microTSS: accurate microRNA transcription start site identification reveals a significant number of divergent pri-miRNAs

Γεωργακίλας, Γεώργιος; Vlachos, Ioannis S.; Paraskevopoulou, Maria D.; Yang, Peter; Zhang, Yuhong; Economides, Aris N.; Hatzigeorgiou, Artemis G.

doi:10.1038/ncomms6700

Cited by 69 publications

(60 citation statements)

References 43 publications

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“…Morton et al (2014) provide a machine-learning based plant study addressing miRNA TSSs as a subcategory of Pol II TSSs. The most recent whole-genome prediction efforts in animals (Bhattacharyya et al, 2012;Georgakilas et al, 2014) focus predominantly on data such as histone modifications, although one can train a remarkably successful TSS prediction model based on sequence alone for Pol II TSSs (Morton et al, 2015); sequence-only based models are particularly useful in organisms where epigenetic data sets are still sparse. The overall machine learning paradigm is to first identify a training set composed of representative TSS locations (in case of miRNAs this may come from other Pol II genes) and non-TSS locations.…”

Section: Using Machine Learning To Identify Elements Predictive Of Trmentioning

confidence: 99%

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

et al. 2016

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ORCID IDs: 0000-0001-6793-6151 (M.M.); 0000-0002-0105-6431 (S.A.F.)RNA Polymerase II (Pol II) regulatory cascades involving transcription factors (TFs) and their targets orchestrate the genetic circuitry of every eukaryotic organism. In order to understand how these cascades function, they can be dissected into small genetic networks, each containing just a few Pol II transcribed genes, that generate specific signal-processing outcomes. Small RNA regulatory circuits involve direct regulation of a small RNA by a TF and/or direct regulation of a TF by a small RNA and have been shown to play unique roles in many organisms. Here, we will focus on small RNA regulatory circuits containing Pol II transcribed microRNAs (miRNAs). While the role of miRNA-containing regulatory circuits as modular building blocks for the function of complex networks has long been on the forefront of studies in the animal kingdom, plant studies are poised to take a lead role in this area because of their advantages in probing transcriptional and posttranscriptional control of Pol II genes. The relative simplicity of tissue-and cell-type organization, miRNA targeting, and genomic structure make the Arabidopsis thaliana plant model uniquely amenable for small RNA regulatory circuit studies in a multicellular organism. In this Review, we cover analysis, tools, and validation methods for probing the component interactions in miRNA-containing regulatory circuits. We then review the important roles that plant miRNAs are playing in these circuits and summarize methods for the identification of small genetic circuits that strongly influence plant function. We conclude by noting areas of opportunity where new plant studies are imminently needed.

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Section: Using Machine Learning To Identify Elements Predictive Of Trmentioning

confidence: 99%

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

et al. 2016

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“…Previous studies have systematically identified genomic locations of the promoters and transcription start sites (TSSs) of miRNAs by integrating chromatin signatures such as H3K4me3 histone modifications, nucleosome position, cap analysis of gene expression (CAGE) tags, and high-throughput TSS sequencing (TSS-Seq) (Marson et al 2008;Ozsolak et al 2008;Megraw et al 2009;Chien et al 2011;Marsico et al 2013;Georgakilas et al 2014;Xiao et al 2014). Nevertheless, while providing valuable information regarding the boundaries of miRNA transcription units, these approaches do not provide annotation of the often complex splicing patterns of miRNA primary transcripts, and thus provide an incomplete picture of miRNA gene structure.…”

