicircles’ local geometry consists of straight segments connected by sharp bends compressing the DNA’s inward-facing major groove. Such an uneven distribution of the bending stress favors minimum free energy configurations that avoid stiff base pair sequences at inward-facing major grooves. Analysis of the minicircles’ inside-out free energy landscapes yields a discrete worm-like chain model of bent DNA energetics that accurately account for its nucleotide sequence and methylation. Experimentally measuring the dependence of the DNA looping time on the DNA sequence validates the model. When applied to a nucleosome-like DNA configuration, the model quantitatively reproduces yeast and human genomes’ nucleosome occupancy. Further analyses of the genome-wide chromatin structure data suggest that DNA bending energetics is a fundamental determinant of genome architecture.

Description: Mo/alumina cermet-based selective coatings are of great interest for concentrated solar-thermal power systems, in particular, parabolic trough collectors. We report on the sputter deposition of high-performance multilayer Mo/alumina cermet coatings on stainless steel with a solar absorptance of 94% and a thermal emittance of 8% (at 400 °C), and excellent thermal stability. The selective coatings were deposited in a 0.95 m3 sputtering chamber in order to correlate the deposition parameters, such as presence of residual gases, deposition power, and sputtering method (DC or RF), with the coating composition and the resulting optical properties. X-ray photoelectron spectroscopy, x-ray diffraction, and Raman spectroscopy have been applied to quantitatively describe the effect of residual oxygen on the distribution of oxidation states of Mo in the metallic infrared reflector layer, the high and low metallic volume fraction cermet layers, as well as the composition of the alumina top layer. The results provide strategies to obtain optimal selective coatings under conditions where residual oxygen cannot be avoided, which are essential for a successful transition from a laboratory to pre-industrial scale of vacuum deposition systems.

Description: This paper presents the effect of the variations of multi-walled carbon nanotube (MWCNT) modification in shape memory polymer hybrid composites concerning their mechanical, thermomechanical, and shape memory characterizations. The process of fabrication includes preparation of the MWCNT/epoxy hybrid nanocomposites by shear mixing, ultrasonication, magnetic stirring, and subsequent molding by hand layup method. The appropriate post-processing was performed for the curing and cutting to prepare the samples for the mechanical and thermomechanical characterizations as per the ASTM standards. An enhancement in the thermomechanical properties was noticed due to the incorporation of the MWCNT. These observations were also validated with improvement in the interfacial bonding between the carbon fiber and the modified matrix, as shown in the morphological fractography. The tensile strengths were improved by 18%, 39%, and 26% with the incorporation of 0.4%, 0.6%, and 0.8% modified MWCNT nanocomposites as compared to pure unmodified SMPC. However, the shape recovery of all the configurations of the shape memory polymer hybrid composites was not compromised on polymer-modified remaining almost unchanged at 94%.

Description: Kilovoltage cone-beam computed tomography (CBCT)-based image-guided radiation therapy (IGRT) is used for daily delivery of radiation therapy, especially for stereotactic body radiation therapy (SBRT), which imposes particularly high demands for setup accuracy. The clinical applications of CBCTs are constrained, however, by poor soft tissue contrast, image artifacts, and instability of Hounsfield unit (HU) values. Here, we propose a new deep learning-based method to generate synthetic CTs (sCT) from thoracic CBCTs. A deep-learning model which integrates histogram matching (HM) into a cycle-consistent adversarial network (Cycle-GAN) framework, called HM-Cycle-GAN, was trained to learn mapping between thoracic CBCTs and paired planning CTs. Perceptual supervision was adopted to minimize blurring of tissue interfaces. An informative maximizing loss was calculated by feeding CBCT into the HM-Cycle-GAN to evaluate the image histogram matching between the planning CTs and the sCTs. The proposed algorithm was evaluated using data from 20 SBRT patients who each received 5 fractions and therefore 5 thoracic CBCTs. To reduce the effect of anatomy mismatch, original CBCT images were pre-processed via deformable image registrations with the planning CT before being used in model training and result assessment. We used planning CTs as ground truth for the derived sCTs from the correspondent co-registered CBCTs. The mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and normalized cross-correlation (NCC) indices were adapted as evaluation metrics of the proposed algorithm. Assessments were done using Cycle-GAN as the benchmark. The average MAE, PSNR, and NCC of the sCTs generated by our method were 66.2 HU, 30.3 dB, and 0.95, respectively, over all CBCT fractions. Superior image quality and reduced noise and artifact severity were seen using the proposed method compared to the results from the standard Cycle-GAN method. Our method could therefore improve the accuracy of IGRT and corrected CBCTs could help improve online adaptive RT by offering better contouring accuracy and dose calculation.

Description: Mitigating bycatch of non-target fish species is a common objective in fisheries management that may be supported by the gathering of data from fishery observer programs and quantitative analysis of bycatch risk factors. We build three GLM models based on Chinese tuna longline fishery observer data in terms of analysis of total bycatch rate (TB rate), total bycatch ratio (TB ratio), and species-specific bycatch rate, respectively. The positive log-linear models assumed a Gaussian observation error model and a linear combination of categorical independent variables, including area, year, month, depth, and bycatch species. Results show that distributions of TB rate and TB ratio followed different trends and a latitudinal decrease was observed from both the northern and southern hemisphere of the equator. Comprehensively, the Pacific is a better place to fish compared to the Indian and Atlantic Oceans in terms of relatively lower TB rate and TB ratio. Fishing in open oceans can somehow avoid a high TB ratio than fishing in coastal waters. As a result, we recommend area 2SW, 2SE, 2 NW, 14SW, 14SE, and 14 NW as appropriate fishing ground for Albacore (Thunnus alalunga) while area 11N,  11S, 18SW, and 18SE to be appropriate fishing ground for fishing bigeye tuna (Thunnus obesus). Setting fishing gears deeper than 500 m would also help to get a low TB rate and TB ratio.

Description: Cellulose is the most abundant biological compound on Earth and while it is the predominant building constituent of plants, it is also a key extracellular matrix component in many diverse bacterial species. While bacterial cellulose was first described in the 19th century, it was not until this last decade that a string of structural works provided insights into how the cellulose synthase BcsA, assisted by its inner-membrane partner BcsB, senses c-di-GMP to simultaneously polymerize its substrate and extrude the nascent polysaccharide across the inner bacterial membrane. It is now established that bacterial cellulose can be produced by several distinct types of cellulose secretion systems and that in addition to BcsAB, they can feature multiple accessory subunits, often indispensable for polysaccharide production. Importantly, the last years mark significant progress in our understanding not only of cellulose polymerization per se but also of the bigger picture of bacterial signaling, secretion system assembly, biofilm formation and host tissue colonization, as well as of structural and functional parallels of this dominant biosynthetic process between the bacterial and eukaryotic domains of life. Here, we review current mechanistic knowledge on bacterial cellulose secretion with focus on the structure, assembly and cooperativity of Bcs secretion system components.

Description: A first principles study, was performed for a 2D, three atom thick monolayer of the Transition Metal Dichalcogenide (TMD) alloy Mo(S1-XTeX)2 adsorbed on an Al-terminated (0001)-sapphire surface. Bulk composition dependent binding energies and band-gaps, and a partial phase diagram, were calculated, using the cluster expansion method. Although the 3D Mo(S1-XTeX)2 alloy system has a phase diagram that is dominated by S-rich/Te-rich phase separation, the 2D system adsorbed on sapphire is dominated by S:Te-ordering. Five ground-state phases are predicted; all have P1 symmetry, and all disorder via contiuous (2’nd order) transitions. These results indicate that synthesis on the sapphire substrate is favorable for band-gap engineering, in which a continuous single phase solid solution allows continuous band-gap tuning, as a function of bulk composition. Whereas, bulk TMD-synthesis followed by exfoliation favors the formation of two-phase mixtures.

Description: In order to meet the requirements of future national defense for high temperature electromagnetic (EM) absorbing performance, a series of FexCo30Ni60−xSi5Al5 (x = 30, 35, 40, 45) high-entropy alloys (HEAs) powders was prepared and their Curie temperatures (TC) were measured by a self-made Wheatstone bridge. According to the results, varying the Fe/Ni ratio affected the crystal structure, Curie temperature, oxidation resistance, and electromagnetic absorbing properties of the above compounds. Since Fe has a BCC structure and is thus easier to form the solid solutions with Si and Al, the crystal structure of the alloy has changed from FCC toward BCC with increasing Fe dopant content. In turn, the Curie temperature (TC) decreased from 473.68 °C to 358.07 °C, being lower than their initial oxidation temperature (〉800 °C). The reflection losses (RL) of powders at room temperature and high temperatures (≤500 °C) were calculated as well. It was found that the flake powders after ball milling gained a larger aspect ratio, resulting in the better absorption effect, which was due to high toughness and low strength characteristics of the initial FCC structure. Furthermore, the permittivity and permeability of alloys upon heating reached impedance matching at a certain temperature, thus achieving the greater RLmax value. Finally, the high-temperature EM absorption characteristics of HEAs were shown to merit a thorough study.

Description: Prior and extensive plastic rewiring of a transcriptional network, followed by a functional switch of the conserved transcriptional regulator, can shape the evolution of a new network with diverged functions. The presence of three distinct iron regulatory systems in fungi that use orthologous transcriptional regulators suggests that these systems evolved in that manner. Orthologs of the transcriptional activator Sef1 are believed to be central to how iron regulatory systems developed in fungi, involving gene gain, plastic network rewiring, and switches in regulatory function. We show that, in the protoploid yeast Lachancea kluyveri, plastic rewiring of the L. kluyveri Sef1 (Lk-Sef1) network, together with a functional switch, enabled Lk-Sef1 to regulate TCA cycle genes, unlike Candida albicans Sef1 that mainly regulates iron-uptake genes. Moreover, we observed pervasive nonfunctional binding of Sef1 to its target genes. Enhancing Lk-Sef1 activity resuscitated the corresponding transcriptional network, providing immediate adaptive benefits in changing environments. Our study not only sheds light on the evolution of Sef1-centered transcriptional networks but also shows the adaptive potential of nonfunctional transcription factor binding for evolving phenotypic novelty and diversity.

Description: Although the investigation of the epigenome becomes increasingly important, still little is known about the long-term evolution of epigenetic marks and systematic investigation strategies are still lacking. Here, we systematically demonstrate the transfer of classic phylogenetic methods such as maximum likelihood based on substitution models, parsimony, and distance-based to interval-scaled epigenetic data. Using a great apes blood data set, we demonstrate that DNA methylation is evolutionarily conserved at the level of individual CpGs in promotors, enhancers, and genic regions. Our analysis also reveals that this epigenomic conservation is significantly correlated with its transcription factor binding density. Binding sites for transcription factors involved in neuron differentiation and components of AP-1 evolve at a significantly higher rate at methylation than at the nucleotide level. Moreover, our models suggest an accelerated epigenomic evolution at binding sites of BRCA1, chromobox homolog protein 2, and factors of the polycomb repressor 2 complex in humans. For most genomic regions, the methylation-based reconstruction of phylogenetic trees is at par with sequence-based reconstruction. Most strikingly, phylogenetic reconstruction using methylation rates in enhancer regions was ineffective independently of the chosen model. We identify a set of phylogenetically uninformative CpG sites enriched in enhancers controlling immune-related genes.

Description: The dispersal of rice (Oryza sativa) following domestication influenced massive social and cultural changes across South, East, and Southeast (SE) Asia. The history of dispersal across islands of SE Asia, and the role of Taiwan and the Austronesian expansion in this process remain largely unresolved. Here, we reconstructed the routes of dispersal of O. sativa ssp. japonica rice to Taiwan and the northern Philippines using whole-genome resequencing of indigenous rice landraces coupled with archaeological and paleoclimate data. Our results indicate that japonica rice found in the northern Philippines diverged from Indonesian landraces as early as 3,500 years before present (BP). In contrast, rice cultivated by the indigenous peoples of the Taiwanese mountains has complex origins. It comprises two distinct populations, each best explained as a result of admixture between temperate japonica that presumably came from northeast Asia, and tropical japonica from the northern Philippines and mainland SE Asia, respectively. We find that the temperate japonica component of these indigenous Taiwan populations diverged from northeast Asia subpopulations at about 2,600 BP, whereas gene flow from the northern Philippines had begun before ∼1,300  BP. This coincides with a period of intensified trade established across the South China Sea. Finally, we find evidence for positive selection acting on distinct genomic regions in different rice subpopulations, indicating local adaptation associated with the spread of japonica rice.

Description: Motivation Immune cells are important components of the immune system and are crucial for disease initiation, progression, prognosis, and survival. Although several computational methods have been designed for predicting the abundance of immune cells, very few tools are applicable to mouse. Given that mouse is the most widely used animal model in biomedical research, there is an urgent need to develop a precise algorithm for predicting mouse immune cells. Results We developed a tool named ImmuCellAI-mouse (Immune Cell Abundance Identifier for mouse), for estimating the abundance of 36 immune cell (sub)types from gene expression data in a hierarchical strategy of three layers. Reference expression profile and robust marker gene sets of immune cell types were curated. The abundance of cells in three layers was predicted separately by calculating the ssGSEA enrichment score of the expression deviation profile per cell type. Benchmark results showed high accuracy of ImmuCellAI-mouse in predicting most immune cell types, with correlation coefficients between predicted value and real cell proportion of most cell types being larger than 0.8. We applied ImmuCellAI-mouse to a mouse breast tumor dataset and revealed the dynamic change of immune cell infiltration during treatment, which is consistent with the findings of the original study but with more details. We also constructed an online server for ImmuCellAI-mouse, on which users can upload expression matrices for analysis. ImmuCellAI-mouse will be a useful tool for studying the immune microenvironment, cancer immunology, and immunotherapy in mouse models, providing an indispensable supplement for human disease studies. Availability Software is available at http://bioinfo.life.hust.edu.cn/ImmuCellAI-mouse/ Supplementary information Supplementary data are available at Bioinformatics online.

