Local Absence of Secondary Structure Permits Translation of mRNAs that Lack Ribosome-Binding Sites

The initiation of translation is a fundamental and highly regulated process in gene expression. Translation initiation in prokaryotic systems usually requires interaction between the ribosome and an mRNA sequence upstream of the initiation codon, the so-called ribosome-binding site (Shine-Dalgarno sequence). However, a large number of genes do not possess Shine-Dalgarno sequences, and it is unknown how start codon recognition occurs in these mRNAs. We have performed genome-wide searches in various groups of prokaryotes in order to identify sequence elements and/or RNA secondary structural motifs that could mediate translation initiation in mRNAs lacking Shine-Dalgarno sequences. We find that mRNAs without a Shine-Dalgarno sequence are generally less structured in their translation initiation region and show a minimum of mRNA folding at the start codon. Using reporter gene constructs in bacteria, we also provide experimental support for local RNA unfoldedness determining start codon recognition in Shine-Dalgarno–independent translation. Consistent with this, we show that AUG start codons reside in single-stranded regions, whereas internal AUG codons are usually in structured regions of the mRNA. Taken together, our bioinformatics analyses and experimental data suggest that local absence of RNA secondary structure is necessary and sufficient to initiate Shine-Dalgarno–independent translation. Thus, our results provide a plausible mechanism for how the correct translation initiation site is recognized in the absence of a ribosome-binding site

Middle East - North Africa and the millennium development goals : implications for German development cooperation

          Closed-loop controlled combustion is a promising technique to improve the overall performance of internal combustion engines and Diesel engines in particular. In order for this technique to be implemented some form of feedback from the combustion process is required. The feedback signal is processed and from it combustionrelated parameters are computed. These parameters are then fed to a control process which drives a series of outputs (e.g. injection timing in Diesel engines) to control their values. This paper’s focus lies on the processing and computation that is needed on the feedback signal before this is ready to be fed to the control process as well as on the electronics necessary to support it. A number of feedback alternatives are briefly discussed and for one of them, the in-cylinder pressure sensor, the CA50 (crank angle in which the integrated heat release curve reaches its 50% value) and the IMEP (Indicated Mean Effective Pressure) are identified as two potential control variables. The hardware architecture of a system capable of calculating both of them on-line is proposed and necessary feasibility size and speed considerations are made by implementing critical blocks in VHDL targeting a flash-based Actel ProASIC3 automotive-grade FPGA

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Housing Cycles in Switzerland - A Time-Varying Approach

In light of the strong increase of house prices in Switzerland, we analyze the effects of mortgage rate shocks, changes in the interplay between housing demand and supply and GDP growth on house prices for the time period 1981- 2014. We employ Bayesian time-varying coefficients vector autoregressions to allow different monetary and immigration regimes over time. A number of structural changes, such as regulatory changes in the aftermath of the 1990s real estate crisis, the introduction of free-labor movements in the 2000s or the zero lower bound interest rate regime in the 2010s might have affected the responses of house prices to influencing factors. We investigate potential parameter changes and their importance in light of the current housing price boom. We find that 40% of house price variations can be explained by changes in demand and supply for housing. Furthermore, the response of house prices to mortgage rate shocks weakened after the 1990s real estate crisis and increased in size again during the recent house price boom

Taming volatile high frequency data with long lag structure: An optimal filtering approach for forecasting

We propose a Bayesian optimal filtering setup for improving out-of-sample forecasting performance when using volatile high frequency data with long lag structure for forecasting low-frequency data. We test this setup by using real-time Swiss construction investment and construction permit data. We compare our approach to different filtering techniques and show that our proposed filter outperforms various commonly used filtering techniques in terms of extracting the more relevant signal of the indicator series for forecasting

Time-Varying and Regional Dynamics in Swiss Housing Markets

Summary In light of the strong increase of house prices in Switzerland in the 2000s and early 2010s, we analyze the effects of mortgage rate shocks, changes in housing demand & supply and business cycle conditions on house prices for the time period 1982–2013. We study intertemporal effects by employing Bayesian timevarying coefficients vector autoregressions (TVC-BVAR), regional effects by using regional BVARs and heterogeneity in housing markets by looking at housing segments. 50 % of house price variations can be explained by housing demand & supply. The response of house prices to mortgage rate shocks weakened after the 1990s real estate crisis and remained constant thereafter. However, owneroccupied apartment prices became again more sensitive to mortgage rate shocks during the recent house price boom. Regional effects are especially prevalent for regions Zurich and Geneva

Macro and micro level impulse responses: A survey experimental identification procedure

This paper analyzes the effects of macroeconomic shocks on prices and output at different levels of aggregation using a bottom up approach. We show how to generate firm level impulse responses by incorporating experimental settings into surveys and by exposing firm executives to treatment scenarios. Aggregation then results in industry level and economy wide impulse responses. We further show that the effects obtained from survey experiments can be mapped into impulse responses retrieved from VARs. We apply the procedure to study the effects of oil price shocks using a representative sample of over 1000 Swiss firms. At the aggregate and industry level our findings confirm, with some notable exceptions, results from a standard VAR. At the micro level we analyze the driving forces behind firm specific impulse responses, controlling for several firm characteristics via panel data analysis and thereby solving existing puzzles

What Do Firm Managers Tell Us About the Transmission Channels of Oil Price Shocks?

In this paper, we investigate the transmission channels of oil price shocks using a factorial survey. We confront CEOs and CFOs of a representative sample of firms with a hypothetical vignette in which the oil price rises exogenously above managers’ baseline expectations. The managers then estimate the short- and medium-term cost, price, and output effects of the shock on their firms. We find that the managers expect the shock to have very different effects on their firms: the cross-sectional distributions of the responses are large, skewed, and have fat tails. Higher firm-specific energy input costs lead managers to expect greater output losses and sales price increases. Higher market power accelerates this input cost effect. Another important determinant is managers’ pre-shock uncertainty about business prospects. The importance of the three channels varies considerably across industries