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Direct drive wave energy converters (DDWECs) have gradually become the mainstream of wave energy converters (WECs). In order to make better use of wave energy, energy storage devices and other renewable energy sources are often used to suppress power fluctuation in DDWECs. However, the addition of other energy sources will increase the complexity of the converter system and the number of power switches. Considering the flexibility of nine-switch converters (NSCs), this paper proposes a novel nine-switch grid-connected/off-grid multiport hybrid wave energy system (HWES). First, the system structure and modulation principle are described. Then, a model for a generator, a grid and energy storage are built, including a control strategy of each part. Finally, a simulation for the grid-connected/off-grid application and an experiment on the off-grid HWES are carried out. The results show that the multiport wave energy system can achieve the objective of stable and reliable power transmission by reducing power devices.

Resting blood pressure (BP) and heart rate (HR) levels are independent risk factors for cardiovascular diseases and mortality. Both phenotypes are critical for lifetime maintenance of the cardiovascular homeostasis and are under the influence of multiple factors. The estimated heritability for both phenotypes is high, but their main genetic determinants remain elusive. To address this shortcoming, we used a strategy to systematically identify genes affecting BP and HR regulation through high-throughput N-ethyl-N-Nitrosurea-induced germline mutagenesis. First, the random chemical-induced mutations were identified in founder animals by whole exome G1 progenitor sequencing and their zygosity established in G2/G3 mice before phenotypic assessment. We used the noninvasive tail cuff method to assess BP and HR in conscious G3 mice distributed in pedigrees of 30-100 G1 descendants. The quantitative traits were then analyzed with Linkage Analyzer in single or multiple combined pedigrees, detecting significant linkage between individual mutations and altered phenotypic scores in heterozygous or homozygous mice. Here, we report the initial results of BP and HR candidate genes selected during the screening of 45,261 G3 mice from 878 pedigrees, testing the effects of 45,317 variant alleles within 14,575 genes, in which 23 % of all autosomal genes were severely damaged. The data indicate that ENU mutagenesis effectively identified 85 candidate genes affecting BP and 132 HR levels, including only 13 and 18 genes previously known to influence BP and HR, respectively. Moreover, we validated the influence of three and seven new genes on BP and HR control through reverse genetics that may be associated with ageing, vascular integrity and cardiac development. These findings shed light on novel underlying mechanisms associated with both phenotypes and highlight sub-systems contributing to the genesis of critical risk factors associated with cardiovascular diseases.

Background Atopy, the overall tendency to become sensitized to an allergen, is heritable but seldom ascribed to mutations within specific genes. Atopic individuals develop abnormally elevated IgE responses to immunization with potential allergens. To gain insight into the genetic causes of atopy, we carried out a forward genetic screen for atopy in mice. Methods We screened mice carrying homozygous and heterozygous N-ethyl-N-nitrosourea (ENU)-induced germline mutations for aberrant antigen-specific IgE and IgG1 production in response to immunization with the model allergen papain. Candidate genes were validated by independent gene mutation. Results Of 31 candidate genes selected for investigation, the effects of mutations in 23 genes on papain-specific IgE or IgG1 were verified. Among the 20 verified genes influencing the IgE response, eight were necessary for the response, while 12 repressed IgE. Nine genes were not previously implicated in the IgE response. Fifteen genes encoded proteins contributing to IgE class switch recombination or B-cell receptor signaling. The precise roles of the five remaining genes (Flcn, Map1lc3b, Me2, Prkd2, and Scarb2) remain to be determined. Loss-of-function mutations in nine of the 12 genes limiting the IgE response were dominant or semi-dominant for the IgE phenotype but did not cause immunodeficiency in the heterozygous state. Using damaging allele frequencies for the corresponding human genes and in silico simulations (Monte Carlo) of undiscovered atopy mutations, we estimated the percentage of humans with heterozygous atopy risk mutations. Conclusions Up to 37% of individuals may be heterozygous carriers for at least one dominant atopy risk mutation.

