SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins

Selenoproteins are proteins containing an uncommon amino acid selenocysteine (Sec). Sec is inserted by a specific translational machinery that recognizes a stem-loop structure, the SECIS element, at the 3′ UTR of selenoprotein genes and recodes a UGA codon within the coding sequence. As UGA is normally a translational stop signal, selenoproteins are generally misannotated and designated tools have to be developed for this class of proteins. Here, we present two new computational methods for selenoprotein identification and analysis, which we provide publicly through the web servers at http://gladyshevlab.org/SelenoproteinPredictionServer or http://seblastian.crg.es. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a new method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins. By applying these tools to diverse eukaryotic genomes, we provide a ranked list of newly predicted selenoproteins together with their annotated cysteine-containing homologues. An analysis of a representative candidate belonging to the AhpC family shows how the use of Sec in this protein evolved in bacterial and eukaryotic lineages

UGA codon position-dependent incorporation of selenocysteine into mammalian selenoproteins

It is thought that the SelenoCysteine Insertion Sequence (SECIS) element and UGA codon are sufficient for selenocysteine (Sec) insertion. However, we found that UGA supported Sec insertion only at its natural position or in its close proximity in mammalian thioredoxin reductase 1 (TR1). In contrast, Sec could be inserted at any tested position in mammalian TR3. Replacement of the 3′-UTR of TR3 with the corresponding segment of a Euplotes crassus TR restricted Sec insertion into the C-terminal region, whereas the 3′-UTR of TR3 conferred unrestricted Sec insertion into E. crassus TR, in which Sec insertion is normally limited to the C-terminal region. Exchanges of 3′-UTRs between mammalian TR1 and E. crassus TR had no effect, as both proteins restricted Sec insertion. We further found that these effects could be explained by the use of selenoprotein-specific SECIS elements. Examination of Sec insertion into other selenoproteins was consistent with this model. The data indicate that mammals evolved the ability to limit Sec insertion into natural positions within selenoproteins, but do so in a selenoprotein-specific manner, and that this process is controlled by the SECIS element in the 3′-UTR

Evidence that mutation accumulation does not cause aging in Saccharomyces cerevisiae

The concept that mutations cause aging phenotypes could not be directly tested previously due to inability to identify age-related mutations in somatic cells and determine their impact on organismal aging. Here, we subjected Saccharomyces cerevisiae to multiple rounds of replicative aging and assessed de novo mutations in daughters of mothers of different age. Mutations did increase with age, but their low numbers, < 1 per lifespan, excluded their causal role in aging. Structural genome changes also had no role. A mutant lacking thiol peroxidases had the mutation rate well above that of wild-type cells, but this did not correspond to the aging pattern, as old wild-type cells with few or no mutations were dying, whereas young mutant cells with many more mutations continued dividing. In addition, wild-type cells lost mitochondrial DNA during aging, whereas shorter-lived mutant cells preserved it, excluding a causal role of mitochondrial mutations in aging. Thus, DNA mutations do not cause aging in yeast. These findings may apply to other damage types, suggesting a causal role of cumulative damage, as opposed to individual damage types, in organismal aging

Analysis of cancer genomes reveals basic features of human aging and its role in cancer development

Somatic mutations have long been implicated in aging and disease, but their impact on fitness and function is difficult to assess. Here by analysing human cancer genomes we identify mutational patterns associated with aging. Our analyses suggest that age-associated mutation load and burden double approximately every 8 years, similar to the all-cause mortality doubling time. This analysis further reveals variance in the rate of aging among different human tissues, for example, slightly accelerated aging of the reproductive system. Age-adjusted mutation load and burden correlate with the corresponding cancer incidence and precede it on average by 15 years, pointing to pre-clinical cancer development times. Behaviour of mutation load also exhibits gender differences and late-life reversals, explaining some gender-specific and late-life patterns in cancer incidence rates. Overall, this study characterizes some features of human aging and offers a mechanism for age being a risk factor for the onset of cancer

Composition and Evolution of the Vertebrate and Mammalian Selenoproteomes

Background: Selenium is an essential trace element in mammals due to its presence in proteins in the form of selenocysteine (Sec). Human genome codes for 25 Sec-containing protein genes, and mouse and rat genomes for 24. Methodology/Principal Findings: We characterized the selenoproteomes of 44 sequenced vertebrates by applying gene prediction and phylogenetic reconstruction methods, supplemented with the analyses of gene structures, alternative splicing isoforms, untranslated regions, SECIS elements, and pseudogenes. In total, we detected 45 selenoprotein subfamilies. 28 of them were found in mammals, and 41 in bony fishes. We define the ancestral vertebrate (28 proteins) and mammalian (25 proteins) selenoproteomes, and describe how they evolved along lineages through gene duplication (20 events), gene loss (10 events) and replacement of Sec with cysteine (12 events). We show that an intronless selenophosphate synthetase 2 gene evolved in early mammals and replaced functionally the original multiexon gene in placental mammals, whereas both genes remain in marsupials. Mammalian thioredoxin reductase 1 and thioredoxinglutathione reductase evolved from an ancestral glutaredoxin-domain containing enzyme, still present in fish. Selenoprotein V and GPx6 evolved specifically in placental mammals from duplications of SelW and GPx3, respectively, and GPx6 lost Sec several times independently. Bony fishes were characterized by duplications of several selenoprotein families (GPx1, GPx3, GPx4, Dio3, MsrB1, SelJ, SelO, SelT, SelU1, and SelW2). Finally, we report identification of new isoforms for several selenoproteins and describe unusually conserved selenoprotein pseudogenes. Conclusions/Significance: This analysis represents the first comprehensive survey of the vertebrate and mammal selenoproteomes, and depicts their evolution along lineages. It also provides a wealth of information on these selenoproteins and their forms

