>Slc7a10|NM_017394|3'UTR
   1 GACCTTGTAGAGACTGGAACAGCCGATTCTGTTTACATGTTGTTTATTGAGAAGGGGGTTGTGTTTTGTTTTGTTTTCAA
  81 AAATTTTTTTTCTGCAAAAAAAGAGAGAGAGAGAGAGAGAGAGAGAGAGAAAGAGAGACCCAACCCTTAGAGGCCTATTG
 161 TAAGGGACTGGCCACTGGGGTCGGGCTTCCTGCCTTAGCAATGCCCTGCTAGCTTCTCCAGAAATGCCTGTAAATAAACA
 241 GGGCTGGTTGTTGCTGTGTGAAAAAAAAAAAAAAAAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' cguucgggucuGGCGUUUUUc 5' |:||||||| Target 5' aaattttttttCTGCAAAAAa 3'	81 - 101	146.00	-7.20
2	miRNA 3' cguucGGGUCU-----GGCGUUUUUc 5' :||||| |:|:||| | Target 5' gcttcTCCAGAAATGCCTGTAAATAa 3'	212 - 237	108.00	-10.62
3	miRNA 3' cguucggguCUGG--CGUUUUUc 5' |||| |:|:|:| Target 5' ---------GACCTTGTAGAGAc 3'	1 - 14	102.00	-5.50

- Nature structural & molecular biology, 2011

MicroRNAs (miRNAs) are 19-22-nucleotide noncoding RNAs that post-transcriptionally regulate mRNA targets. We have identified endogenous miRNA binding sites in mouse embryonic stem cells (mESCs), by performing photo-cross-linking immunoprecipitation using antibodies to Argonaute (Ago2) followed by deep sequencing of RNAs (CLIP-seq). We also performed CLIP-seq in Dicer(-)/(-) mESCs that lack mature miRNAs, allowing us to define whether the association of Ago2 with the identified sites was miRNA dependent. A significantly enriched motif, GCACUU, was identified only in wild-type mESCs in 3' untranslated and coding regions. This motif matches the seed of a miRNA family that constitutes ~68% of the mESC miRNA population. Unexpectedly, a G-rich motif was enriched in sequences cross-linked to Ago2 in both the presence and absence of miRNAs. Expression analysis and reporter assays confirmed that the seed-related motif confers miRNA-directed regulation on host mRNAs and that the G-rich motif can modulate this regulation.

- BMC genomics, 2013

BACKGROUND: Validation of physiologic miRNA targets has been met with significant challenges. We employed HITS-CLIP to identify which miRNAs participate in liver regeneration, and to identify their target mRNAs. RESULTS: miRNA recruitment to the RISC is highly dynamic, changing more than five-fold for several miRNAs. miRNA recruitment to the RISC did not correlate with changes in overall miRNA expression for these dynamically recruited miRNAs, emphasizing the necessity to determine miRNA recruitment to the RISC in order to fully assess the impact of miRNA regulation. We incorporated RNA-seq quantification of total mRNA to identify expression-weighted Ago footprints, and developed a microRNA regulatory element (MRE) prediction algorithm that represents a greater than 20-fold refinement over computational methods alone. These high confidence MREs were used to generate candidate 'competing endogenous RNA' (ceRNA) networks. CONCLUSION: HITS-CLIP analysis provide novel insights into global miRNA:mRNA relationships in the regenerating liver.