International audience; Significance: The vast majority of autoimmune diseases are polygenic, and causal loci uncovered by genetic-mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this missing heritability include rare meaningful variants, rare copy number variations or deletions, epistasis, epigenetics, disease heterogeneity, and rare or infrequent variants that segregate within individual families (even within monozygotic twins). Here we demonstrate that experimental models of spontaneous autoimmune diseases may be invaluable tools to map rare germline variants impacting disease susceptibility traits. We identified a variant of the dual-specificity phosphatase 10 encoding gene that accelerates disease in an autoimmune type 1 diabetes model, the nonobese diabetic mouse.Abstract: Insulin-dependent or type 1 diabetes (T1D) is a polygenic autoimmune disease. In humans, more than 60 loci carrying common variants that confer disease susceptibility have been identified by genome-wide association studies, with a low individual risk contribution for most variants excepting those of the major histocompatibility complex (MHC) region (40 to 50% of risk); hence the importance of missing heritability due in part to rare variants. Nonobese diabetic (NOD) mice recapitulate major features of the human disease including genetic aspects with a key role for the MHC haplotype and a series of Idd loci. Here we mapped in NOD mice rare variants arising from genetic drift and significantly impacting disease risk. To that aim we established by selective breeding two sublines of NOD mice from our inbred NOD/Nck colony exhibiting a significant difference in T1D incidence. Whole-genome sequencing of high (H)- and low (L)-incidence sublines (NOD/NckH and NOD/NckL) revealed a limited number of subline-specific variants. Treating age of diabetes onset as a quantitative trait in automated meiotic mapping (AMM), enhanced susceptibility in NOD/NckH mice was unambiguously attributed to a recessive missense mutation of Dusp10, which encodes a dual specificity phosphatase. The causative effect of the mutation was verified by targeting Dusp10 with CRISPR-Cas9 in NOD/NckL mice, a manipulation that significantly increased disease incidence. The Dusp10 mutation resulted in islet cell down-regulation of type I interferon signature genes, which may exert protective effects against autoimmune aggression. De novo mutations akin to rare human susceptibility variants can alter the T1D phenotype.

Using random germline mutagenesis in mice, we identified a viable hypomorphic allele (boh) of the transcription-factor-encoding gene Ovol2 that resulted in obesity, which initially developed with normal food intake and physical activity but decreased energy expenditure. Fat weight was dramatically increased, while lean weight was reduced in 12-week-old boh homozygous mice, culminating by 24 weeks in massive obesity, hepatosteatosis, insulin resistance, and diabetes. The Ovol2

Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the identification of mutations causing immune phenotypes in mice by creating Candidate Explorer (CE), a machine-learning software program that integrates 67 features of genetic mapping data into a single numeric score, mathematically convertible to the probability of verification of any putative mutation–phenotype association. At this time, CE has evaluated putative mutation–phenotype associations arising from screening damaging mutations in ∼55% of mouse genes for effects on flow cytometry measurements of immune cells in the blood. CE has therefore identified more than half of genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

Here we report the isolation by selective breeding of two sublines of Non-Obese Diabetic (NOD) mice exhibiting a significant difference in the incidence of autoimmune type 1 diabetes (T1D). Whole genome sequencing of the NOD/NckH (high T1D incidence) and NOD/NckL (low T1D incidence) revealed the presence of a limited number of variants specific to each subline. Treating the age of T1D onset as a quantitative trait and using automated meiotic mapping (AMM), enhanced susceptibility in the NOD/NckH subline was unambiguously attributed to a recessive allele of Dusp10 which encodes a dual specificity phosphatase. The causative effect of the mutation was verified with a high level of confidence by targeting Dusp10 with CRISPR/Cas9 in NOD/NckL mice: in these animals a higher incidence of diabetes was observed. Expression of wild-type Dusp10 correlated with higher levels of surface PD-L1 in the islets of NOD/NckL mice.

When applied to immunity, forward genetic studies use meiotic mapping to provide strong statistical evidence that a particular mutation is causative of a particular immune phenotype. Notwithstanding this, co-segregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the selection of authentic causative mutations using a machine learning software tool, Candidate Explorer (CE), which integrates 65 data features into a single numeric score, mathematically convertible to the likelihood of verification of any putative mutation-phenotype association. CE has identified most genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

