microrna targets

Single nucleotide polymorphisms (SNPs) can lead to the susceptibility and onset of diseases through their effects on gene expression at the posttranscriptional level. Recent findings indicate that SNPs could create, destroy, or modify the efficiency of miRNA binding to the 3’UTR of a gene, resulting in gene dysregulation. With the rapidly growing number of published disease-associated SNPs (dSNPs), there is a strong need for resources specifically recording dSNPs on the 3’UTRs and their nucleotide distance from miRNA target sites. Bruno et al. from the Center for Computational Research SUNY at the University of Buffalo presents miRdSNP, a database incorporating three important areas of dSNPs, miRNA target sites, and diseases.

miRdSNP provides a unique database of dSNPs on the 3’UTRs of human genes manually curated from PubMed. The current release includes 786 dSNP-disease associations for 630 unique dSNPs and 204 disease types. miRdSNP annotates genes with experimentally confirmed targeting by miRNAs and indexes miRNA target sites predicted by TargetScan and PicTar as well as potential miRNA target sites newly generated by dSNPs. A robust web interface and search tools are provided for [click to continue…]

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from Nature Asia-Pacific.com

A sensitive and reproducible method to validate several hundred microRNA target genes in one experiment is described online this week in Nature Methods. These results give a better understanding of how these target genes could be regulated.

MicroRNAs are short RNA molecules that do not encode a protein but are crucial in regulating gene expression by blocking translation or marking the RNA for degradation. The targets of specific microRNAs can be predicted by computational algorithms, but experimental approaches to validate the predicted targets at a large scale are needed.

Michael Hengartner and colleagues report a proteomics approach to follow up on computationally predicted microRNA target genes in the roundworm Caenorhabditis elegans. To determine which genes are regulated by a specific microRNA known as let-7, the researchers compared protein levels in normal worms to protein levels in mutant worms in which let-7 levels were reduced. They used a highly sensitive detection technique called selected reaction monitoring (SRM) mass spectrometry in combination with a quantitative method, isotope-coded affinity tagging (ICAT). When the protein levels changed in the mutant worms compared to the normal worms, this indicated that the gene was indeed regulated by let-7.

The general approach should be readily adaptable to validate the predicted target genes of any microRNA in any organism. (read more… )

Jovanovic M, Reiter L, Picotti P, Lange V, Bogan E, A Hurschler B, Blenkiron C, J Lehrbach N, C Ding X, Weiss M, P Schrimpf S, A Miska E, Großhans H, Aebersold R, O Hengartner M. (2010) A quantitative targeted proteomics approach to validate predicted microRNA targets in C. elegans. Nat Methods [Epub ahead of print].  [abstract]

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from Epigenie blog – May 5, 2010 

Up to now, all miRNAs have been assumed to work the same way when it comes to finding their mRNA targets, but a new paper shows that miRNAs behave more like rugged individualists in how they function.

Researchers from the University of Kentucky broke out the RIP-Chip method (Argonaute, aka AGO, co-IP assays coupled with downstream microarray analysis) in H4 glioneuronal cells transfected with certain miRNAs to get an idea of what each miRNA is targeting and how. The RIP-Chip technique showed hard evidence of what mRNAs are targeted, and even the proteins involved in the microribonucleoparticles (miRNPs) for each miRNA tested (miR-107, miR-124, miR-128, and miR-320). After looking over targets of each miRNA, here’s what they found:

  • miR-124 displayed a standard targeting profile: using a 5’ seed sequence to target a 3’ mRNA UTR.
  • miR-107, however, targeted the open reading frame (ORF) regions, and not the 3’UTRs, of its targets.
  • miR-128 and miR-320 were shown to utilize more of a mixture of 5’ and 3’ seed regions to bind targets.

Sure, the authors only looked at one cell-line, and RIP-Chip assays can only asses non-degraded targets, but the take-home message is the same: miRNAs are like snowflakes, every one is unique. So, the only way to really know what your favorite miRNA is targeting, is to go test it out.

Get zeroed in on all the miRNA targeting details in RNA Biology, May 2010.

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A new web server called TAPIR, designed for the prediction of plant microRNA targets. The server offers the possibility to search for plant miRNA targets using a fast and a precise algorithm. The precise option is much slower but guarantees to find less perfectly paired miRNA – target duplexes. Furthermore, the precise option allows the prediction of target mimics, which are characterized by a miRNA – target duplex having a large loop, making them undetectable by traditional tools.

The TAPIR web server can be accessed at:  http://bioinformatics.psb.ugent.be/webtools/tapir

Bonnet E, He Y, Billiau K, Van de Peer Y. (2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics [Epub ahead of print]. [abstract]

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