Hello,
I have 2 synthetic mature miRNA that I transfected into cells and I saw a cool phenotype of growth that I am interested to characterize further, so after transfection in a murine cell line I extracted RNA and did a microarray. I have one microarray for each of the 2 synthetic microRNAs + control miRNA. After analysis I have a list of deferentially expressed genes in both conditions of both synthetic miRNAs, and unsurprisingly the lists are very similar.
Is there any way I can predict the target/targets of these synthetic miRNAs? I was wondering if I could search for TFs that regulate most of these deferentially expressed genes, and maybe guess the target from that.
Any advice is appreciated,
Adrian
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Adrian Pelin
1 answer
A method I now for this is the "Upstream Regulator Analysis" of Ingenuity Pathway Analysis (IPA). IPA is a commercial tool and quite expensive. However, the methodology is not so complicated and described in Kraemer et al. (2013). In principle, you can adapt the method for you analysis but IPA clearly benefits from the comprehensive database that comes with the software.
Alternatively, when doing your own analysis, you can utilize a Gene Regulatory database like TRRUST or RegNetwork and create your own gene sets for an Over-Representation Analysis or Gene Set Enrichment Analysis, i.e., one set for each TF containing the genes that are regulated by this TF. For significant gene sets you can then check if the observed fold-changes of the genes are negatively correlated with the direction of regulation of the TF given in the database (miRNA blocks TF, thus if TF up-regulates you expect to see down-regulation and vice-versa).
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You could use MEME to see if the genes share common motifs and search for those motifs. Or scan using TF binding motifs from JASPR.
I know this isn't the fun bioinformatics approach, but if your gene list is small enough, you could probably get through enough papers in an evening on pubmed to figure out what's going on.