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confidence: 99%

Genome-wide annotation of microRNA primary transcript structures reveals novel regulatory mechanisms

et al. 2015

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Precise regulation of microRNA (miRNA) expression is critical for diverse physiologic and pathophysiologic processes. Nevertheless, elucidation of the mechanisms through which miRNA expression is regulated has been greatly hindered by the incomplete annotation of primary miRNA (pri-miRNA) transcripts. While a subset of miRNAs are hosted in protein-coding genes, the majority of pri-miRNAs are transcribed as poorly characterized noncoding RNAs that are 10's to 100's of kilobases in length and low in abundance due to efficient processing by the endoribonuclease DROSHA, which initiates miRNA biogenesis. Accordingly, these transcripts are poorly represented in existing RNA-seq data sets and exhibit limited and inaccurate annotation in current transcriptome assemblies. To overcome these challenges, we developed an experimental and computational approach that allows genome-wide detection and mapping of pri-miRNA structures. Deep RNA-seq in cells expressing dominant-negative DROSHA resulted in much greater coverage of pri-miRNA transcripts compared with standard RNA-seq. A computational pipeline was developed that produces highly accurate pri-miRNA assemblies, as confirmed by extensive validation. This approach was applied to a panel of human and mouse cell lines, providing pri-miRNA transcript structures for 1291/1871 human and 888/1181 mouse miRNAs, including 594 human and 425 mouse miRNAs that fall outside protein-coding genes. These new assemblies uncovered unanticipated features and new potential regulatory mechanisms, including links between pri-miRNAs and distant protein-coding genes, alternative pri-miRNA splicing, and transcripts carrying subsets of miRNAs encoded by polycistronic clusters. These results dramatically expand our understanding of the organization of miRNA-encoding genes and provide a valuable resource for the study of mammalian miRNA regulation.

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“…The identifi ed interactions can be accessed through the accompanying link ( 5 ). miRPath v3.0 offers numerous options: users can select the analysis mode ( 6 ), use of FDR or conservative statistics ( 7 ), thresholds ( 8 ), or to employ empirical or hypergeometric distributions ( 9 ). Advanced visualizations are created in high resolution ( 10 ).…”

Section: Figmentioning

confidence: 99%

“…Requested graphs are shown by pressing the "Graphs" button ( 8 ). The regulator identifi cation (miRNAs or TFs ) modules can be directly invoked following a parallel miRNA and mRNA differential expression analysis ( 9 ). Top results can be exported to miRPath for further functional investigation ( 10 ).…”

Section: Selecting Candidate Mirnas For Downstream Studies From Ngs Dmentioning

confidence: 99%

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Functional Analysis of miRNAs Using the DIANA Tools Online Suite

Vlachos

Hatzigeorgiou

2016

Methods in Molecular Biology

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microRNAs (miRNAs) are central regulators of gene expression. They are actively studied for their involvement in numerous physiological and pathological conditions but also as diagnostic biomarkers or promising therapeutic targets. The increased complexity of the miRNA interactomes hinders straightforward interpretation of miRNA expression differences between states and conditions. To this end, functional analysis web servers process and combine experimental and in silico data, enabling researchers to uncover targeted pathways and transcriptional mechanisms that are hidden within numerous interactions and vast expression datasets. DIANA-tools ( www.microrna.gr ) is a web server hosting state-of-the-art utilities and databases for miRNA functional investigation. Available utilities cover a wide scope of different needs and research scenarios, rendering DIANA website a one-stop-shop for miRNA analyses. The most commonly utilized databases and algorithms include DIANA-microT-CDS, DIANA-TarBase v7.0, DIANA-lncBase v2.0, DIANA-miRGen v3.0, DIANA-miRPath v3.0, and DIANA-mirExTra v2.0.In the presented protocol, we will utilize different online tools in order to explore miRNA functions and to identify probable targets of interest for downstream analyses and wet lab experiments. The combined use of different applications from the DIANA suite can shed light to numerous different aspects of miRNA regulation and regulatory function, without the necessity for extensive bioinformatics expertise or computational infrastructure.

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microTSS: accurate microRNA transcription start site identification reveals a significant number of divergent pri-miRNAs

Cited by 69 publications

References 43 publications

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

Genome-wide annotation of microRNA primary transcript structures reveals novel regulatory mechanisms

Functional Analysis of miRNAs Using the DIANA Tools Online Suite

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