Tag Archives: database

lnCeDB: Database of Human Long Noncoding RNA Acting as Competing Endogenous RNA

database

Long noncoding RNA (lncRNA) influences post-transcriptional regulation by interfering with the microRNA (miRNA) pathways, acting as competing endogenous RNA (ceRNA). These lncRNAs have miRNA responsive elements (MRE) in them, and control endogenous miRNAs available for binding with their target mRNAs, thus reducing the repression of these mRNAs.

lnCeDB provides a database of human lncRNAs (from GENCODE 19 version) that can potentially act as ceRNAs. The putative mRNA targets of human miRNAs and the targets mapped to AGO clipped regions are collected from TargetScan and StarBase respectively. The lncRNA targets of human miRNAs (up to GENCODE 11) are downloaded from miRCode database. miRNA targets on the rest of the GENCODE 19 lncRNAs are predicted by our algorithm for finding seed-matched target sites. These putative miRNA-lncRNA interactions are mapped to the Ago interacting regions within lncRNAs. To find out the likelihood of an lncRNA-mRNA pair for actually being ceRNA we take recourse to two methods. First, a ceRNA score is calculated from the ratio of the number of shared MREs between the pair with the total number of MREs of the individual candidate gene. Second, the P-value for each ceRNA pair is determined by hypergeometric test using the number of shared miRNAs between the ceRNA pair against the number of miRNAs interacting with the individual RNAs. Typically, in a pair of RNAs being targeted by common miRNA(s), there should be a correlation of expression so that the increase in level of one ceRNA results in the increased level of the other ceRNA. Near-equimolar concentration of the competing RNAs is associated with more profound ceRNA effect. In lnCeDB one can not only browse for lncRNA-mRNA pairs having common targeting miRNAs, but also compare the expression of the pair in 22 human tissues to estimate the chances of the pair for actually being ceRNAs.

Availability: Downloadable freely from http://gyanxet-beta.com/lncedb/.

Das S, Ghosal S, Sen R, Chakrabarti J (2014) lnCeDB: Database of Human Long Noncoding RNA Acting as Competing Endogenous RNA. PLoS ONE 9(6): e98965. [article]

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lncRNAMap: A map of putative regulatory functions in the long non-coding transcriptome

lncRNA

lncRNAMap is an integrated and comprehensive database relating to exploration of the putative regulatory functions of human lncRNAs with two mechanisms of regulation, by encoding siRNAs and by acting as miRNA decoys. To investigate lncRNAs producing siRNAs that regulate protein-coding genes, lncRNAMap integrated small RNAs (sRNAs) that were supported by publicly available deep sequencing data from various sRNA libraries and constructed lncRNA-derived siRNA-target interactions. In addition, lncRNAMap demonstrated that lncRNAs can act as targets for miRNAs that would otherwise regulate protein-coding genes. Previously studies indicated that intergenic lncRNAs (lincRNAs) either positive or negative regulated neighboring genes, therefore, lncRNAMap surveyed neighboring genes within a 1Mb distance from the genomic location of specific lncRNAs and provided the expression profiles of lncRNA and its neighboring genes. The gene expression profiles may supply the relationship between lncRNA and its neighboring genes.

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lncRNAMap is a powerful user-friendly platform for the investigation of putative regulatory functions of human lncRNAs with producing siRNAs and acting as miRNA decoy.

Availability – lncRNAMap is freely available on the web at http://lncRNAMap.mbc.nctu.edu.tw/

  • Chan WL, Huang HD, Chang JG. (2014) lncRNAMap: A map of putative regulatory functions in the long non-coding transcriptome. Comput Biol Chem [Epub ahead of print]. [abstract]

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  • lincRNAs regulate miRNAs

