15,692 research outputs found

    Network-based approaches to explore complex biological systems towards network medicine

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    Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes

    In silico prediction of housekeeping long intergenic non-coding RNAs reveals HKlincR1 as an essential player in lung cancer cell survival

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    Prioritising long intergenic noncoding RNAs (lincRNAs) for functional characterisation is a significant challenge. Here we applied computational approaches to discover lincRNAs expected to play a critical housekeeping (HK) role within the cell. Using the Illumina Human BodyMap RNA sequencing dataset as a starting point, we first identified lincRNAs ubiquitously expressed across a panel of human tissues. This list was then further refined by reference to conservation score, secondary structure and promoter DNA methylation status. Finally, we used tumour expression and copy number data to identify lincRNAs rarely downregulated or deleted in multiple tumour types. The resulting list of candidate essential lincRNAs was then subjected to co-expression analyses using independent data from ENCODE and The Cancer Genome Atlas (TCGA). This identified a substantial subset with a predicted role in DNA replication and cell cycle regulation. One of these, HKlincR1, was selected for further characterisation. Depletion of HKlincR1 affected cell growth in multiple lung cancer cell lines, and led to disruption of genes involved in cell growth and viability. In addition, HKlincR1 expression was correlated with overall survival in lung adenocarcinoma patients. Our in silico studies therefore reveal a set of housekeeping noncoding RNAs of interest both in terms of their role in normal homeostasis, and their relevance in tumour growth and maintenance

    Epigenome Modifying Tools In Asthma

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    Post-transcriptional Regulation through Long Noncoding RNAs (lncRNAs)

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    This book is a collection of eight articles, of which seven are reviews and one is a research paper, that together form a Special Issue that describes the roles that long noncoding RNAs (lncRNA) play in gene regulation at a post-transcriptional level

    microRNAs of parasitic helminths – identification, characterization and potential as drug targets

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    microRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation. They were first identified in the free-living nematode Caenorhabditis elegans, where the miRNAs lin-4 and let-7 were shown to be essential for regulating correct developmental progression. The sequence of let-7 was subsequently found to be conserved in higher organisms and changes in expression of let-7, as well as other miRNAs, are associated with certain cancers, indicating important regulatory roles. Some miRNAs have been shown to have essential functions, but the roles of many are currently unknown. With the increasing availability of genome sequence data, miRNAs have now been identified from a number of parasitic helminths, by deep sequencing of small RNA libraries and bioinformatic approaches. While some miRNAs are widely conserved in a range of organisms, others are helminth-specific and many are novel to each species. Here we review the potential roles of miRNAs in regulating helminth development, in interacting with the host environment and in development of drug resistance. Use of fluorescently-labeled small RNAs demonstrates uptake by parasites, at least in vitro. Therefore delivery of miRNA inhibitors or mimics has potential to alter miRNA activity, providing a useful tool for probing the roles of miRNAs and suggesting novel routes to therapeutics for parasite control

    The interplay between viral-derived miRNAs and host immunity during infection

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    MicroRNAs are short non-coding RNAs that play a crucial role in the regulation of gene expression during cellular processes. The host-encoded miRNAs are known to modulate the antiviral defense during viral infection. In the last decade, multiple DNA and RNA viruses have been shown to produce miRNAs known as viral miRNAs (v-miRNAs) so as to evade the host immune response. In this review, we highlight the origin and biogenesis of viral miRNAs during the viral lifecycle. We also explore the role of viral miRNAs in immune evasion and hence in maintaining chronic infection and disease. Finally, we offer insights into the underexplored role of viral miRNAs as potential targets for developing therapeutics for treating complex viral diseases

    Non-Coding RNAs and Cancer

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