Description: Understanding the tradeoffs faced by organisms is a major goal of evolutionary biology. One of the main approaches for identifying these tradeoffs is Pareto task inference (ParTI). Two recent papers claim that results obtained in ParTI studies are spurious due to phylogenetic dependence (Mikami T, Iwasaki W. 2021. The flipping t-ratio test: phylogenetically informed assessment of the Pareto theory for phenotypic evolution. Methods Ecol Evol. 12(4):696–706) or hypothetical p-hacking and population-structure concerns (Sun M, Zhang J. 2021. Rampant false detection of adaptive phenotypic optimization by ParTI-based Pareto front inference. Mol Biol Evol. 38(4):1653–1664). Here, we show that these claims are baseless. We present a new method to control for phylogenetic dependence, called SibSwap, and show that published ParTI inference is robust to phylogenetic dependence. We show how researchers avoided p-hacking by testing for the robustness of preprocessing choices. We also provide new methods to control for population structure and detail the experimental tests of ParTI in systems ranging from ammonites to cancer gene expression. The methods presented here may help to improve future ParTI studies.

Description: Establishing an RNA-associated interaction repository facilitates the system-level understanding of RNA functions. However, as these interactions are distributed throughout various resources, an essential prerequisite for effectively applying these data requires that they are deposited together and annotated with confidence scores. Hence, we have updated the RNA-associated interaction database RNAInter (RNA Interactome Database) to version 4.0, which is freely accessible at http://www.rnainter.org or http://www.rna-society.org/rnainter/. Compared with previous versions, the current RNAInter not only contains an enlarged data set, but also an updated confidence scoring system. The merits of this 4.0 version can be summarized in the following points: (i) a redefined confidence scoring system as achieved by integrating the trust of experimental evidence, the trust of the scientific community and the types of tissues/cells, (ii) a redesigned fully functional database that enables for a more rapid retrieval and browsing of interactions via an upgraded user-friendly interface and (iii) an update of entries to 〉47 million by manually mining the literature and integrating six database resources with evidence from experimental and computational sources. Overall, RNAInter will provide a more comprehensive and readily accessible RNA interactome platform to investigate the regulatory landscape of cellular RNAs.

Description: Motivation As one of the most important post-translational modifications (PTMs), protein lysine crotonylation (Kcr) has attracted wide attention, which involves in important physiological activities, such as cell differentiation and metabolism. However, experimental methods are expensive and time-consuming for Kcr identification. Instead, computational methods can predict Kcr sites in silico with high efficiency and low cost. Results In this study, we proposed a novel predictor, BERT-Kcr, for protein Kcr sites prediction, which was developed by using a transfer learning method with pre-trained bidirectional encoder representations from transformers (BERT) models. These models were originally used for natural language processing (NLP) tasks, such as sentence classification. Here, we transferred each amino acid into a word as the input information to the pre-trained BERT model. The features encoded by BERT were extracted and then fed to a BiLSTM network to build our final model. Compared with the models built by other machine learning and deep learning classifiers, BERT-Kcr achieved the best performance with AUROC of 0.983 for 10-fold cross-validation. Further evaluation on the independent test set indicates that BERT-Kcr outperforms the state-of-the-art model Deep-Kcr with an improvement of about 5% for AUROC. The results of our experiment indicate that the direct use of sequence information and advanced pre-trained models of natural language processing could be an effective way for identifying post-translational modification sites of proteins. Availability The BERT-Kcr model is publicly available on http://zhulab.org.cn/BERT-Kcr_models/. Supplementary information Supplementary data are available at Bioinformatics online.

Description: The state-space assessment model (SAM) is extended by allowing a functional relationship between observation variance and the corresponding prediction. An estimated relationship between observation variance and predicted value for each individual observation allows the model to assign smaller (or larger) variance to predicted larger log-observations. This relation is different from the usual assumption of constant variance of log-observations within age groups. The prediction–variance link is implemented and compared to the usual constant variance assumption for the official assessments of North East Arctic cod and haddock. For both of these stocks, the prediction–variance link is found to give a significant improvement.

Description: We evidence English teacher and student perspectives on the learning of pre-university mathematics ‘A Level’ courses through the pandemic period to July 2021. Data are drawn from a 2017–21 classroom-close study of enactment of such courses in 13 fairly representative centres, using an institutional ethnographic approach. The pandemic picture was generally one of the significant and sustained negative impacts, though over the course of the study, respondents reported progress in addressing early limitations in the harnessing of digital platforms for learning. A small number of participating students reported home-based study beneficial for their mathematics learning, and a bigger group identified some wider benefits that partly offset the challenges. Most participating 16–18-year-old students, though, reported finding remote learning of mathematics both demanding and limiting. Pandemic constraints impacted most strongly on opportunities to engage with newer emphases within A Level courses: problem solving, reasoning, modelling, statistics and mechanics. Receiving academics reported that mathematical preparedness, and confidence, for mathematics-intense university courses has also been widely affected, with a bigger range of preparedness and confidence than usual. The study draws attention to the importance of studying subject-specific impact and drawing on student as well as teacher perceptions. It exposes a range of consequences of the cancellation of examinations and a need to develop and share effective pedagogies for working remotely with pre-university students.

Description: Proteome-pI 2.0 is an update of an online database containing predicted isoelectric points and pKa dissociation constants of proteins and peptides. The isoelectric point—the pH at which a particular molecule carries no net electrical charge—is an important parameter for many analytical biochemistry and proteomics techniques. Additionally, it can be obtained directly from the pKa values of individual charged residues of the protein. The Proteome-pI 2.0 database includes data for over 61 million protein sequences from 20 115 proteomes (three to four times more than the previous release). The isoelectric point for proteins is predicted by 21 methods, whereas pKa values are inferred by one method. To facilitate bottom-up proteomics analysis, individual proteomes were digested in silico with the five most commonly used proteases (trypsin, chymotrypsin, trypsin + LysC, LysN, ArgC), and the peptides’ isoelectric point and molecular weights were calculated. The database enables the retrieval of virtual 2D-PAGE plots and customized fractions of a proteome based on the isoelectric point and molecular weight. In addition, isoelectric points for proteins in NCBI non-redundant (nr), UniProt, SwissProt, and Protein Data Bank are available in both CSV and FASTA formats. The database can be accessed at http://isoelectricpointdb2.org.

Description: As a crucial molecular mechanism, post-translational modifications (PTMs) play critical roles in a wide range of biological processes in plants. Recent advances in mass spectrometry-based proteomic technologies have greatly accelerated the profiling and quantification of plant PTM events. Although several databases have been constructed to store plant PTM data, a resource including more plant species and more PTM types with quantitative dynamics still remains to be developed. In this paper, we present an integrative database of quantitative PTMs in plants named qPTMplants (http://qptmplants.omicsbio.info), which hosts 1 242 365 experimentally identified PTM events for 429 821 nonredundant sites on 123 551 proteins under 583 conditions for 23 PTM types in 43 plant species from 293 published studies, with 620 509 quantification events for 136 700 PTM sites on 55 361 proteins under 354 conditions. Moreover, the experimental details, such as conditions, samples, instruments and methods, were manually curated, while a variety of annotations, including the sequence and structural characteristics, were integrated into qPTMplants. Then, various search and browse functions were implemented to access the qPTMplants data in a user-friendly manner. Overall, we anticipate that the qPTMplants database will be a valuable resource for further research on PTMs in plants.

Description: Large-scale multi-omics datasets, most prominently from the TCGA consortium, have been made available to the public for systematic characterization of human cancers. However, to date, there is a lack of corresponding online resources to utilize these valuable data to study gene expression dysregulation and viral infection, two major causes for cancer development and progression. To address these unmet needs, we established OncoDB, an online database resource to explore abnormal patterns in gene expression as well as viral infection that are correlated to clinical features in cancer. Specifically, OncoDB integrated RNA-seq, DNA methylation, and related clinical data from over 10 000 cancer patients in the TCGA study as well as from normal tissues in the GTEx study. Another unique aspect of OncoDB is its focus on oncoviruses. By mining TCGA RNA-seq data, we have identified six major oncoviruses across cancer types and further correlated viral infection to changes in host gene expression and clinical outcomes. All the analysis results are integratively presented in OncoDB with a flexible web interface to search for data related to RNA expression, DNA methylation, viral infection, and clinical features of the cancer patients. OncoDB is freely accessible at http://oncodb.org.

Description: Summary We present several recent improvements to minimap2, a versatile pairwise aligner for nucleotide sequences. Now minimap2 v2.22 can more accurately map long reads to highly repetitive regions and align through insertions or deletions up to 100 kb by default, addressing major weakness in minimap2 v2.18 or earlier. Availability and implementation https://github.com/lh3/minimap2.

Description: Sequence compositions of nucleic acids and proteins have significant impact on gene expression, RNA stability, translation efficiency, RNA/protein structure and molecular function, and are associated with genome evolution and adaptation across all kingdoms of life. Therefore, a devoted resource of sequence compositions and associated features is fundamentally crucial for a wide range of biological research. Here, we present CompoDynamics (https://ngdc.cncb.ac.cn/compodynamics/), a comprehensive database of sequence compositions of coding sequences (CDSs) and genomes for all kinds of species. Taking advantage of the exponential growth of RefSeq data, CompoDynamics presents a wealth of sequence compositions (nucleotide content, codon usage, amino acid usage) and derived features (coding potential, physicochemical property and phase separation) for 118 689 747 high-quality CDSs and 34 562 genomes across 24 995 species. Additionally, interactive analytical tools are provided to enable comparative analyses of sequence compositions and molecular features across different species and gene groups. Collectively, CompoDynamics bears the great potential to better understand the underlying roles of sequence composition dynamics across genes and genomes, providing a fundamental resource in support of a broad spectrum of biological studies.

Description: Virus infections are huge threats to living organisms and cause many diseases, such as COVID-19 caused by SARS-CoV-2, which has led to millions of deaths. To develop effective strategies to control viral infection, we need to understand its molecular events in host cells. Virus related functional genomic datasets are growing rapidly, however, an integrative platform for systematically investigating host responses to viruses is missing. Here, we developed a user-friendly multi-omics portal of viral infection named as MVIP (https://mvip.whu.edu.cn/). We manually collected available high-throughput sequencing data under viral infection, and unified their detailed metadata including virus, host species, infection time, assay, and target, etc. We processed multi-layered omics data of more than 4900 viral infected samples from 77 viruses and 33 host species with standard pipelines, including RNA-seq, ChIP-seq, and CLIP-seq, etc. In addition, we integrated these genome-wide signals into customized genome browsers, and developed multiple dynamic charts to exhibit the information, such as time-course dynamic and differential gene expression profiles, alternative splicing changes and enriched GO/KEGG terms. Furthermore, we implemented several tools for efficiently mining the virus-host interactions by virus, host and genes. MVIP would help users to retrieve large-scale functional information and promote the understanding of virus-host interactions.

Description: mBodyMap is a curated database for microbes across the human body and their associations with health and diseases. Its primary aim is to promote the reusability of human-associated metagenomic data and assist with the identification of disease-associated microbes by consistently annotating the microbial contents of collected samples using state-of-the-art toolsets and manually curating the meta-data of corresponding human hosts. mBodyMap organizes collected samples based on their association with human diseases and body sites to enable cross-dataset integration and comparison. To help users find microbes of interest and visualize and compare their distributions and abundances/prevalence within different body sites and various diseases, the mBodyMap database is equipped with an intuitive interface and extensive graphical representations of the collected data. So far, it contains a total of 63 148 runs, including 14 401 metagenomes and 48 747 amplicons related to health and 56 human diseases, from within 22 human body sites across 136 projects. Also available in the database are pre-computed abundances and prevalence of 6247 species (belonging to 1645 genera) stratified by body sites and diseases. mBodyMap can be accessed at: https://mbodymap.microbiome.cloud.

Description: Long-term (2004–2020) studies showed yearly summer/autumn blooms in the NE Black Sea dominated by large (cell volume 〉 5000 μm3) diatoms (Pseudosolenia calcar-avis and Proboscia alata). This phenomenon is characterized by high (〉250 W m−2 photosynthetically active radiation, PAR) insolation, and low phosphorus concentrations (to analytical zero). These diatoms contained 〉100 chloroplasts per cell, which at low irradiance are evenly distributed throughout the cell. As light increases (to 1000 μmol photons m−2 s−1 PAR), chloroplasts aggregate within 20 min, usually to the center of the cell. In consequence, the light absorption coefficient is decreased by 〉3 fold. At elevated photon flux density (PFD), P. calcar-avis also shows a “conveyor” of chloroplasts moving from the aggregate to the cell periphery and back. This mechanism enables a continuous fine-tuning of the cells’ ability to absorb light, likely also facilitating photo-damage repair. This rapid photoacclimation mechanism allows large diatoms to minimize photodamage at high PFD and acclimate well to low PFD. We hypothesize that competitive success of large diatoms in conditions of high light gradients is aided by this short-term rapid photoacclimation enhancing growth rate while minimizing chloroplast repair costs, aided by the ability of large cells to accumulate nutrients for chloroplast synthesis.

Description: Motivation Deep learning approaches have empowered single-cell omics data analysis in many ways and generated new insights from complex cellular systems. As there is an increasing need for single cell omics data to be integrated across sources, types, and features of data, the challenges of integrating single-cell omics data are rising. Here, we present an unsupervised deep learning algorithm that learns discriminative representations for single-cell data via maximizing mutual information, SMILE (Single-cell Mutual Information Learning). Results Using a unique cell-pairing design, SMILE successfully integrates multi-source single-cell transcriptome data, removing batch effects and projecting similar cell types, even from different tissues, into the shared space. SMILE can also integrate data from two or more modalities, such as joint profiling technologies using single-cell ATAC-seq, RNA-seq, DNA methylation, Hi-C, and ChIP data. When paired cells are known, SMILE can integrate data with unmatched feature, such as genes for RNA-seq and genome wide peaks for ATAC-seq. Integrated representations learned from joint profiling technologies can then be used as a framework for comparing independent single source data. Supplementary information Supplementary data are available at Bioinformatics online. The source code of SMILE including analyses of key results in the study can be found at: https://github.com/rpmccordlab/SMILE.

Description: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

Description: Liquid-liquid phase separation (LLPS) partitions cellular contents, underlies the formation of membraneless organelles and plays essential biological roles. To date, most of the research on LLPS has focused on proteins, especially RNA-binding proteins. However, accumulating evidence has demonstrated that RNAs can also function as ‘scaffolds’ and play essential roles in seeding or nucleating the formation of granules. To better utilize the knowledge dispersed in published literature, we here introduce RNAPhaSep (http://www.rnaphasep.cn), a manually curated database of RNAs undergoing LLPS. It contains 1113 entries with experimentally validated RNA self-assembly or RNA and protein co-involved phase separation events. RNAPhaSep contains various types of information, including RNA information, protein information, phase separation experiment information and integrated annotation from multiple databases. RNAPhaSep provides a valuable resource for exploring the relationship between RNA properties and phase behaviour, and may further enhance our comprehensive understanding of LLPS in cellular functions and human diseases.

Description: Liquid–liquid phase separation (LLPS) is critical for assembling membraneless organelles (MLOs) such as nucleoli, P-bodies, and stress granules, which are involved in various physiological processes and pathological conditions. While the critical role of RNA in the formation and the maintenance of MLOs is increasingly appreciated, there is still a lack of specific resources for LLPS-related RNAs. Here, we presented RPS (http://rps.renlab.org), a comprehensive database of LLPS-related RNAs in 20 distinct biomolecular condensates from eukaryotes and viruses. Currently, RPS contains 21,613 LLPS-related RNAs with three different evidence types, including ‘Reviewed’, ‘High-throughput’ and ‘Predicted’. RPS provides extensive annotations of LLPS-associated RNA properties, including sequence features, RNA structures, RNA–protein/RNA–RNA interactions, and RNA modifications. Moreover, RPS also provides comprehensive disease annotations to help users to explore the relationship between LLPS and disease. The user-friendly web interface of RPS allows users to access the data efficiently. In summary, we believe that RPS will serve as a valuable platform to study the role of RNA in LLPS and further improve our understanding of the biological functions of LLPS.

Description: The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the ‘Support’ link.

Description: Drug discovery relies on the knowledge of not only drugs and targets, but also the comparative agents and targets. These include poor binders and non-binders for developing discovery tools, prodrugs for improved therapeutics, co-targets of therapeutic targets for multi-target strategies and off-target investigations, and the collective structure-activity and drug-likeness landscapes of enhanced drug feature. However, such valuable data are inadequately covered by the available databases. In this study, a major update of the Therapeutic Target Database, previously featured in NAR, was therefore introduced. This update includes (a) 34 861 poor binders and 12 683 non-binders of 1308 targets; (b) 534 prodrug-drug pairs for 121 targets; (c) 1127 co-targets of 672 targets regulated by 642 approved and 624 clinical trial drugs; (d) the collective structure-activity landscapes of 427 262 active agents of 1565 targets; (e) the profiles of drug-like properties of 33 598 agents of 1102 targets. Moreover, a variety of additional data and function are provided, which include the cross-links to the target structure in PDB and AlphaFold, 159 and 1658 newly emerged targets and drugs, and the advanced search function for multi-entry target sequences or drug structures. The database is accessible without login requirement at: https://idrblab.org/ttd/.

Description: Motivation Identifying proteins that interact with drugs plays an important role in the initial period of developing drugs, which helps to reduce the development cost and time. Recent methods for predicting drug–protein interactions mainly focus on exploiting various data about drugs and proteins. These methods failed to completely learn and integrate the attribute information of a pair of drug and protein nodes and their attribute distribution. Results We present a new prediction method, GVDTI, to encode multiple pairwise representations, including attention-enhanced topological representation, attribute representation and attribute distribution. First, a framework based on graph convolutional autoencoder is constructed to learn attention-enhanced topological embedding that integrates the topology structure of a drug–protein network for each drug and protein nodes. The topological embeddings of each drug and each protein are then combined and fused by multi-layer convolution neural networks to obtain the pairwise topological representation, which reveals the hidden topological relationships between drug and protein nodes. The proposed attribute-wise attention mechanism learns and adjusts the importance of individual attribute in each topological embedding of drug and protein nodes. Secondly, a tri-layer heterogeneous network composed of drug, protein and disease nodes is created to associate the similarities, interactions and associations across the heterogeneous nodes. The attribute distribution of the drug–protein node pair is encoded by a variational autoencoder. The pairwise attribute representation is learned via a multi-layer convolutional neural network to deeply integrate the attributes of drug and protein nodes. Finally, the three pairwise representations are fused by convolutional and fully connected neural networks for drug–protein interaction prediction. The experimental results show that GVDTI outperformed other seven state-of-the-art methods in comparison. The improved recall rates indicate that GVDTI retrieved more actual drug–protein interactions in the top ranked candidates than conventional methods. Case studies on five drugs further confirm GVDTI’s ability in discovering the potential candidate drug-related proteins. Contact zhang@hlju.edu.cn  Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.

Description: Friedreich’s ataxia (FRDA) is a severe multisystem disease caused by transcriptional repression induced by expanded GAA repeats located in intron 1 of the Frataxin (FXN) gene encoding frataxin. FRDA results from decreased levels of frataxin; thus, stabilization of the FXN mRNA already present in patient cells represents an attractive and unexplored therapeutic avenue. In this work, we pursued a novel approach based on oligonucleotide-mediated targeting of FXN mRNA ends to extend its half-life and availability as a template for translation. We demonstrated that oligonucleotides designed to bind to FXN 5′ or 3′ noncoding regions can increase FXN mRNA and protein levels. Simultaneous delivery of oligonucleotides targeting both ends increases efficacy of the treatment. The approach was confirmed in several FRDA fibroblast and induced pluripotent stem cell-derived neuronal progenitor lines. RNA sequencing and single-cell expression analyses confirmed oligonucleotide-mediated FXN mRNA upregulation. Mechanistically, a significant elongation of the FXN mRNA half-life without any changes in chromatin status at the FXN gene was observed upon treatment with end-targeting oligonucleotides, indicating that transcript stabilization is responsible for frataxin upregulation. These results identify a novel approach toward upregulation of steady-state mRNA levels via oligonucleotide-mediated end targeting that may be of significance to any condition resulting from transcription downregulation.

