tRNA splicing

Introns interrupt the continuity of many eukaryal genes, and therefore their removal by splicing is a crucial step in gene expression. Interestingly, even within Eukarya there are at least four splicing mechanisms. mRNA splicing in the nucleus takes place in two phosphotransfer reactions on a complex and dynamic machine, the spliceosome. This reaction is related in mechanism to the two self-splicing mechanisms for Group 1 and Group 2 introns. In fact the Group 2 introns are spliced by an identical mechanism to mRNA splicing, although there is no general requirement for either proteins or co-factors. Thus it seems likely that the Group 2 and nuclear mRNA splicing reactions have diverged from a common ancestor. tRNA genes are also interrupted by introns, but here the splicing mechanism is quite different because it is catalyzed by three enzymes, all proteins and with an intrinsic requirement for ATP hydrolysis. tRNA splicing occurs in all three major lines of descent, the Bacteria, the Archaea, and the Eukarya. In bacteria the introns are self-splicing (1-3). Until recently it was thought that the mechanisms of tRNA splicing in Eukarya and Archaea were unrelated as well. In the past year, however, it has been found that the first enzyme in the tRNA splicing pathway, the tRNA endonuclease, has been conserved in evolution since the divergence of the Eukarya and the Archaea. Surprising insights have been obtained by comparison of the structures and mechanisms of tRNA endonuclease from these two divergent lines

Statistical coverage for supersymmetric parameter estimation: a case study with direct detection of dark matter

Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the employed statistical framework and scanning algorithm. In frequentist parameter estimation, a central requirement for properly constructed confidence intervals is that they cover true parameter values, preferably at exactly the stated confidence level when experiments are repeated infinitely many times. Since most widely-used scanning techniques are optimised for Bayesian statistics, one needs to assess their abilities in providing correct confidence intervals in terms of the statistical coverage. Here we investigate this for the Constrained Minimal Supersymmetric Standard Model (CMSSM) when only constrained by data from direct searches for dark matter. We construct confidence intervals from one-dimensional profile likelihoods and study the coverage by generating several pseudo-experiments for a few benchmark sets of pseudo-true parameters. We use nested sampling to scan the parameter space and evaluate the coverage for the benchmarks when either flat or logarithmic priors are imposed on gaugino and scalar mass parameters. The sampling algorithm has been used in the configuration usually adopted for exploration of the Bayesian posterior. We observe both under- and over-coverage, which in some cases vary quite dramatically when benchmarks or priors are modified. We show how most of the variation can be explained as the impact of explicit priors as well as sampling effects, where the latter are indirectly imposed by physicality conditions. For comparison, we also evaluate the coverage for Bayesian credible intervals, and observe significant under-coverage in those cases.Comment: 30 pages, 5 figures; v2 includes major updates in response to referee's comments; extra scans and tables added, discussion expanded, typos corrected; matches published versio

Observational constraints on the curvaton model of inflation

Simple curvaton models can generate a mixture of of correlated primordial adiabatic and isocurvature perturbations. The baryon and cold dark matter isocurvature modes differ only by an observationally null mode in which the two perturbations almost exactly compensate, and therefore have proportional effects at linear order. We discuss the CMB anisotropy in general mixed models, and give a simple approximate analytic result for the large scale CMB anisotropy. Working numerically we use the latest WMAP observations and a variety of other data to constrain the curvaton model. We find that models with an isocurvature contribution are not favored relative to simple purely adiabatic models. However a significant primordial totally correlated baryon isocurvature perturbation is not ruled out. Certain classes of curvaton model are thereby ruled out, other classes predict enough non-Gaussianity to be detectable by the Planck satellite. In the appendices we review the relevant equations in the covariant formulation and give series solutions for the radiation dominated era.Comment: Minor changes and corrections to match version accepted by PR

Ataluren stimulates ribosomal selection of near-cognate tRNAs to promote nonsense suppression

