miRNA – Target Prediction, Validation, and Functional Analysis

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miRNA’s regulation of genes is determined by the binding of their seed region to the target. Due to the short length of the seed region (7 nt), one miRNA may target more than one gene. Furthermore, a given gene may be regulated by multiple miRNAs. miRNA targets can be predicted using bioinformatic tools, but should always be validated experimentally.

Target Prediction

There are a wide range of bioinformatics programs which can be used to predict miRNA targets. Commonly used programs include miRanda, DIANA-microT, Targetscan, and PicTar (1)(2)(3)(4).

Some of the basic criteria used to predict a miRNA-mRNA pairing are:

  • The seed region of the miRNA demonstrates sequence complementarity to a region in the 3’UTR of the target mRNA.
  • The target site is conserved between mRNAs of different species.
  • The miRNA-mRNA duplex is thermally stable.
  • There are no secondary structures surrounding the miRNA binding site.

Different miRNA target prediction algorithms may calculate these parameters differently and consider them of varying importance. Therefore, the same miRNA when run through different target prediction programs may generate very different lists of potential targets. For this reason, the most specific method to determine likely miRNA targets is actually to examine the results of multiple target prediction programs, looking for targets that are present in all datasets (5).

miRNA targets

Figure 1 – To narrow down a list of potential miRNA targets, one can combine the results of multiple target prediction programs. The most likely targets are shared amongst all sets of results.

Tools for miRNA Research

In order to validate miRNA targets experimentally, specially-designed vectors and/or synthetic molecules may be utilized. Below we discuss the most popular tools for miRNA research, followed by an explanation of how miRNA target validation and function analyses can be carried out.

miRNA mimics and inhibitors

Figure 2 – Summary of how miRNA mimics and inhibitors function. Alone, endogenous miRNA (green strand) will bind to its target, leading to gene silencing. Mimics are synthetic RNA duplexes in which one strand is designed to mimic an endogenous miRNA. This strand (in orange) regulates its target in the same way as endogenous miRNA. miRNA inhibitors (in purple) are single-stranded oligonucleotides designed to bind a particular miRNA. miRNA inhibitors prevent the bound miRNA from interacting with its target, preventing the gene from being silenced.

3'UTR Reporter Vectors

A vector cloned with the 3’UTR of a predicted target gene downstream of a reporter such as GFP or luciferase. If a miRNA binds to the target, reporter expression should be reduced. If a miRNA does not bind, reporter expression will be unaffected. To act as a control, sometimes a variation will be cloned where the putative binding site of the miRNA is mutated.

miRNA Mimics

miRNA mimics are synthetic RNA duplexes designed to mimic the endogenous functions of the miRNA of interest. One strand is designed to represent the mature miRNA. An agomir is a mimic that has been chemically modified to be more resistant to degradation and have higher transfection efficiency.

miRNA Inhibitors

miRNA inhibitors (sometimes called antimiRs) are synthetic single-stranded oligonucleotides. They are designed with complementarity to their corresponding miRNA, so they will bind and inhibit the miRNA’s function in cells. An antagomir is an inhibitor that has been chemically modified to be more resistant to degradation and have higher transfection efficiency.

miRNA Expression Vectors

There are three types of vectors which may be used in miRNA experiments. In all cases, the cellular machinery is needed to process the transcript into mature RNA species.

The simplest are shRNA vectors, which express a short hairpin RNA (22-29 nt), usually from a Polymerase III promoter such as U6 or H1 (6). These are designed to target a specific locus, rather than to mimic a particular miRNA. These should not be confused with siRNA vectors, which express double-stranded siRNA without the hairpin loop. At abm, we employ a convergent U6 and H1 promoter system which only requires the sense siRNA sequence (22-29nt) to be cloned between the promoters for siRNA expression.

There are also precursor-expressing vectors, which express a pre-miRNA sequence from a Polymerase II promoter, such as CMV. In this case, the entire sequence surrounding the miRNA of interest is expressed, and the precursor is processed by the cell into the resulting mature miRNAs. This approach will cause both arms of the miRNA to be expressed.

Finally, there are vectors designed to express mature miRNAs, usually from a Polymerase II promoter. These vectors have the mature miRNA sequence inserted into the context of an endogenous miRNA (commonly miR-30), ensuring efficient cleavage by Dicer (7). The passenger strand sequence is often modified to make it less likely to be loaded into the RISC.

miRNA expression vectors may be transfected directly or packaged into a virus, depending on the experiment and preferred method of delivery. For stable, long term expression of a miRNA, the gene may be integrated into host DNA using a lentivirus. Transient, high levels of expression can be achieved using an AAV or adenovirus. Expression vectors also have the advantage of being able to express a reporter protein such as GFP alongside the miRNA of interest.

miRNA Inhibitor Vectors

miRNA inhibitor vectors express a transcript of the miRNA target sequence (8). miRNAs will bind to these target sequence “decoys”, leading to decreased binding of the miRNA to the natural target, inhibiting the miRNA’s effects on the cell. An inhibitor vector may transcribe only a single copy of the miRNA binding site, or many copies. In the latter case, the vector may be designated a “miRNA sponge” due to its higher binding capacity.

All of these research tools are available from abm! See our collection of miRNA products, available ready-to-use for a huge number of miRNAs from human, mouse, and rat.
Target Validation

While computational approaches are useful to narrow down a list of potential targets, miRNA-mRNA interactions must always be validated using experimental approaches (5). The simplest way of verifying a miRNA target is by cloning a vector with the 3’UTR of a predicted target gene downstream of a reporter such as GFP or Luciferase. If the miRNA binds to the target, reporter expression should be reduced. If the miRNA does not bind, reporter expression will be unaffected.

Some considerations when performing target validation are:

  • Use the entire 3’UTR sequence when testing, not just the putative miRNA binding site. Sequences distal to the binding site may have an effect on miRNA binding and gene regulation.
  • Whether a miRNA regulates a target depends not only on sequence, but also other factors such as cell type, whether the cell is differentiated, and whether the cell is under stress. Therefore, target validation should be performed in the cell of interest, under conditions as close to in vivo as possible.
  • miRNA expression increases with increasing cell confluence. It is important to monitor and control for cell density in any miRNA experiment.

Target validation using UTR reporters can be performed in a few ways:

  • Clone two variations of the 3’UTR reporter vector: one with the wild type 3’UTR, and another with a mutated version of the putative miRNA binding site. Transfect/transduce cell lines that express the miRNA of interest with the reporter vectors. If the cells with the wild type 3’UTR vector show reduced reporter expression in comparison to those with the mutant 3’UTR, it indicates that an endogenous miRNA can bind that target site.
  • Transfect/transduce cell lines with a 3’UTR reporter vector. Add a miRNA inhibitor. If the miRNA binds the inhibitor, it will cause reduced miRNA binding to the 3’UTR reporter, leading to increased reporter expression.
  • Transfect/transduce cell lines with a 3’UTR reporter vector. Increase amounts of the miRNA of interest by introducing either synthetic miRNA mimics or a miRNA overexpression vector. If there is an interaction between the miRNA and the target site, increasing miRNA levels should have a dose-dependent effect on reporter expression levels. This effect should be absent when the experiment is performed using a mutant 3’UTR reporter vector.
abm has you covered for target validation! We offer 3'UTR reporter constructs specifically designed for use in target validation experiments. Pair with our site-directed mutagenesis service, or a miRNA mimic or inhibitor. Or, for studying miRNA binding to the 5'UTR, we also offer 5'UTR reporter constructs.
Functional Analysis

Once a miRNA’s target has been confirmed, the next logical step is to determine what effect that miRNA has on the cell or animal.

The functional effect of a miRNA can be studied by examining the phenotypic effects of miRNA inhibition or overexpression. This may be done in cell culture or in animal models by administering miRNA mimics/expression vectors or miRNA inhibitors/inhibition vectors. Their effects can be confirmed by measuring miRNA levels (qPCR, Northern blotting) and/or protein levels (Western blotting).

For large scale characterization, transcriptome and proteome analyses can be used. This provides an overview of the effects of a miRNA on a system. Transcriptome/proteome analysis has several downsides:

  • Proteome analysis is complicated and costly. It requires a large quantity of material and requires the purchase or generation of appropriate antibodies.
  • Transcriptome analysis may not catch all types of gene regulation carried out by miRNAs. miRNAs cause gene regulation in two ways: degradation of the mRNA, and repression of translation. The latter type of regulation would not be detectable via transcriptomics.
  • miRNAs are moderate regulators and may not have a large effect on expression level. For this reason, it can be difficult to distinguish true results from the natural “noise” of biological samples.

Rather than manipulating miRNA expression using transfected materials, it is also possible to generate transgenic animal models via genetic approaches (9). Some examples would be: the knockout of miRNA genes, the knock-in of an expression cassette to overexpress a miRNA, and the mutation of miRNA-binding sites in protein-encoding genes (10).

Some general considerations when performing functional analyses in vivo are:

  • Consider potential off-target effects of overexpressing or inhibiting a miRNA. One miRNA may regulate many different genes, and different tissues may have different reactions to miRNA inhibition/expression. If possible, it is best to limit the number of unintended side effects by using a tissue-specific delivery system or investigating a tissue-specific miRNA.
  • The inhibition or deletion of a single miRNA may not result in a phenotypic result. miRNAs often exist in families or clusters of highly-related sequences that can be highly redundant. As well, in some cases, genetic deletions might be compensated for over time.
  • When performing a genetic miRNA deletion, design the targeting strategy carefully. miRNAs are often found within introns or as a polycistronic transcript, so care must be taken to design a deletion so it doesn’t disrupt transcription of other genes.
Our CRISPR experts have developed a specialty service just for genomic miRNA knockouts.
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  • Managing MicroRNAs with Vector-Encoded Decoy-Type Inhibitors. Bak, Rasmus O, Hollensen, Anne Kruse and Mikkelsen, Jacob Giehm. 8, 2013, Molecular Therapy, Vol. 21, pp. 1478-1485.
  • Small RNA Detection by in Situ Hybridization Methods. Urbanek, Martyna O., Nawrocka, Anna U. and Krzyzosiak, Wlodzimierz J. 6, 2015, International Journal of Molecular Sciences, Vol. 16, pp. 13259-13286.
  • Strategies to determine the biological function of microRNAs. Krützfeldt, Jan, Poy, Matthew N and Stoffel, Markus. 2006, Nature Genetics, Vol. 38, pp. S14-S19.
  • Serum response factor regulates a muscle-specific microRNA that targets Hand2 during cardiogenesis. Zhao, Yong, Samal, Eva and Srivastava, Deepak. 2005, Nature, Vol. 436, pp. 214-220.