A T cell sleeper agent against stress Considerable changes in cellular metabolism occur when T cells transition from a resting to an activated state. One side effect of this process is an increase in reactive oxygen species (ROS). These molecules potentiate T cell receptor (TCR) signaling but can also result in detrimental oxidative stress (see the Perspective by Su and Dutta). Yue et al. describe one mechanism by which T cells can resolve this contradiction. Using mice with a T cell-specific deficiency in Schlafen 2 (SLFN2), they found that this protein binds to and protects transfer RNAs from oxidative stress-induced cleavage by the ribonuclease angiogenin. This process is downstream of ROS generation, which allows activated T cells to maintain protein synthesis despite the ROS that would otherwise inhibit translation. Science , this issue p. eaba4220 ; see also p. 683

Motivation: Classical nuclear export signals (NESs) are short cognate peptides that direct proteins out of the nucleus via the CRM1-mediated export pathway. CRM1 regulates the localization of hundreds of macromolecules involved in various cellular functions and diseases. Due to the diverse and complex nature of NESs, reliable prediction of the signal remains a challenge despite several attempts made in the last decade. Results: We present a new NES predictor, LocNES. LocNES scans query proteins for NES consensus-fitting peptides and assigns these peptides probability scores using Support Vector Machine model, whose feature set includes amino acid sequence, disorder propensity, and the rank of position-specific scoring matrix score. LocNES demonstrates both higher sensitivity and precision over existing NES prediction tools upon comparative analysis using experimentally identified NESs. Availability and implementation: LocNES is freely available at http://prodata.swmed.edu/LocNES Contact: yuhmin.chook@utsouthwestern.edu Supplementary information: Supplementary data are available at Bioinformatics online.

A 221-entry NESdb database produces data sets of true- and false-positive nuclear export signals (NES). Analysis of these data sets leads to identification of a set of sequence and structural properties that distinguishes true NESs from peptides without export capability that merely conform to the NES consensus sequences., We compiled >200 nuclear export signal (NES)–containing CRM1 cargoes in a database named NESdb. We analyzed the sequences and three-dimensional structures of natural, experimentally identified NESs and of false-positive NESs that were generated from the database in order to identify properties that might distinguish the two groups of sequences. Analyses of amino acid frequencies, sequence logos, and agreement with existing NES consensus sequences revealed strong preferences for the Φ1-X3-Φ2-X2-Φ3-X-Φ4 pattern and for negatively charged amino acids in the nonhydrophobic positions of experimentally identified NESs but not of false positives. Strong preferences against certain hydrophobic amino acids in the hydrophobic positions were also revealed. These findings led to a new and more precise NES consensus. More important, three-dimensional structures are now available for 68 NESs within 56 different cargo proteins. Analyses of these structures showed that experimentally identified NESs are more likely than the false positives to adopt α-helical conformations that transition to loops at their C-termini and more likely to be surface accessible within their protein domains or be present in disordered or unobserved parts of the structures. Such distinguishing features for real NESs might be useful in future NES prediction efforts. Finally, we also tested CRM1-binding of 40 NESs that were found in the 56 structures. We found that 16 of the NES peptides did not bind CRM1, hence illustrating how NESs are easily misidentified.

There are 221 experimentally validated, leucine-rich nuclear export signal (NES)–containing CRM1 cargoes in a database named NESdb. Entries in NESdb are annotated with sequence and structural information on both NES and cargo proteins, as well as with experimental evidence on NES-mapping and CRM1-mediated nuclear export., The leucine-rich nuclear export signal (NES) is the only known class of targeting signal that directs macromolecules out of the cell nucleus. NESs are short stretches of 8–15 amino acids with regularly spaced hydrophobic residues that bind the export karyopherin CRM1. NES-containing proteins are involved in numerous cellular and disease processes. We compiled a database named NESdb that contains 221 NES-containing CRM1 cargoes that were manually curated from the published literature. Each NESdb entry is annotated with information about sequence and structure of both the NES and the cargo protein, as well as information about experimental evidence of NES-mapping and CRM1-mediated nuclear export. NESdb will be updated regularly and will serve as an important resource for nuclear export signals. NESdb is freely available to nonprofit organizations at http://prodata.swmed.edu/LRNes.

The Karyopherin-β family of nuclear transport factors mediates the majority of nucleocytoplasmic transport. Although each of the 19 Karyopherin-βs transports unique sets of cargos, only three classes of nuclear localization and export signals, or NLSs and NESs, have been characterized. The short basic classical-NLS was first discovered in the 1980s and their karyopherin-bound structures were first reported more than 10 years ago. More recently, structural and biophysical studies of Karyopherin-β2-cargo complexes led to definition of the complex and diverse PY-NLS. Structural knowledge of the leucine-rich NES is finally available more than 10 years after the discovery of its recognition by the exportin CRM1. We review recent findings relating to how these three classes of nuclear targeting signals are recognized by their Karyopherin-β nuclear transport factors.