Description: Digital technologies displace labor from routine tasks, raising concerns that labor is racing against the machine. We develop an empirically tractable task-based framework to estimate the aggregate employment effects of routine-replacing technological change (RRTC), along with the labor and product demand channels through which this aggregate effect comes about, focusing on the role of inter-regional trade. While RRTC has indeed had strong displacement effects in Europe between 1999 and 2010, it has simultaneously created new jobs through increased product demand, resulting in net employment growth. However, the distribution of gains from technological progress matters for its job-creating potential.

Description: The UCSC Genome Browser, https://genome.ucsc.edu, is a graphical viewer for exploring genome annotations. The website provides integrated tools for visualizing, comparing, analyzing, and sharing both publicly available and user-generated genomic datasets. Data highlights this year include a collection of easily accessible public hub assemblies on new organisms, now featuring BLAT alignment and PCR capabilities, and new and updated clinical tracks (gnomAD, DECIPHER, CADD, REVEL). We introduced a new Track Sets feature and enhanced variant displays to aid in the interpretation of clinical data. We also added a tool to rapidly place new SARS-CoV-2 genomes in a global phylogenetic tree enabling researchers to view the context of emerging mutations in our SARS-CoV-2 Genome Browser. Other new software focuses on usability features, including more informative mouseover displays and new fonts.

Description: The inhibitor of DNA-binding 3 (ID3) is a transcriptional regulator that limits interaction of basic helix-loop-helix transcription factors with their target DNA sequences. We previously reported that ID3 loss is associated with mutational signatures linked to DNA repair defects. Here we demonstrate that ID3 exhibits a dual role to promote DNA double-strand break (DSB) repair, particularly homologous recombination (HR). ID3 interacts with the MRN complex and RECQL helicase to activate DSB repair and it facilitates RAD51 loading and downstream steps of HR. In addition, ID3 promotes the expression of HR genes in response to ionizing radiation by regulating both chromatin accessibility and activity of the transcription factor E2F1. Consistently, analyses of TCGA cancer patient data demonstrate that low ID3 expression is associated with impaired HR. The loss of ID3 leads to sensitivity of tumor cells to PARP inhibition, offering new therapeutic opportunities in ID3-deficient tumors.

Description: Motivation Deciphering nucleosome–nucleosome interactions is an important step toward mesoscale description of chromatin organization but computational tools to perform such analyses are not publicly available. Results We developed iNucs, a user-friendly and efficient Python-based bioinformatics tool to compute and visualize nucleosome-resolved interactions using standard pairs format input generated from pairtools. Availabilityand implementation https://github.com/Karimi-Lab/inucs/. Supplementary information Supplementary data are available at Bioinformatics online.

Description: Motivation Over the past decades, vast amounts of genome sequencing data have been produced, requiring an enormous level of storage capacity. The time and resources needed to store and transfer such data cause bottlenecks in genome sequencing analysis. To resolve this issue, various compression techniques have been proposed to reduce the size of original FASTQ raw sequencing data, but these remain suboptimal. Long-read sequencing has become dominant in genomics, whereas most existing compression methods focus on short-read sequencing only. Results We designed a compression algorithm based on read reordering using a novel scoring model for reducing FASTQ file size with no information loss. We integrated all data processing steps into a software package called FastqCLS and provided it as a Docker image for ease of installation and execution to help users easily install and run. We compared our method with existing major FASTQ compression tools using benchmark datasets. We also included new long-read sequencing data in this validation. As a result, FastqCLS outperformed in terms of compression ratios for storing long-read sequencing data. Availability and implementation FastqCLS can be downloaded from https://github.com/krlucete/FastqCLS. Supplementary information Supplementary data are available at Bioinformatics online.

Description: The bacterial metadatabase BacDive (https://bacdive.dsmz.de) has developed into a leading database for standardized prokaryotic data on strain level. With its current release (07/2021) the database offers information for 82 892 bacterial and archaeal strains covering taxonomy, morphology, cultivation, metabolism, origin, and sequence information within 1048 data fields. By integrating high-quality data from additional culture collections as well as detailed information from species descriptions, the amount of data provided has increased by 30% over the past three years. A newly developed query builder tool in the advanced search now allows complex database queries. Thereby bacterial strains can be systematically searched based on combinations of their attributes, e.g. growth and metabolic features for biotechnological applications or to identify gaps in the present knowledge about bacteria. A new interactive dashboard provides a statistic overview over the most important data fields. Additional new features are improved genomic sequence data, integrated NCBI TaxIDs and links to BacMedia, the new sister database on cultivation media. To improve the findability and interpretation of data through search engines, data in BacDive are annotated with bioschemas.org terms.

Description: PhylomeDB is a unique knowledge base providing public access to minable and browsable catalogues of pre-computed genome-wide collections of annotated sequences, alignments and phylogenies (i.e. phylomes) of homologous genes, as well as to their corresponding phylogeny-based orthology and paralogy relationships. In addition, PhylomeDB trees and alignments can be downloaded for further processing to detect and date gene duplication events, infer past events of inter-species hybridization and horizontal gene transfer, as well as to uncover footprints of selection, introgression, gene conversion, or other relevant evolutionary processes in the genes and organisms of interest. Here, we describe the latest evolution of PhylomeDB (version 5). This new version includes a newly implemented web interface and several new functionalities such as optimized searching procedures, the possibility to create user-defined phylome collections, and a fully redesigned data structure. This release also represents a significant core data expansion, with the database providing access to 534 phylomes, comprising over 8 million trees, and homology relationships for genes in over 6000 species. This makes PhylomeDB the largest and most comprehensive public repository of gene phylogenies. PhylomeDB is available at http://www.phylomedb.org.

Description: Non-canonical forms of nucleic acids represent challenging objects for both structure-determination and investigation of their potential role in living systems. In this work, we uncover a structure adopted by GA repetition locked in a parallel homoduplex by an i-motif. A series of DNA oligonucleotides comprising GAGA segment and C3 clip is analyzed by NMR and CD spectroscopies to understand the sequence–structure–stability relationships. We demonstrate how the relative position of the homopurine GAGA segment and the C3 clip as well as single-base mutations (guanine deamination and cytosine methylation) affect base pairing arrangement of purines, i-motif topology and overall stability. We focus on oligonucleotides C3GAGA and methylated GAGAC3 exhibiting the highest stability and structural uniformity which allowed determination of high-resolution structures further analyzed by unbiased molecular dynamics simulation. We describe sequence-specific supramolecular interactions on the junction between homoduplex and i-motif blocks that contribute to the overall stability of the structures. The results show that the distinct structural motifs can not only coexist in the tight neighborhood within the same molecule but even mutually support their formation. Our findings are expected to have general validity and could serve as guides in future structure and stability investigations of nucleic acids.

Description: Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.

