Fine-Tuning Nonhomogeneous Regression for Probabilistic Precipitation Forecasts: Unanimous Predictions, Heavy Tails, and Link Functions

Raw ensemble forecasts of precipitation amounts and their forecast uncertainty have large errors, especially in mountainous regions where the modeled topography in the numerical weather prediction model and real topography differ most. Therefore, statistical postprocessing is typically applied to obtain automatically corrected weather forecasts. This study applies the nonhomogenous regression framework as a state-of-the-art ensemble postprocessing technique to predict a full forecast distribution and improves its forecast performance with three statistical refinements. First of all, a novel split-type approach effectively accounts for unanimous zero precipitation predictions of the global ensemble model of the ECMWF. Additionally, the statistical model uses a censored logistic distribution to deal with the heavy tails of precipitation amounts. Finally, it is investigated which are the most suitable link functions for the optimization of regression coefficients for the scale parameter. These three refinements are tested for 10 stations in a small area of the European Alps for lead times from +24 to +144 h and accumulation periods of 24 and 6 h. Together, they improve probabilistic forecasts for precipitation amounts as well as the probability of precipitation events over the default postprocessing method. The improvements are largest for the shorter accumulation periods and shorter lead times, where the information of unanimous ensemble predictions is more important. </jats:p

cDNA Library Generation for the Analysis of Small RNAs by High-Throughput Sequencing

The RNome of a cell is highly diverse and consists besides messenger RNAs (mRNAs), transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) also of other small and long transcript entities without apparent coding potential. This class of molecules, commonly referred to as non-protein-coding RNAs (ncRNAs), is involved in regulating numerous biological processes and thought to contribute to cellular complexity. Therefore, much effort is put into their identification and further functional characterization. Here we provide a cost-effective and reliable method for cDNA library construction of small RNAs in the size range of 20-500 residues. The effectiveness of the described method is demonstrated by the analysis of ribosome-associated small RNAs in the eukaryotic model organism Trypanosoma brucei

Consequential considerations when mapping tRNA fragments

We examine several of the choices that went into the design of tDRmapper, a recently reported tool for identifying transfer RNA (tRNA) fragments in deep sequencing data, evaluate them in the context of currently available knowledge, and discuss their potential impact on the output that the tool generates

Stem cell function and stress response are controlled by protein synthesis.

Whether protein synthesis and cellular stress response pathways interact to control stem cell function is currently unknown. Here we show that mouse skin stem cells synthesize less protein than their immediate progenitors in vivo, even when forced to proliferate. Our analyses reveal that activation of stress response pathways drives both a global reduction of protein synthesis and altered translational programmes that together promote stem cell functions and tumorigenesis. Mechanistically, we show that inhibition of post-transcriptional cytosine-5 methylation locks tumour-initiating cells in this distinct translational inhibition programme. Paradoxically, this inhibition renders stem cells hypersensitive to cytotoxic stress, as tumour regeneration after treatment with 5-fluorouracil is blocked. Thus, stem cells must revoke translation inhibition pathways to regenerate a tissue or tumour.This work was funded by Cancer Research UK (CR-UK), Worldwide Cancer Research, the Medical Research Council (MRC), the European Research Council (ERC), and EMBO. Research in Michaela Frye's laboratory is supported by a core support grant from the Wellcome Trust and MRC to the Wellcome Trust-Medical Research Cambridge Stem Cell Institute.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nature1828