99,364 research outputs found

    Multifractal characterisation of length sequences of coding and noncoding segments in a complete genome

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    The coding and noncoding length sequences constructed from a complete genome are characterised by multifractal analysis. The dimension spectrum DqD_{q} and its derivative, the 'analogous' specific heat CqC_{q}, are calculated for the coding and noncoding length sequences of bacteria, where qq is the moment order of the partition sum of the sequences. From the shape of the % D_{q} and CqC_{q} curves, it is seen that there exists a clear difference between the coding/noncoding length sequences of all organisms considered and a completely random sequence. The complexity of noncoding length sequences is higher than that of coding length sequences for bacteria. Almost all DqD_{q} curves for coding length sequences are flat, so their multifractality is small whereas almost all DqD_{q} curves for noncoding length sequences are multifractal-like. We propose to characterise the bacteria according to the types of the CqC_{q} curves of their noncoding length sequences.Comment: 15 pages with 5 figures, Latex, Accepted for publication in Physica

    Time series model based on global structure of complete genome

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    A time series model based on the global structure of the complete genome is proposed. Three kinds of length sequences of the complete genome are considered. The correlation dimensions and Hurst exponents of the length sequences are calculated. Using these two exponents, some interesting results related to the problem of classification and evolution relationship of bacteria are obtained.Comment: 11 pages with 3 figures and 2 tables, Chaos, Solitons and Fractals (Accepted for publications

    Profiling of RNAs from Human Islet-Derived Exosomes in a Model of Type 1 Diabetes

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    Type 1 diabetes (T1D) is characterized by the immune-mediated destruction of insulin-producing islet β cells. Biomarkers capable of identifying T1D risk and dissecting disease-related heterogeneity represent an unmet clinical need. Toward the goal of informing T1D biomarker strategies, we profiled coding and noncoding RNAs in human islet-derived exosomes and identified RNAs that were differentially expressed under proinflammatory cytokine stress conditions. Human pancreatic islets were obtained from cadaveric donors and treated with/without IL-1β and IFN-γ. Total RNA and small RNA sequencing were performed from islet-derived exosomes to identify mRNAs, long noncoding RNAs, and small noncoding RNAs. RNAs with a fold change ≥1.3 and a p-value <0.05 were considered as differentially expressed. mRNAs and miRNAs represented the most abundant long and small RNA species, respectively. Each of the RNA species showed altered expression patterns with cytokine treatment, and differentially expressed RNAs were predicted to be involved in insulin secretion, calcium signaling, necrosis, and apoptosis. Taken together, our data identify RNAs that are dysregulated under cytokine stress in human islet-derived exosomes, providing a comprehensive catalog of protein coding and noncoding RNAs that may serve as potential circulating biomarkers in T1D

    A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

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    Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer

    A Note on Zipf's Law, Natural Languages, and Noncoding DNA regions

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    In Phys. Rev. Letters (73:2, 5 Dec. 94), Mantegna et al. conclude on the basis of Zipf rank frequency data that noncoding DNA sequence regions are more like natural languages than coding regions. We argue on the contrary that an empirical fit to Zipf's ``law'' cannot be used as a criterion for similarity to natural languages. Although DNA is a presumably an ``organized system of signs'' in Mandelbrot's (1961) sense, an observation of statistical features of the sort presented in the Mantegna et al. paper does not shed light on the similarity between DNA's ``grammar'' and natural language grammars, just as the observation of exact Zipf-like behavior cannot distinguish between the underlying processes of tossing an MM sided die or a finite-state branching process.Comment: compressed uuencoded postscript file: 14 page

    T-ALL and thymocytes : a message of noncoding RNAs

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    In the last decade, the role for noncoding RNAs in disease was clearly established, starting with microRNAs and later expanded towards long noncoding RNAs. This was also the case for T cell acute lymphoblastic leukemia, which is a malignant blood disorder arising from oncogenic events during normal T cell development in the thymus. By studying the transcriptomic profile of protein-coding genes, several oncogenic events leading to T cell acute lymphoblastic leukemia (T-ALL) could be identified. In recent years, it became apparent that several of these oncogenes function via microRNAs and long noncoding RNAs. In this review, we give a detailed overview of the studies that describe the noncoding RNAome in T-ALL oncogenesis and normal T cell development

    The fate of Arabidopsis thaliana homeologous CNSs and their motifs in the Paleohexaploid Brassica rapa.

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    Following polyploidy, duplicate genes are often deleted, and if they are not, then duplicate regulatory regions are sometimes lost. By what mechanism is this loss and what is the chance that such a loss removes function? To explore these questions, we followed individual Arabidopsis thaliana-A. thaliana conserved noncoding sequences (CNSs) into the Brassica ancestor, through a paleohexaploidy and into Brassica rapa. Thus, a single Brassicaceae CNS has six potential orthologous positions in B. rapa; a single Arabidopsis CNS has three potential homeologous positions. We reasoned that a CNS, if present on a singlet Brassica gene, would be unlikely to lose function compared with a more redundant CNS, and this is the case. Redundant CNSs go nondetectable often. Using this logic, each mechanism of CNS loss was assigned a metric of functionality. By definition, proved deletions do not function as sequence. Our results indicated that CNSs that go nondetectable by base substitution or large insertion are almost certainly still functional (redundancy does not matter much to their detectability frequency), whereas those lost by inferred deletion or indels are approximately 75% likely to be nonfunctional. Overall, an average nondetectable, once-redundant CNS more than 30 bp in length has a 72% chance of being nonfunctional, and that makes sense because 97% of them sort to a molecular mechanism with deletion in its description, but base substitutions do cause loss. Similarly, proved-functional G-boxes go undetectable by deletion 82% of the time. Fractionation mutagenesis is a procedure that uses polyploidy as a mutagenic agent to genetically alter RNA expression profiles, and then to construct testable hypotheses as to the function of the lost regulatory site. We show fractionation mutagenesis to be a deletion machine in the Brassica lineage

    RNA regulation of lipotoxicity and metabolic stress

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    Noncoding RNAs are an emerging class of nonpeptide regulators of metabolism. Metabolic diseases and the altered metabolic environment induce marked changes in levels of microRNAs and long noncoding RNAs. Furthermore, recent studies indicate that a growing number of microRNAs and long noncoding RNAs serve as critical mediators of adaptive and maladaptive responses through their effects on gene expression. The metabolic environment also has a profound impact on the functions of classes of noncoding RNAs that have been thought primarily to subserve housekeeping functions in cells—ribosomal RNAs, transfer RNAs, and small nucleolar RNAs. Evidence is accumulating that these RNAs are also components of an integrated cellular response to the metabolic milieu. This Perspective discusses the different classes of noncoding RNAs and their contributions to the pathogenesis of metabolic stress
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