The synthesis and turnover rates of the two 12 S and 16 S mt rRNAs and of the mt mRNAs for subunits I and III of cytochrome oxidase have been determined by measuring the kinetics of incorporation of t3H]uridine in the mtRNA of rat hepatocytes. All the RNA species examined have approximately the same turnover (tl -100 min) and therefore the rate of synthesis, which is about IO-times higher for the rRNAs, seer& to be the factor responsible for the different mt rRNA and mRNA steady-state levels.mtRNA synthesis rate; Turnover rate; Transcription regulation; (Rat hepatocyte)
RNA editing is a post-transcriptional/co-transcriptional molecular phenomenon whereby a genetic message is modified from the corresponding DNA template by means of substitutions, insertions, and/or deletions. It occurs in a variety of organisms and different cellular locations through evolutionally and biochemically unrelated proteins. RNA editing has a plethora of biological effects including the modulation of alternative splicing and fine-tuning of gene expression. RNA editing events by base substitutions can be detected on a genomic scale by NGS technologies through the REDItools package, an ad hoc suite of Python scripts to study RNA editing using RNA-Seq and DNA-Seq data or RNA-Seq data alone. REDItools implement effective filters to minimize biases due to sequencing errors, mapping errors, and SNPs. The package is freely available at Google Code repository (http://code.google.com/p/reditools/) and released under the MIT license. In the present unit we show three basic protocols corresponding to three main REDItools scripts. C 2015 by John Wiley & Sons, Inc. Keywords: RNA editing r RNA-Seq r DNA-Seq r transcriptomics r NGS r next-generation sequencing r REDItools How to cite this article: Picardi, E., D'Erchia, A.M., Montalvo, A., and Pesole, G. 2015. Using REDItools to Detect RNA Editing Events in NGS Datasets.REDItoolDnaRNA.py identifies RNA editing modifications by comparing pre-aligned RNA-Seq and DNA-Seq reads from the same sample/individual. The script explores genomic positions site by site and returns a textual table containing such information as: the coverage depth, the mean quality score, the observed base distribution, the strand if available, and the list of observed substitutions as well as the frequency of variation. In the meantime, similar information is also extracted from DNA-Seq data, and is provided to exclude potential genomic SNPs. Through the workflow implemented in REDItoolDnaRna.py, individual positions can be filtered according to a variety of parameters such as: read coverage, base quality, mapping quality, reads supporting the variation, substitution type, and frequency. In addition, positions in homopolymeric regions of predefined length or in intronic sequences surrounding known splice sites can be filtered out, as well as invariant RNA-Seq positions or sites not supported by Using REDItools to detect RNA editing events in NGS datasets 12.12.2
RNA editing is an important co/post-transcriptional molecular process able to modify RNAs by nucleotide insertions/deletions or substitutions. In human, the most common RNA editing event involves the deamination of adenosine (A) into inosine (I) through the adenosine deaminase acting on RNA proteins. Although A-to-I editing can occur in both coding and non-coding RNAs, recent findings, based on RNA-seq experiments, have clearly demonstrated that a large fraction of RNA editing events alter non-coding RNAs sequences including untranslated regions of mRNAs, introns, long non-coding RNAs (lncRNAs), and low molecular weight RNAs (tRNA, miRNAs, and others). An accurate detection of A-to-I events occurring in non-coding RNAs is of utmost importance to clarify yet unknown functional roles of RNA editing in the context of gene expression regulation and maintenance of cell homeostasis. In the last few years, massive transcriptome sequencing has been employed to identify putative RNA editing changes at genome scale. Despite several efforts, the computational prediction of A-to-I sites in complete eukaryotic genomes is yet a challenging task. We have recently developed a software package, called REDItools, in order to simplify the detection of RNA editing events from deep sequencing data. In the present work, we show the potential of our tools in recovering A-to-I candidates from RNA-Seq experiments as well as guidelines to improve the RNA editing detection in non-coding RNAs, with specific attention to the lncRNAs.
In a model system consisting of highly coupled rat liver mitochondria respiring in the presence of substrate, pyruvate kinase, phosphoenolpyruvate, ATP, hexokinase and glucose, the increase in the mitochondrial concentration results in a progressive decrease in the activity of pyruvate kinase. These results are in accord with a role of pyruvate kinase as a determinant of glycolytic activity by competing with mitochondrial oxidative phosphorylation for the available ADP.The addition of adequate amounts of the amino acids, cysteine, alanine and phenylalanine, known as inhibitors of pyruvate kinase, to living Ehrlich ascites tumor cell suspensions results in a stimulation of the respiratory rate and in a decrease of the glycolytic rate of the cells. Concomitant with these changes, there is an accumulation of intracellular phosphoenolpyruvate and ADP, and a decrease in pyruvate and ATP. These results provide additional evidence for paying attention to pyruvate kinase as another key enzyme whose properties and activities may be major determinants for the control of glycolysis and the Crabtree and Pasteur effects of tumor cells.In previous studies, evidence was presented to suggest that competition for ADP between pyruvate kinase and the respiratory system of oxidative phosphorylation may exert a controlling influence upon glycolysis, and that high pyruvate kinase activity may be a major factor responsible for the high glycolytic activity characteristic of neoplasia [l, 21. In a previous report in this journal [3], we described a model system composed of intact, well-coupled rat liver mitochondria, together with variable quantities of purified rabbit muscle pyruvate kinase, and an ADP-regenerating system consisting of glucose and yeast hexokinase. In this system, the addition of increasing pyruvate kinase levels progressively lowered respiration, thus simulating the Crabtree effect; and also progressively increased the ATP/ADP ratio. In the present paper, we report data from additional experiments which show that by further manipulations of the relative activities of pyruvate kinase and mitochondria in this system, lowered rates of pyruvate formation can be induced by increasing mitochondrial respiration, thus simulating the Pasteur effect, and this is accompanied by a decreased ATP/ADP ratio.
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MitBASE is an integrated and comprehensive database of mitochondrial DNA data which collects, under a single interface, databases for Plant, Vertebrate, Invertebrate, Human, Protist and Fungal mtDNA and a Pilot database on nuclear genes involved in mitochondrial biogenesis in Saccharomyces cerevisiae. MitBASE reports all available information from different organisms and from intraspecies variants and mutants. Data have been drawn from the primary databases and from the literature; value adding information has been structured, e.g., editing information on protist mtDNA genomes, pathological information for human mtDNA variants, etc. The different databases, some of which are structured using commercial packages (Microsoft Access, File Maker Pro) while others use a flat-file format, have been integrated under ORACLE. Ad hoc retrieval systems have been devised for some of the above listed databases keeping into account their peculiarities. The database is resident at the EBI and is available at the following site: http://www3.ebi.ac.uk/Research/Mitbase/mitbas e.pl. The impact of this project is intended for both basic and applied research. The study of mitochondrial genetic diseases and mitochondrial DNA intraspecies diversity are key topics in several biotechnological fields. The database has been funded within the EU Biotechnology programme.
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