A premature termination codon (PTC) in the ORF of an mRNA generally leads to production of a truncated polypeptide, accelerated degradation of the mRNA, and depression of overall mRNA expression. Accordingly, nonsense mutations cause some of the most severe forms of inherited disorders. The small-molecule drug ataluren promotes therapeutic nonsense suppression and has been thought to mediate the insertion of near-cognate tRNAs at PTCs. However, direct evidence for this activity has been lacking. Here, we expressed multiple nonsense mutation reporters in human cells and yeast and identified the amino acids inserted when a PTC occupies the ribosomal A site in control, ataluren-treated, and aminoglycoside-treated cells. We find that ataluren\u27s likely target is the ribosome and that it produces full-length protein by promoting insertion of near-cognate tRNAs at the site of the nonsense codon without apparent effects on transcription, mRNA processing, mRNA stability, or protein stability. The resulting readthrough proteins retain function and contain amino acid replacements similar to those derived from endogenous readthrough, namely Gln, Lys, or Tyr at UAA or UAG PTCs and Trp, Arg, or Cys at UGA PTCs. These insertion biases arise primarily from mRNA:tRNA mispairing at codon positions 1 and 3 and reflect, in part, the preferred use of certain nonstandard base pairs, e.g., U-G. Ataluren\u27s retention of similar specificity of near-cognate tRNA insertion as occurs endogenously has important implications for its general use in therapeutic nonsense suppression

Correlated perturbations from inflation and the cosmic microwave background

We compare the latest cosmic microwave background data with theoretical predictions including correlated adiabatic and CDM isocurvature perturbations with a simple power-law dependence. We find that there is a degeneracy between the amplitude of correlated isocurvature perturbations and the spectral tilt. A negative (red) tilt is found to be compatible with a larger isocurvature contribution. Estimates of the baryon and CDM densities are found to be almost independent of the isocurvature amplitude. The main result is that current microwave background data do not exclude a dominant contribution from CDM isocurvature fluctuations on large scales.Comment: 5 pages, revtex, 3 figures. V3 - DASI data added and reionization taken into account. New figure 2. Matches version to appear in PR

CLP1 Founder Mutation Links tRNA Splicing and Maturation to Cerebellar Development and Neurodegeneration

SummaryNeurodegenerative diseases can occur so early as to affect neurodevelopment. From a cohort of more than 2,000 consanguineous families with childhood neurological disease, we identified a founder mutation in four independent pedigrees in cleavage and polyadenylation factor I subunit 1 (CLP1). CLP1 is a multifunctional kinase implicated in tRNA, mRNA, and siRNA maturation. Kinase activity of the CLP1 mutant protein was defective, and the tRNA endonuclease complex (TSEN) was destabilized, resulting in impaired pre-tRNA cleavage. Germline clp1 null zebrafish showed cerebellar neurodegeneration that was rescued by wild-type, but not mutant, human CLP1 expression. Patient-derived induced neurons displayed both depletion of mature tRNAs and accumulation of unspliced pre-tRNAs. Transfection of partially processed tRNA fragments into patient cells exacerbated an oxidative stress-induced reduction in cell survival. Our data link tRNA maturation to neuronal development and neurodegeneration through defective CLP1 function in humans

Cosmological parameters from SDSS and WMAP

We measure cosmological parameters using the three-dimensional power spectrum P(k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a ``vanilla'' flat adiabatic Lambda-CDM model without tilt (n=1), running tilt, tensor modes or massive neutrinos. Adding SDSS information more than halves the WMAP-only error bars on some parameters, tightening 1 sigma constraints on the Hubble parameter from h~0.74+0.18-0.07 to h~0.70+0.04-0.03, on the matter density from Omega_m~0.25+/-0.10 to Omega_m~0.30+/-0.04 (1 sigma) and on neutrino masses from <11 eV to <0.6 eV (95%). SDSS helps even more when dropping prior assumptions about curvature, neutrinos, tensor modes and the equation of state. Our results are in substantial agreement with the joint analysis of WMAP and the 2dF Galaxy Redshift Survey, which is an impressive consistency check with independent redshift survey data and analysis techniques. In this paper, we place particular emphasis on clarifying the physical origin of the constraints, i.e., what we do and do not know when using different data sets and prior assumptions. For instance, dropping the assumption that space is perfectly flat, the WMAP-only constraint on the measured age of the Universe tightens from t0~16.3+2.3-1.8 Gyr to t0~14.1+1.0-0.9 Gyr by adding SDSS and SN Ia data. Including tensors, running tilt, neutrino mass and equation of state in the list of free parameters, many constraints are still quite weak, but future cosmological measurements from SDSS and other sources should allow these to be substantially tightened.Comment: Minor revisions to match accepted PRD version. SDSS data and ppt figures available at http://www.hep.upenn.edu/~max/sdsspars.htm

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models\u27 performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe\u27s common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe