Functional combination strategy for prioritization of human miRNA target

MicroRNAs (miRNAs) are a class of non-coding RNAs known to play important regulatory roles through targets, which can affect human cell proliferation, differentiation, and metabolism. Overlaps between different miRNA target prediction algorithms (MTPAs) are small, which limit the understanding of miRNA's biological functions. However, the overlaps increase on functional levels, such as Gene Ontology (GO), Protein–Protein Interaction Network (PPIN) and pathways. Here, we performed prioritization on existing predicted target sets for each miRNA by considering all the possible combinations of 7 functional levels. After analyzing the results of both single and multiple functional levels, we found that functional combination strategies including pathways and GO performed better in the prioritization of human miRNA target. The combination which performed best was “Pathway + GO BP + GO MF + GO CC + Target + PPIN”. For the prioritized result of this combination, the valid target had top ranking, and our method performed better than the MTPAs after comparison adopting the validated ranking levels. Top genes in ranking lists generated by this strategy were either validated by experiments or share same functions with the corresponding miRNA/its validated genes in disease related biological processes.     

Modulation of specific cell cycle phases in human embryonic stem cells by lncRNA RNA decoys

Recent studies have shown that long noncoding RNAs (lncRNAs) are crucial regulators of human embryonic stem cells (hESCs). However, modes of actions of lncRNAs in hESCs are not well illustrated. Here, we predicted a regulatory network in hESCs in which lncRNAs interact with TFs and thereby control the expressions of downstream targets of TFs. The predicted network is comprised of 2289 3‐motif subgraphs which are characterized by 3 nodes: (i) a lncRNA which is predicted to interact with (ii) a TF and (iii) a gene which is a target of TF and coexpressing with lncRNA. We performed functional annotation of the network by identifying hub nodes followed by pathway enrichment study, which unveiled an active G1‐S cell cycle phase transition‐specific subnetwork that encompasses 2 lncRNAs, MALAT1 and DANCR. Our analysis revealed that MALAT1 and DANCR might be playing key roles in G1‐S phase transition by acting as RNA decoy via interacting with crucial stemness maintaining TFs. We predicted that MALAT1 possibly compete with DNMT1 and CDCA7 genes to bind to E2F1 thereby interrupting repression of DNMT1 and activation of CDCA7 by E2F1 in hESCs, whereas DANCR possibly competes with IPO7 gene to bind to MYC thereby interrupting MYC‐mediated activation of IPO7 in hESCs. Both of these are conjectured to contribute to rapid G1‐S phase transition aiding in stemness maintenance of hESCs. This study presents a crucial TF target cross talks mediated by lncRNAs in hESCs regulating its properties which needs further investigation.