Reduced Utilization of Selenium by Naked Mole Rats Due to a Specific Defect in GPx1 Expression

Naked mole rat (MR) Heterocephalus glaber is a rodent model of delayed aging because of its unusually long life span (\u3e28 years). It is also not known to develop cancer. In the current work, tissue imaging by x-ray fluorescence microscopy and direct analyses of trace elements revealed low levels of selenium in the MR liver and kidney, whereas MR and mouse brains had similar selenium levels. This effect was not explained by uniform selenium deficiency because methionine sulfoxide reductase activities were similar in mice and MR. However, glutathione peroxidase activity was an order of magnitude lower inMRliver and kidney than in mouse tissues. In addition, metabolic labeling of MR cells with 75Se revealed a loss of the abundant glutathione peroxidase 1 (GPx1) band, whereas other selenoproteins were preserved. To characterize theMRselenoproteome, we sequenced its liver transcriptome. Gene reconstruction revealed standard selenoprotein sequences except for GPx1, which had an early stop codon, and SelP, which had low selenocysteine content. When expressed inHEK293cells,MRGPx1waspresent in low levels,and its expression could be rescued neither by removing the early stop codon nor by replacing its SECIS element. In addition, GPx1 mRNAwas present in lower levels inMRliver than in mouse liver. To determine if GPx1 deficiency could account for the reduced selenium content, we analyzed GPx1 knock-out mice and found reduced selenium levels in their livers and kidneys. Thus, MR is characterized by the reduced utilization of selenium due to a specific defect in GPx1 expression

Selenoprotein gene nomenclature

The human genome contains 25 genes coding for selenocysteine-containing proteins (selenoproteins). These proteins are involved in a variety of functions, most notably redox homeostasis. Selenoprotein enzymes with known functions are designated according to these functions: TXNRD1, TXNRD2, and TXNRD3 (thioredoxin reductases), GPX1, GPX2, GPX3, GPX4 and GPX6 (glutathione peroxidases), DIO1, DIO2, and DIO3 (iodothyronine deiodinases), MSRB1 (methionine-R-sulfoxide reductase 1) and SEPHS2 (selenophosphate synthetase 2). Selenoproteins without known functions have traditionally been denoted by SEL or SEP symbols. However, these symbols are sometimes ambiguous and conflict with the approved nomenclature for several other genes. Therefore, there is a need to implement a rational and coherent nomenclature system for selenoprotein-encoding genes. Our solution is to use the root symbol SELENO followed by a letter. This nomenclature applies to SELENOF (selenoprotein F, the 15 kDa selenoprotein, SEP15), SELENOH (selenoprotein H, SELH, C11orf31), SELENOI (selenoprotein I, SELI, EPT1), SELENOK (selenoprotein K, SELK), SELENOM (selenoprotein M, SELM), SELENON (selenoprotein N, SEPN1, SELN), SELENOO (selenoprotein O, SELO), SELENOP (selenoprotein P, SeP, SEPP1, SELP), SELENOS (selenoprotein S, SELS, SEPS1, VIMP), SELENOT (selenoprotein T, SELT), SELENOV (selenoprotein V, SELV) and SELENOW (selenoprotein W, SELW, SEPW1). This system, approved by the HUGO Gene Nomenclature Committee, also resolves conflicting, missing and ambiguous designations for selenoprotein genes and is applicable to selenoproteins across vertebrates

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon

The current consensus is that drought has developed in the Sahel during the second half of the twentieth century as a result of remote effects of oceanic anomalies amplified by local land–atmosphere interactions. This paper focuses on the impacts of oceanic anomalies upon West African climate and specifically aims to identify those from SST anomalies in the Pacific/Indian Oceans during spring and summer seasons, when they were significant. Idealized sensitivity experiments are performed with four atmospheric general circulation models (AGCMs). The prescribed SST patterns used in the AGCMs are based on the leading mode of covariability between SST anomalies over the Pacific/Indian Oceans and summer rainfall over West Africa. The results show that such oceanic anomalies in the Pacific/Indian Ocean lead to a northward shift of an anomalous dry belt from the Gulf of Guinea to the Sahel as the season advances. In the Sahel, the magnitude of rainfall anomalies is comparable to that obtained by other authors using SST anomalies confined to the proximity of the Atlantic Ocean. The mechanism connecting the Pacific/Indian SST anomalies with West African rainfall has a strong seasonal cycle. In spring (May and June), anomalous subsidence develops over both the Maritime Continent and the equatorial Atlantic in response to the enhanced equatorial heating. Precipitation increases over continental West Africa in association with stronger zonal convergence of moisture. In addition, precipitation decreases over the Gulf of Guinea. During the monsoon peak (July and August), the SST anomalies move westward over the equatorial Pacific and the two regions where subsidence occurred earlier in the seasons merge over West Africa. The monsoon weakens and rainfall decreases over the Sahel, especially in August.Peer reviewe