One of my projects is to observe what (if any) effects the sequences flanking the miRNA target sites and the structure of the RNA transcript has on the miRNAs efficacy. I found a rather old paper (published in about 2013) that has found that areas flanking miRNAs target sites are typically unstructured. This paper uses a computational approach to the determined the aforementioned results. It goes without saying that I think this paper is interesting because my experiment could very well substantiate with experimental data or disagree with this study.
In this article, Selection on Synonymous Sites for Increased Accessibility around miRNA Binding Sites in Plants, the researchers retrieved the genomes and miRNAs for Arabidopsis thaliana, Zea mays, Oryza sativa, and Populus trichocarpa. They also downloaded expression data for miRNAs and their targets in A. thaliana from the Massively Parallel Signature Sequencing project. Using RNAFold, the researchers determined delta G open (the difference between the free energy of all secondary structures and the free energy of all structures in which the target site is unpaired), delta G local (the free energy of the local secondary structure of the miRNA target sites), and the GC content as typically higher GC content typically correlates with higher structure. They also calculated the Z-scores of these values as well.
Compared to the randomized sites, it was found that the area near the miRNA target sites are depleted in GC nucleotides and are typically unstructured. This trend is true regardless of the expression level of the mRNA target and the miRNA which targets it. However, what is really interesting is that the Z-score of delta G open (which is essentially the measure of how much energy is needed to “open” the miRNA target site) shows an obvious trend of decreasing as one moved closer to the miRNA target site and increasing as one moved away (in either 5′ or 3′ prime) from the same in all the species analyzed. However, this trend was apparent but much “weaker” in Arabidopsis. Also of note,targets of miRNAs that repress their targets by cleavage or translational repression show the exact same trend. I wonder if there is anything worth experimenting on this issue or if it’s merely an artifact of the data.
Again, I found this study interesting but some problems jump out at me. Firstly, programs like RNAFold are not totally accurate in determining the structure of transcripts in vivo. I wonder how the data will change if they used Sally Assmann’s DMS-seq data for Arabidopsis. Another issue is that the study only takes the 17 nucleotides upstream and 13 nucleotides downstream of the target into account when doing these analyses. This is because Kerterz et al. 2008 found that this region played an important role in animal miRNA repression efficiency. I wonder how this squares up with the collaboration we did with Christophe in which he hypothesized that because plants miRNA extensively binding with their target, flanking sequence context doesn’t change the miRNA efficacy.
In conclusion, I still think this paper is worth reading (or at least skimming through). One way or another, the experiment I mentioned will be important to this study. There are ways to transiently express genes in other species (such as Arabidopsis & rice), so it may be worth testing out the transient expression in these systems and see if the data is different from Nicotiana transient expression.
Note the papers can be found here: