CeRNA database

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Competing endogenous RNAs (ceRNAs, also refer as miRNA sponges) hypothesis: ceRNAs regulate other RNA transcripts (e.g., PTEN) by competing for shared microRNAs. [1] They are playing important roles in developmental, physiological and pathological processes, such as cancer. Multiple classes of ncRNAs (lncRNAs, circRNAs, pseudogenes) and protein-coding mRNAs function as key ceRNAs (sponges) and to regulate the expression of mRNAs in plants and mammalian cells. [2]

This competing endogenous RNA (ceRNA) databases and resources is a compilation of databases and web portals and servers used for ceRNA prediction and ceRNA networks.

NameDescriptiontypeReferences
ceRNABaseceRNABase is designed for decoding Pan-Cancer ceRNA networks involving lncRNAs and mRNAs by analyzing 5599 tumor and normal samples and 108 CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH) datasets.database and server [3]
cefinderCompeting endogenous RNA database: predicted ceRNA candidates from genome.database [4]
ceRNAFunctionceRNAFunction is a web server to predict lncRNA and protein functions from pan-cancer ceRNA networks using 13 functional terms (including: GO, KEGG, BIOCARTA, etc.).webserver [3] [5]
CupidCupid is a method for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA (ceRNA) interactions. It is an integrative approach significantly improves on miRNA-target prediction accuracy as assessed by both mRNA and protein level measurements in breast cancer cell lines. Cupid is implemented in 3 steps: Step 1: re-evaluate candidate miRNA binding sites in 3' UTRs. Step2: interactions are predicted by integrating information about selected sites and the statistical dependency between the expression profiles of miRNA and putative targets. Step 3: Cupid assesses whether inferred targets compete for predicted miRNA regulators.software (MATLAB) [6]
HermesHermes predicts ceRNA (competing endogenous RNA) interactions from expression profiles of candidate RNAs and their common miRNA regulators using conditional mutual information.software (MATLAB) [7]
Linc2GOa human LincRNA function annotation resource based on ceRNA webserver.database [8]
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Related Research Articles

microRNA Small non-coding ribonucleic acid molecule

MicroRNA (miRNA) are small, single-stranded, non-coding RNA molecules containing 21 to 23 nucleotides. Found in plants, animals and some viruses, miRNAs are involved in RNA silencing and post-transcriptional regulation of gene expression. miRNAs base-pair to complementary sequences in mRNA molecules, then silence said mRNA molecules by one or more of the following processes:

  1. Cleavage of the mRNA strand into two pieces,
  2. Destabilization of the mRNA by shortening its poly(A) tail, or
  3. Reducing translation of the mRNA into proteins.

Cross-linking and immunoprecipitation is a method used in molecular biology that combines UV crosslinking with immunoprecipitation in order to identify RNA binding sites of proteins on a transcriptome-wide scale, thereby increasing our understanding of post-transcriptional regulatory networks. CLIP can be used either with antibodies against endogenous proteins, or with common peptide tags or affinity purification, which enables the possibility of profiling model organisms or RBPs otherwise lacking suitable antibodies.

mir-133 microRNA precursor family

mir-133 is a type of non-coding RNA called a microRNA that was first experimentally characterised in mice. Homologues have since been discovered in several other species including invertebrates such as the fruitfly Drosophila melanogaster. Each species often encodes multiple microRNAs with identical or similar mature sequence. For example, in the human genome there are three known miR-133 genes: miR-133a-1, miR-133a-2 and miR-133b found on chromosomes 18, 20 and 6 respectively. The mature sequence is excised from the 3' arm of the hairpin. miR-133 is expressed in muscle tissue and appears to repress the expression of non-muscle genes.

This microRNA database and microRNA targets databases is a compilation of databases and web portals and servers used for microRNAs and their targets. MicroRNAs (miRNAs) represent an important class of small non-coding RNAs (ncRNAs) that regulate gene expression by targeting messenger RNAs.

Degradome sequencing (Degradome-Seq), also referred to as parallel analysis of RNA ends (PARE), is a modified version of 5'-Rapid Amplification of cDNA Ends (RACE) using high-throughput, deep sequencing methods such as Illumina's SBS technology. The degradome encompasses the entire set of proteases that are expressed at a specific time in a given biological material, including tissues, cells, organisms, and biofluids. Thus, sequencing this degradome offers a method for studying and researching the process of RNA degradation. This process is used to identify and quantify RNA degradation products, or fragments, present in any given biological sample. This approach allows for the systematic identification of targets of RNA decay and provides insight into the dynamics of transcriptional and post-transcriptional gene regulation.

PAR-CLIP is a biochemical method for identifying the binding sites of cellular RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs). The method relies on the incorporation of ribonucleoside analogs that are photoreactive, such as 4-thiouridine (4-SU) and 6-thioguanosine (6-SG), into nascent RNA transcripts by living cells. Irradiation of the cells by ultraviolet light of 365 nm wavelength induces efficient crosslinking of photoreactive nucleoside–labeled cellular RNAs to interacting RBPs. Immunoprecipitation of the RBP of interest is followed by isolation of the crosslinked and coimmunoprecipitated RNA. The isolated RNA is converted into a cDNA library and is deep sequenced using next-generation sequencing technology.

StarBase is a database for decoding miRNA-mRNA, miRNA-lncRNA, miRNA-sncRNA, miRNA-circRNA, miRNA-pseudogene, protein-lncRNA, protein-ncRNA, protein-mRNA interactions, and ceRNA networks from CLIP-Seq and degradome sequencing data. StarBase provides miRFunction and ceRNAFunction web tools to predict the function of ncRNAs and protein-coding genes from the miRNA and ceRNA regulatory networks. StarBase also developed Pan-Cancer Analysis Platform to decipher Pan-Cancer Analysis Networks of lncRNAs, miRNAs, ceRNAs, and RNA-binding proteins (RBPs) by mining clinical and expression profiles of 14 cancer types from The Cancer Genome Atlas (TCGA) Data Portal.

High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) is a variant of CLIP for genome-wide mapping protein–RNA binding sites or RNA modification sites in vivo. HITS-CLIP was originally used to generate genome-wide protein-RNA interaction maps for the neuron-specific RNA-binding protein and splicing factor NOVA1 and NOVA2; since then a number of other splicing factor maps have been generated, including those for PTB, RbFox2, SFRS1, hnRNP C, and even N6-Methyladenosine (m6A) mRNA modifications.

miR-214

miR-214 is a vertebrate-specific family of microRNA precursors. The ~22 nucleotide mature miRNA sequence is excised from the precursor hairpin by the enzyme Dicer. This sequence then associates with RISC which effects RNA interference.

In molecular biology, competing endogenous RNAs regulate other RNA transcripts by competing for shared microRNAs (miRNAs). Models for ceRNA regulation describe how changes in the expression of one or multiple miRNA targets alter the number of unbound miRNAs and lead to observable changes in miRNA activity - i.e., the abundance of other miRNA targets. Models of ceRNA regulation differ greatly. Some describe the kinetics of target-miRNA-target interactions, where changes in the expression of one target species sequester one miRNA species and lead to changes in the dysregulation of the other target species. Others attempt to model more realistic cellular scenarios, where multiple RNA targets are affecting multiple miRNAs and where each target pair is co-regulated by multiple miRNA species. Some models focus on mRNA 3' UTRs as targets, and others consider long non-coding RNA targets as well. It's evident that our molecular-biochemical understanding of ceRNA regulation remains incomplete.

MicroRNA sequencing (miRNA-seq), a type of RNA-Seq, is the use of next-generation sequencing or massively parallel high-throughput DNA sequencing to sequence microRNAs, also called miRNAs. miRNA-seq differs from other forms of RNA-seq in that input material is often enriched for small RNAs. miRNA-seq allows researchers to examine tissue-specific expression patterns, disease associations, and isoforms of miRNAs, and to discover previously uncharacterized miRNAs. Evidence that dysregulated miRNAs play a role in diseases such as cancer has positioned miRNA-seq to potentially become an important tool in the future for diagnostics and prognostics as costs continue to decrease. Like other miRNA profiling technologies, miRNA-Seq has both advantages and disadvantages.

In molecular biology mir-330 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

In molecular biology mir-365 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

In molecular biology mir-744 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

In molecular biology mir-390 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

In molecular biology mir-397 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

In molecular biology mir-398 microRNA is a short RNA molecule. MicroRNAs function to regulate the expression levels of other genes by several mechanisms.

Cancer systems biology encompasses the application of systems biology approaches to cancer research, in order to study the disease as a complex adaptive system with emerging properties at multiple biological scales. Cancer systems biology represents the application of systems biology approaches to the analysis of how the intracellular networks of normal cells are perturbed during carcinogenesis to develop effective predictive models that can assist scientists and clinicians in the validations of new therapies and drugs. Tumours are characterized by genomic and epigenetic instability that alters the functions of many different molecules and networks in a single cell as well as altering the interactions with the local environment. Cancer systems biology approaches, therefore, are based on the use of computational and mathematical methods to decipher the complexity in tumorigenesis as well as cancer heterogeneity.

Transcription factors are proteins that bind genomic regulatory sites. Identification of genomic regulatory elements is essential for understanding the dynamics of developmental, physiological and pathological processes. Recent advances in chromatin immunoprecipitation followed by sequencing (ChIP-seq) have provided powerful ways to identify genome-wide profiling of DNA-binding proteins and histone modifications. The application of ChIP-seq methods has reliably discovered transcription factor binding sites and histone modification sites.

mIR141

MicroRNA 141 is a non-coding RNA molecule that in humans is encoded by the MIR141 gene.

References

  1. ↑ Salmena, L; Poliseno, L; Tay, Y; Kats, L; Pandolfi, PP (Aug 5, 2011). "A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language?". Cell. 146 (3): 353–8. doi:10.1016/j.cell.2011.07.014. PMC   3235919 . PMID   21802130.
  2. ↑ Tay, Y; Rinn, J; Pandolfi, PP (Jan 16, 2014). "The multilayered complexity of ceRNA crosstalk and competition". Nature. 505 (7483): 344–52. Bibcode:2014Natur.505..344T. doi:10.1038/nature12986. PMC   4113481 . PMID   24429633.
  3. 1 2 Li, JH; Liu, S; Zhou, H; Qu, LH; Yang, JH (Jan 1, 2014). "starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data". Nucleic Acids Research. 42 (1): D92–7. doi:10.1093/nar/gkt1248. PMC   3964941 . PMID   24297251.
  4. ↑ Sarver, AL; Subramanian, S (2012). "Competing endogenous RNA database". Bioinformation. 8 (15): 731–3. doi:10.6026/97320630008731. PMC   3449376 . PMID   23055620.
  5. ↑ Yang, J. -H.; Li, J. -H.; Shao, P.; Zhou, H.; Chen, Y. -Q.; Qu, L. -H. (2010). "StarBase: A database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data". Nucleic Acids Research. 39 (Database issue): D202–D209. doi:10.1093/nar/gkq1056. PMC   3013664 . PMID   21037263.
  6. ↑ Chiu, Hua-Sheng; Llobet-Navas, David; Yang, Xuerui; Chung, Wei-Jen; Ambesi-Impiombato, Alberto; Iyer, Archana; Kim, Hyunjae "Ryan"; Seviour, Elena G.; Luo, Zijun; Sehgal, Vasudha; Moss, Tyler; Lu, Yiling; Ram, Prahlad; Silva, José; Mills, Gordon B.; Califano, Andrea; Sumazin, Pavel (February 2015). "Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks". Genome Research. 25 (2): 257–67. doi:10.1101/gr.178194.114. PMC   4315299 . PMID   25378249.
  7. ↑ Sumazin, P; Yang, X; Chiu, HS; Chung, WJ; Iyer, A; Llobet-Navas, D; Rajbhandari, P; Bansal, M; Guarnieri, P; Silva, J; Califano, A (Oct 14, 2011). "An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma". Cell. 147 (2): 370–81. doi:10.1016/j.cell.2011.09.041. PMC   3214599 . PMID   22000015.
  8. ↑ Liu, K; Yan, Z; Li, Y; Sun, Z (Sep 1, 2013). "Linc2GO: a human LincRNA function annotation resource based on ceRNA hypothesis". Bioinformatics. 29 (17): 2221–2. doi: 10.1093/bioinformatics/btt361 . PMID   23793747.
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