G.U wobble base pairs are the most common and highly conserved non-Watson-Crick base pairs in RNA. Previous surface maps imply uniformly negative electrostatic potential at the major groove of G.U wobble base pairs embedded in RNA helices, suitable for entrapment of cationic ligands. In this work, we have used a Poisson-Boltzmann approach to gain a more detailed and accurate characterization of the electrostatic profile. We found that the major groove edge of an isolated G.U wobble displays distinctly enhanced negativity compared with standard GC or AU base pairs; however, in the context of different helical motifs, the electrostatic pattern varies. G.U wobbles with distinct widening have similar major groove electrostatic potentials to their canonical counterparts, whereas those with minimal widening exhibit significantly enhanced electronegativity, ranging from 0.8 to 2.5 kT/e, depending upon structural features. We propose that the negativity at the major groove of G.U wobble base pairs is determined by the combined effect of the base atoms and the sugar-phosphate backbone, which is impacted by stacking pattern and groove width as a result of base sequence. These findings are significant in that they provide predictive power with respect to which G.U sites in RNA are most likely to bind cationic ligands.

We have investigated electrostatic and surface features of an essential region of the catalytic core of the spliceosome, the eukaryotic precursor messenger (pre-m)RNA splicing apparatus. The nucleophile for the first of two splicing reactions is the 2'-hydroxyl (OH) of the ribose of a specific adenosine within the intron. During assembly of the spliceosome's catalytic core, this adenosine is positioned by pairing with a short region of the U2 small nuclear (sn)RNA to form the pre-mRNA branch site helix. The solution structure of the spliceosomal pre-mRNA branch site [Newby,M.I. and Greenbaum,N.L. (2002) Nature Struct. Biol., 9, 958-965] showed that a phylogenetically conserved pseudouridine (psi) residue in the segment of U2 snRNA that pairs with the intron induces a markedly different structure compared with that of its unmodified counterpart. In order to achieve a more detailed understanding of the factors that contribute to recognition of the spliceosome's branch site helix and activation of the nucleophile for the first step of pre-mRNA splicing, we have calculated surface areas and electrostatic potentials of psi-modified and unmodified branch site duplexes. There was no significant difference between the total accessible area or ratio of total polar:nonpolar groups between modified and unmodified duplexes. However, there was substantially greater exposure of nonpolar area of the adenine base, and less exposure of the 2'-OH, in the psi-modified structure. Electrostatic potentials computed using a hybrid boundary element and finite difference nonlinear Poisson-Boltzmann approach [Boschitsch, A.H. and Fenley, M.O. (2004) J. Comput. Chem., 25, 935-955] revealed a region of exceptionally negative potential in the major groove surrounding the 2'-OH of the branch site adenosine. These surface and electrostatic features may contribute to the overall recognition of the pre-mRNA branch site region by other components of the splicing reaction.

Proteins and DNA form complexes due to complementary properties of their molecular structure and electrostatic potential at the binding interface. While proteins predominantly consist of globular domains complemented by linkers and tails, DNA generally forms a double helix through hydrogen bonding between bases on opposite strands. Globular domains of DNA-binding proteins are condensed structures with little flexibility that often bind the major groove while protein linkers and tails are extremely flexible, which play a role for many protein families in binding the minor groove. Protein residues have been observed to recognize the sequence-dependent shape of DNA, engage in hydrogen bonding with the functional groups of the bases, form water-mediated hydrogen bonds, or be attracted by the negative electrostatic potential that surrounds DNA. Due to the polyanionic character of the double helix, basic side chains, such as arginines and lysines, are key protein residues involved in DNA binding. Much structural and biophysical knowledge on protein-DNA recognition has been gathered from experimental and computational studies, but the vast amount of DNA sequence information from genomic studies demonstrates that our understanding of the molecular origins of protein-DNA binding specificity, gene regulation, and chromatin organization is far from completion. The present book chapter offers a new perspective on protein-DNA binding, which emphasizes the need to consider shape and electrostatic complementarity together when rationalizing protein-DNA complex formation.