DIANA-LncBase – experimentally verified and computationally predicted microRNA targets on long non-coding RNAs

diana-lncbase

Recently, the attention of the research community has been focused on long non-coding RNAs (lncRNAs) and their physiological/pathological implications. As the number of experiments increase in a rapid rate and transcriptional units are better annotated, databases indexing lncRNA properties and function gradually become essential tools to this process. Aim of DIANA-LncBase (www.microrna.gr/LncBase) is to reinforce researchers’ attempts and unravel microRNA (miRNA)-lncRNA putative functional interactions. This study provides, for the first time, a comprehensive annotation of miRNA targets on lncRNAs. DIANA-LncBase hosts transcriptome-wide experimentally verified and computationally predicted miRNA recognition elements (MREs) on human and mouse lncRNAs. The analysis performed includes an integration of most of the available lncRNA resources, relevant high-throughput HITS-CLIP and PAR-CLIP experimental data as well as state-of-the-art in silico target predictions. The experimentally supported entries available in DIANA-LncBase correspond to >5000 interactions, while the computationally predicted interactions exceed 10 million. DIANA-LncBase hosts detailed information for each miRNA-lncRNA pair, such as external links, graphic plots of transcripts’ genomic location, representation of the binding sites, lncRNA tissue expression as well as MREs conservation and prediction scores.

Availability – DIANA-LncBase is available at:  www.microrna.gr/LncBase

Paraskevopoulou MD, Georgakilas G, Kostoulas N, Reczko M, Maragkakis M, Dalamagas TM, Hatzigeorgiou AG. (2012) DIANA-LncBase: experimentally verified and computationally predicted microRNA targets on long non-coding RNAs. Nucleic Acids Res [Epub ahead of print]. [article]

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  • diana-lncbase
  • mirna lncrna database prediction
  • long noncoding rna mirna binding
  • mirna binding site prediction
  • miRNA target prediction 2012

LncRNADisease – a database for long-non-coding RNA-associated diseases

lncrnadisease

In recent years, a large number of lncRNAs have been identified and increasing evidence shows that lncRNAs play critical roles in various biological processes. Therefore, the dysfunctions of lncRNAs are associated with a wide range of diseases. It thus becomes important to understand lncRNAs’ roles in diseases and to identify candidate lncRNAs for disease diagnosis, treatment and prognosis. For this purpose, a high-quality lncRNA-disease association database would be extremely beneficial. Here, scientists at Peking University, China describe the LncRNADisease database that collected and curated approximately 480 entries of experimentally supported lncRNA-disease associations, including 166 diseases. LncRNADisease also curated 478 entries of lncRNA interacting partners at various molecular levels, including protein, RNA, miRNA and DNA. Moreover, they annotated lncRNA-disease associations with genomic information, sequences, references and species. The scientists normalized the disease name and the type of lncRNA dysfunction and provided a detailed description for each entry. Finally, they developed a bioinformatic method to predict novel lncRNA-disease associations and integrated the method and the predicted associated diseases of 1564 human lncRNAs into the database.

LncRNADisease – a long-non-coding RNA (lncRNA) and disease association database, is publicly accessible at http://cmbi.bjmu.edu.cn/lncrnadisease

Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X, Zhang Q, Yan G, Cui Q. (2012) LncRNADisease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res [Epub ahead of print]. [article]

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ChIPBase: decoding the transcriptional regulation of microRNA and lncRNA genes from ChIP-Seq data

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microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and represent two classes of important non-coding RNAs in eukaryotes. Although these non-coding RNAs have been implicated in organismal development and in various human diseases, surprisingly little is known about their transcriptional regulation. Recent advances in chromatin immunoprecipitation with next-generation DNA sequencing (ChIP-Seq) have provided methods of detecting transcription factor binding sites (TFBSs) with unprecedented sensitivity. In this study, we describe ChIPBase (http://deepbase.sysu.edu.cn/chipbase/), a novel database that we have developed to facilitate the comprehensive annotation and discovery of transcription factor binding maps and transcriptional regulatory relationships of miRNAs and lncRNAs from ChIP-Seq data.

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  • dna immunoprecipitation microRna
  • miRna clip