Improving microRNA target prediction going beyond the seed

MicroRNAs (miRNAs) are a class of non-coding RNAs ~22nt in length known to play a pivotal role in the regulation of gene expression. They bind to their targets by Watson-Crick base pairing, leading to translational inhibition, deadenylation, and eventual mRNA degradation. Binding usually occurs in the 5' portion of the miRNA between positions 2-7 known as the miRNA 'seed' sequence. Different miRNAs can share identical seed sequences, and therefore computational prediction methods will currently report identical targets for all miRNAs from the same family. However, recent studies have shown that additional binding outside of the seed region can confer specificity of targeting to different miRNAs sharing a similar or identical seed.
This studentship will investigate the effect of supplementary (non-seed) binding on the efficacy and specificity of miRNA-mediated repression using miRNA over-expression/repression RNA-Seq datasets. These will be used to precisely characterise the position(s) of supplementary binding sites and to compare the effectiveness and specificity of targeting against seed-only sites across a broad range of miRNAs. Results from these experiments will then be incorporated into our FilTar tool for computational miRNA target prediction.