Description: Marine predatory fish face unpredictable prey environments, ranging from abundance to scarcity of food. Dimensioning their assimilative system to accommodate gorging and fasting is therefore a central life history choice. Assimilative capacity experiments typically operate with sustained feeding to satiation, and therefore ignore the fluctuations in natural feeding opportunities. A more relevant description of the adaptive response is the episodic capacity associated with binge feeding (hyperphagia). We develop the theoretical foundation to define episodic and sustained capacity and its allometry. Extensive empirical evidence on marine piscivorous fish at higher latitudes confirms that the episodic capacity scales almost linearly with predator body mass (exponent approximately 0.95), producing an increasing factorial hyperphagic scope (exponent approximately 0.20). Our synthesis overturns the reigning steady state perspective on assimilative capacity. The fish can utilize an episodic capacity, typically twice the size of the sustained capacity, resulting in local dynamics of functional responses with profound implications for scaling-up to ecosystem level.

Description: Pseudomonas aeruginosa possesses one of the most complex bacterial regulatory networks, which largely contributes to its success as a pathogen. However, most of its transcription factors (TFs) are still uncharacterized and the potential intra-species variability in regulatory networks has been mostly ignored so far. Here, we used DAP-seq to map the genome-wide binding sites of all 55 DNA-binding two-component systems (TCSs) response regulators (RRs) across the three major P. aeruginosa lineages. The resulting networks encompass about 40% of all genes in each strain and contain numerous new regulatory interactions across most major physiological processes. Strikingly, about half of the detected targets are specific to only one or two strains, revealing a previously unknown large functional diversity of TFs within a single species. Three main mechanisms were found to drive this diversity, including differences in accessory genome content, as exemplified by the strain-specific plasmid in IHMA87 outlier strain which harbors numerous binding sites of conserved chromosomally-encoded RRs. Additionally, most RRs display potential auto-regulation or RR-RR cross-regulation, bringing to light the vast complexity of this network. Overall, we provide the first complete delineation of the TCSs regulatory network in P. aeruginosa that will represent an important resource for future studies on this pathogen.

Description: The human pseudouridine synthase PUS7 is a versatile RNA modification enzyme targeting many RNAs thereby playing a critical role in development and brain function. Whereas all target RNAs of PUS7 share a consensus sequence, additional recognition elements are likely required, and the structural basis for RNA binding by PUS7 is unknown. Here, we characterize the structure–function relationship of human PUS7 reporting its X-ray crystal structure at 2.26 Å resolution. Compared to its bacterial homolog, human PUS7 possesses two additional subdomains, and structural modeling studies suggest that these subdomains contribute to tRNA recognition through increased interactions along the tRNA substrate. Consistent with our modeling, we find that all structural elements of tRNA are required for productive interaction with PUS7 as the consensus sequence of target RNA alone is not sufficient for pseudouridylation by human PUS7. Moreover, PUS7 binds several, non-modifiable RNAs with medium affinity which likely enables PUS7 to screen for productive RNA substrates. Following tRNA modification, the product tRNA has a significantly lower affinity for PUS7 facilitating its dissociation. Taken together our studies suggest a combination of structure-specific and sequence-specific RNA recognition by PUS7 and provide mechanistic insight into its function.

Description: Ecological interactions among marine zooplankton are poorly described because conventional sampling gears, such as plankton nets and traps, obscure the physical and biological environment that individuals experience. With in situ imagery, however, it is possible to resolve these interactions and potentially convert snapshot distributions into process-oriented oceanographic and ecological understanding. We describe a variety of imagery-detected ecological interactions with high spatial resolution in the northern Gulf of Mexico shelf waters (20–35 m bottom depth), providing new evidence of parasitism, predation, and life stage spatial structuring for different zooplankton groups. Chaetognaths were infected with an anteriorly attached, parasitic polychaete (1.1% of 33 824 individuals), and these infected chaetognaths were more common further offshore, south of a nearshore patch where unparasitized individuals reached concentrations of ∼90 m–3. Predation by Liriope spp. hydromedusae tended to occur in the shallowest 10–15 m, and doliolids formed distinct patches of different life stages, indicating that the environment is replete with sharp transitions among various ecological processes. Similar patterns in other marine ecosystems likely exist, and we encourage hybrid (machine/human expertise) approaches that broaden the scope for analysis of plankton images, which are rich sources of new ecological information and hypotheses yet to be examined quantitatively.

Description: Microbes living in plant tissues—endophytes—are mainly studied in crop plants where they typically colonize the root apoplast. Trees—a large carbon source with a high capacity for photosynthesis—provide a variety of niches for endophytic colonization. We have earlier identified a new type of plant–endophyte interaction in buds of adult Scots pine, where Methylorubrum species live inside the meristematic cells. The endosymbiont Methylorubrum extorquens DSM13060 significantly increases needle and root growth of pine seedlings without producing plant hormones, but by aggregating around host nuclei. Here, we studied gene expression and metabolites of the pine host induced by M. extorquens DSM13060 infection. Malic acid was produced by pine to potentially boost M. extorquens colonization and interaction. Based on gene expression, the endosymbiont activated the auxin- and ethylene (ET)-associated hormonal pathways through induction of CUL1 and HYL1, and suppressed salicylic and abscisic acid signaling of pine. Infection by the endosymbiont had an effect on pine meristem and leaf development through activation of GLP1-7 and ALE2, and suppressed flowering, root hair and lateral root formation by downregulation of AGL8, plantacyanin, GASA7, COW1 and RALFL34. Despite of systemic infection of pine seedlings by the endosymbiont, the pine genes CUL1, ETR2, ERF3, HYL, GLP1-7 and CYP71 were highly expressed in the shoot apical meristem, rarely in needles and not in stem or root tissues. Low expression of MERI5, CLH2, EULS3 and high quantities of ononitol suggest that endosymbiont promotes viability and protects pine seedlings against abiotic stress. Our results indicate that the endosymbiont positively affects host development and stress tolerance through mechanisms previously unknown for endophytic bacteria, manipulation of plant hormone signaling pathways, downregulation of senescence and cell death-associated genes and induction of ononitol biosynthesis.

Description: Translational errors during protein synthesis cause phenotypic mutations that are several orders of magnitude more frequent than DNA mutations. Such phenotypic mutations may affect adaptive evolution through their interactions with DNA mutations. To study how mistranslation may affect the adaptive evolution of evolving proteins, we evolved populations of green fluorescent protein (GFP) in either high-mistranslation or low-mistranslation Escherichia coli hosts. In both hosts, we first evolved GFP under purifying selection for the ancestral phenotype green fluorescence, and then under directional selection toward the new phenotype yellow fluorescence. High-mistranslation populations evolved modestly higher yellow fluorescence during each generation of evolution than low-mistranslation populations. We demonstrate by high-throughput sequencing that elevated mistranslation reduced the accumulation of deleterious DNA mutations under both purifying and directional selection. It did so by amplifying the fitness effects of deleterious DNA mutations through negative epistasis with phenotypic mutations. In contrast, mistranslation did not affect the incidence of beneficial mutations. Our findings show that phenotypic mutations interact epistatically with DNA mutations. By reducing a population’s mutation load, mistranslation can affect an important determinant of evolvability.

