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It is generally believed that introns are not translated; therefore, the potential intronic features that may be related to the translation step (occurring after splicing) have yet to be thoroughly studied. Here, focusing on four fungi, we performed for the first time a comprehensive study aimed at characterizing how translation efficiency is encoded in introns and affects their evolution. By analysing their intronome we provide evidence of selection for STOP codons close to the intronic 50 end, and show that the beginning of introns are selected for significantly high translation, presumably to reduce translation and metabolic costs in cases of non-spliced introns. Ribosomal profiling data analysis in Saccharomyces cerevisiae supports the conjecture that in this organism intron retention frequently occurs, introns are partially translated, and their translation efficiency affects organismal fitness. We show that the reported results are more significant in highly translated and highly spliced genes, but are not associated only with genes with a specific function. We also discuss the potential relation of the reported signals to efficient nonsense-mediated decay due to splicing errors. These new discoveries are supported by population-genetics considerations. In addition, they are contributory steps towards a broader understanding of intron evolution and the effect of silent mutations on gene expression and organismal fitness. [ABSTRACT FROM AUTHOR]

Motivation: Dozens of studies in recent years have demonstrated that codon usage encodes various aspects related to all stages of gene expression regulation. When relevant high-quality large-scale gene expression data are available, it is possible to statistically infer and model these signals, enabling analysing and engineering gene expression. However, when these data are not available, it is impossible to infer and validate such models. Results: In this current study, we suggest Chimera--an unsupervised computationally efficient approach for exploiting hidden high-dimensional information related to the way gene expression is encoded in the open reading frame (ORF), based solely on the genome of the analysed organism. One version of the approach, named Chimera Average Repetitive Substring (ChimeraARS), estimates the adaptability of an ORF to the intracellular gene expression machinery of a genome (host), by computing its tendency to include long substrings that appear in its coding sequences; the second version, named ChimeraMap, engineers the codons of a protein such that it will include long substrings of codons that appear in the host coding sequences, improving its adaptation to a new host's gene expression machinery. We demonstrate the applicability of the new approach for analysing and engineering heterologous genes and for analysing endogenous genes. Specifically, focusing on Escherichia coli, we show that it can exploit information that cannot be detected by conventional approaches (e.g. the CAI--Codon Adaptation Index), which only consider single codon distributions; for example, we report correlations of up to 0.67 for the ChimeraARS measure with heterologous gene expression, when the CAI yielded no correlation. [ABSTRACT FROM AUTHOR]

Summary: iMAT is an Integrative Metabolic Analysis Tool, enabling the integration of transcriptomic and proteomic data with genome-scale metabolic network models to predict enzymes' metabolic flux, based on the method previously described by Shlomi et al. The prediction of metabolic fluxes based on high-throughput molecular data sources could help to advance our understanding of cellular metabolism, since current experimental approaches are limited to measuring fluxes through merely a few dozen enzymes.Availability and Implementation: http://imat.cs.tau.ac.il/Contact: zurhadas@post.tau.ac.il; ruppin@post.tau.ac.il; tomersh@cs.technion.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Summary: The RFMapp is a graphical user interface application based on the RFM (ribosome flow model), enabling the estimation of the translation elongation rates of messenger ribonucleic acids (mRNAs) and the profile of ribosomal densities along the mRNAs, in a computationally efficient way. The RFMapp is based on the approach previously described by Reuveni et al., and unlike other traditional approaches in the field, which are mainly related to the genes' mean codon translation efficiency, the RFM additionally considers the codon order, the ribosomes' size and their order. Thus, it has been shown that RFM outperforms traditional predictors when analyzing both heterologous and endogenous genes.Availability and implementation: Distributable cross-platform application and guideline are available for download at: http://www.cs.tau.ac.il/∼tamirtul/RFM_Installers/install.htmContact: tamirtul@post.tau.ac.il [ABSTRACT FROM AUTHOR]

Alternative transcription and translation initiation multiply the number of protein isoforms in subcellular compartments without increasing the gene copy number. The Lon protease modulates protein quality control in plant organelles. Herein we show that Lon1 and Lon4 proteases evolved complementary subsets of regulatory components for dual-targeting to mitochondria and chloroplasts.Cellular homeostasis relies on components of protein quality control including chaperones and proteases. In bacteria and eukaryotic organelles, Lon proteases play a critical role in removing irreparably damaged proteins and thereby preventing the accumulation of deleterious degradation-resistant aggregates. Gene expression, live-cell imaging, immunobiochemical, and functional complementation approaches provide conclusive evidence for Lon1 dual-targeting to chloroplasts and mitochondria. Dual-organellar deposition of Lon1 isoforms depends on both transcriptional regulation and alternative translation initiation via leaky ribosome scanning from the first AUG sequence context that deviates extensively from the optimum Kozak consensus. Organelle-specific Lon1 targeting results in partial complementation of Arabidopsis lon1-1 mutants, whereas full complementation is solely accomplished by dual-organellar targeting. Both the optimal and non-optimal AUG sequence contexts are functional in yeast and facilitate leaky ribosome scanning complementing the pim1 phenotype when the mitochondrial presequence is used. Bioinformatic search identified a limited number of Arabidopsis genes with Lon1-type dual-targeting sequence organization. Lon4, the paralog of Lon1, has an ambiguous presequence likely evolved from the twin presequences of an ancestral Lon1-like gene, generating a single dual-targeted protein isoform. We postulate that Lon1 and its subfunctional paralog Lon4 evolved complementary subsets of transcriptional and posttranscriptional regulatory components responsive to environmental cues for dual-organellar targeting. [ABSTRACT FROM PUBLISHER]