We next examined whether miRNAs can be classified according to the coherence and non-coherence of their targets during development given that we found non-coherent targets to be as common as coherent ones.
In this light, it may be that greater ACC activity to the non-coherent stimuli reflected the greater effort to resolve the appraisal of non-coherence, compared to the faster and presumably less effortful appraisal of coherence.
More research is needed on predictors of (non- coherence inon- coherenceects.
Many of the late-expressed miRNAs in developing cerebellum were characterized by their target non-coherence.
These results suggest that many late-expressed miRNAs mediate target non-coherence in a tissue-specific and functional manner.
We found that evoked (phase-locked) alpha-band activity increased significantly for appraisals of coherence, in contrast to appraisals of non-coherence.
Based on the finding that late miRNAs are characterized by the non-coherence of their targets, we examined the ontological correlates of the target sets.
In comparison, there are far fewer significant miRNAs either for the non-coherence or for the coherence of their targets in the developing lung, where there is no apparent bias towards a particular category (Table S4).
Moreover, the statistical significances at later stages P21 and P30 are higher than at early stages P10 and P15, which demonstrate progressive nature of developmental non-coherence of mRNA target of late miRNAs.
Regulation of the actin cytoskeleton and MAPK signaling pathway are among the identified lung development-specific non-coherent ontological target sets for miR-140, which is significant in lung development for its target non-coherence (Table S4).
Intriguingly, miR-15 is found most significant for its targets non-coherence, especially for signal transduction related functions in mouse development (Table S17) while target gene acvr2 is coherent to miR-15 consistent with that in [44].