Description: In plants, miRNA production is orchestrated by a suite of proteins that control transcription of the pri-miRNA gene, post-transcriptional processing and nuclear export of the mature miRNA. Post-transcriptional processing of miRNAs is controlled by a pair of physically interacting proteins, hyponastic leaves 1 (HYL1) and Dicer-like 1 (DCL1). However, the evolutionary history and structural basis of the HYL1–DCL1 interaction is unknown. Here we use ancestral sequence reconstruction and functional characterization of ancestral HYL1 in vitro and in Arabidopsis thaliana to better understand the origin and evolution of the HYL1–DCL1 interaction and its impact on miRNA production and plant development. We found the ancestral plant HYL1 evolved high affinity for both double-stranded RNA (dsRNA) and its DCL1 partner before the divergence of mosses from seed plants (∼500 Ma), and these high-affinity interactions remained largely conserved throughout plant evolutionary history. Structural modeling and molecular binding experiments suggest that the second of two dsRNA-binding motifs (DSRMs) in HYL1 may interact tightly with the first of two C-terminal DCL1 DSRMs to mediate the HYL1–DCL1 physical interaction necessary for efficient miRNA production. Transgenic expression of the nearly 200 Ma-old ancestral flowering-plant HYL1 in A. thaliana was sufficient to rescue many key aspects of plant development disrupted by HYL1− knockout and restored near-native miRNA production, suggesting that the functional partnership of HYL1–DCL1 originated very early in and was strongly conserved throughout the evolutionary history of terrestrial plants. Overall, our results are consistent with a model in which miRNA-based gene regulation evolved as part of a conserved plant “developmental toolkit.”

Description: Reconstructing the histories of complex adaptations and identifying the evolutionary mechanisms underlying their origins are two of the primary goals of evolutionary biology. Taricha newts, which contain high concentrations of the deadly toxin tetrodotoxin (TTX) as an antipredator defense, have evolved resistance to self-intoxication, which is a complex adaptation requiring changes in six paralogs of the voltage-gated sodium channel (Nav) gene family, the physiological target of TTX. Here, we reconstruct the origins of TTX self-resistance by sequencing the entire Nav gene family in newts and related salamanders. We show that moderate TTX resistance evolved early in the salamander lineage in three of the six Nav paralogs, preceding the proposed appearance of tetrodotoxic newts by ∼100 My. TTX-bearing newts possess additional unique substitutions across the entire Nav gene family that provide physiological TTX resistance. These substitutions coincide with signatures of positive selection and relaxed purifying selection, as well as gene conversion events, that together likely facilitated their evolution. We also identify a novel exon duplication within Nav1.4 encoding an expressed TTX-binding site. Two resistance-conferring changes within newts appear to have spread via nonallelic gene conversion: in one case, one codon was copied between paralogs, and in the second, multiple substitutions were homogenized between the duplicate exons of Nav1.4. Our results demonstrate that gene conversion can accelerate the coordinated evolution of gene families in response to a common selection pressure.

Description: Historically it has been difficult to study the evolution of bacterial small RNAs (sRNAs) across distantly related species. For example, identifying homologs of sRNAs is often difficult in genomes that have undergone multiple structural rearrangements. Also, some types of regulatory sRNAs evolve at rapid rates. The high degree of genomic synteny among divergent host-restricted bacterial lineages, including intracellular symbionts, is conducive to sRNA maintenance and homolog identification. In turn, symbiont genomes can provide us with novel insights into sRNA evolution. Here, we examine the sRNA expression profile of the obligate symbiont of psyllids, Carsonella ruddii, which has one of the smallest cellular genomes described. Using RNA-seq, we identified 36 and 32 antisense sRNAs (asRNAs) expressed by Carsonella from the psyllids Bactericera cockerelli (Carsonella-BC) and Diaphorina citri (Carsonella-DC), respectively. The majority of these asRNAs were associated with genes that are involved in essential amino acid biosynthetic pathways. Eleven of the asRNAs were conserved in both Carsonella lineages and the majority were maintained by selection. Notably, five of the corresponding coding sequences are also the targets of conserved asRNAs in a distantly related insect symbiont, Buchnera. We detected differential expression of two asRNAs for genes involved in arginine and leucine biosynthesis occurring between two distinct Carsonella-BC life stages. Using asRNAs identified in Carsonella, Buchnera, and Profftella which are all endosymbionts, and Escherichia coli, we determined that regions upstream of these asRNAs encode unique conserved patterns of AT/GC richness, GC skew, and sequence motifs which may be involved in asRNA regulation.

Description: In this article, we make use of large-scale municipal border changes in Germany to provide the first evidence on the effect of local border changes on the distribution of activity in space. To allow for a comparison of economic activity within unique geographical units over time, we use geo-coded light data as well as local land-use data. Applying a difference-in-differences approach, we find evidence that municipalities absorbing their merger partners and hosting the new administrative center experience a significant increase in local activity, while the municipalities that are being absorbed and are losing the administrative center experience a decrease in such activity. The difference between the gains in activity from absorbing municipalities and the losses from absorbed ones is positive. These previously undocumented results point to the importance of distance to the administrative center as a determinant of the spatial distribution of economic activity.

Description: In higher plants, whole-genome duplication (WGD) is thought to facilitate the evolution of C4 photosynthesis from C3 photosynthesis. To understand this issue, we used new and existing leaf-development transcriptomes to construct two coding sequence databases for C4Gynandropsis gynandra and C3Tarenaya hassleriana, which shared a WGD before their divergence. We compared duplicated genes in the two species and found that the WGD contributed to four aspects of the evolution of C4 photosynthesis in G. gynandra. First, G. gynandra has retained the duplicates of ALAAT (alanine aminotransferase) and GOGAT (glutamine oxoglutarate aminotransferase) for nitrogen recycling to establish a photorespiratory CO2 pump in bundle sheath (BS) cells for increasing photosynthesis efficiency, suggesting that G. gynandra experienced a C3–C4 intermediate stage during the C4 evolution. Second, G. gynandra has retained almost all known vein-development-related paralogous genes derived from the WGD event, likely contributing to the high vein complexity of G. gynandra. Third, the WGD facilitated the evolution of C4 enzyme genes and their recruitment into the C4 pathway. Fourth, several genes encoding photosystem I proteins were derived from the WGD and are upregulated in G. gynandra, likely enabling the NADH dehydrogenase-like complex to produce extra ATPs for the C4 CO2 concentration mechanism. Thus, the WGD apparently played an enabler role in the evolution of C4 photosynthesis in G. gynandra. Importantly, an ALAAT duplicate became highly expressed in BS cells in G. gynandra, facilitating nitrogen recycling and transition to the C4 cycle. This study revealed how WDG may facilitate C4 photosynthesis evolution.