Dataset Information

Genetic variability of microRNA regulome in human.

ABSTRACT: MicroRNAs are currently being extensively studied due to their important role as post-transcriptional regulators. During miRNA biogenesis, precursors undergo two cleavage steps performed by Drosha-DGCR8 (Microprocessor) cleaving of pri-miRNA to produce pre-miRNA and Dicer-mediated cleaving to create mature miRNA. Genetic variants within human miRNA regulome have been shown to influence miRNA expression, target interaction and to affect the phenotype. In this study, we reviewed the literature, existing bioinformatics tools and catalogs associated with polymorphic miRNA regulome, and organized them into four categories: (1) polymorphisms located within miRNA genes (miR-SNPs), (2) transcription factor-binding sites/miRNA regulatory regions (miR-rSNPs), (3) miRNA target sites (miR-TS-SNPs), and 4. miRNA silencing machinery (miR-SM-SNPs). Since the miR-SM-SNPs have not been systematically studied yet, we have collected polymorphisms associated with miRNA silencing machinery. We have developed two catalogs containing genetic variability within: (1) genes encoding three main catalytic components of the silencing machinery, DROSHA, DGCR8, and DICER1; (2) miRNA genes itself, overlapping Drosha and Dicer cleavage sites. The developed resource of polymorphisms is available online (http://www.integratomics-time.com/miRNA-regulome) and will be useful for further functional studies and development of biomarkers associated with diseases and phenotypic traits.

SUBMITTER: Obsteter J

PROVIDER: S-EPMC4299713 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Genetic variability of microRNA regulome in human.

Obsteter Jana J Dovc Peter P Kunej Tanja T

Molecular genetics & genomic medicine 20140915 1

MicroRNAs are currently being extensively studied due to their important role as post-transcriptional regulators. During miRNA biogenesis, precursors undergo two cleavage steps performed by Drosha-DGCR8 (Microprocessor) cleaving of pri-miRNA to produce pre-miRNA and Dicer-mediated cleaving to create mature miRNA. Genetic variants within human miRNA regulome have been shown to influence miRNA expression, target interaction and to affect the phenotype. In this study, we reviewed the literature, ex ...[more]

PMID: 25629077

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Project description:BACKGROUND: Transcription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studied on a per disease basis, and no current resources provide a global overview of the relations between transcription factors and disease. Furthermore, existing pipelines for related large-scale analysis are tailored for particular sources of input data, and there is a need for generic methodology for integrating complementary sources of genomic information. RESULTS: We here present a large-scale analysis of multiple diseases versus multiple transcription factors, with a global map of over-and under-representation of 446 transcription factors in 1010 diseases. This map, referred to as the differential disease regulome, provides a first global statistical overview of the complex interrelationships between diseases, genes and controlling elements. The map is visualized using the Google map engine, due to its very large size, and provides a range of detailed information in a dynamic presentation format.The analysis is achieved through a novel methodology that performs a pairwise, genome-wide comparison on the cartesian product of two distinct sets of annotation tracks, e.g. all combinations of one disease and one TF.The methodology was also used to extend with maps using alternative data sets related to transcription and disease, as well as data sets related to Gene Ontology classification and histone modifications. We provide a web-based interface that allows users to generate other custom maps, which could be based on precisely specified subsets of transcription factors and diseases, or, in general, on any categorical genome annotation tracks as they are improved or become available. CONCLUSION: We have created a first resource that provides a global overview of the complex relations between transcription factors and disease. As the accuracy of the disease regulome depends mainly on the quality of the input data, forthcoming ChIP-seq based binding data for many TFs will provide improved maps. We further believe our approach to genome analysis could allow an advance from the current typical situation of one-time integrative efforts to reproducible and upgradable integrative analysis. The differential disease regulome and its associated methodology is available at http://hyperbrowser.uio.no.

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Genetic variability of microRNA regulome in human.

Publications

Genetic variability of microRNA regulome in human.

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