>RPS27A|NM_001135592|3'UTR
   1 CTGTATGAGTTAATAAAAGACATGAACTAACATTTATTGTTGGGTTTTATTGCAGTAAAAAGAATGGTTTTTAAGCACCA
  81 AATTGATGGTCACACCATTTCCTTTTAGTAGTGCTACTGCTATCGCTGTGTGAATGTTGCCTCTGGGGATTATGTGACCC
 161 AGTGGTTCTGTATACCTGCCAGGTGCCAACCACTTGTAAAGGTCTTGATATTTTCAATTCTTAGACTACCTATACTTTGG
 241 CAGAAGTTATATTTAATGTAAGTTGTCTAAATATAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' cauucuuCACGAAUGUAACGUc 5' | |:|| :|||||| Target 5' tattgttGGGTTT-TATTGCAg 3'	35 - 55	134.00	-10.70
2	miRNA 3' cauucUUCACGAAU-GU-AACGUc 5' |:|||| | || |||:| Target 5' ctgccAGGTGCCAACCACTTGTAa 3'	176 - 199	109.00	-8.30
3	miRNA 3' cauucuuCACGAAUGUAACGuc 5' |||: |::|||| Target 5' tatcgctGTGTGAATGTTGCct 3'	121 - 142	103.00	-5.50

Mutant ID	Mutant Position	Mutant Source
COSN31509492	8	COSMIC
COSN30158182	17	COSMIC
COSN30458003	30	COSMIC
COSN31961649	160	COSMIC
COSN1240297	164	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs148807785	2	dbSNP
rs759130681	2	dbSNP
rs773878636	2	dbSNP
rs1237538845	4	dbSNP
rs1473522814	6	dbSNP
rs771159154	10	dbSNP
rs1418392951	14	dbSNP
rs767889668	17	dbSNP
rs1428847633	18	dbSNP
rs1258186204	25	dbSNP
rs1172579088	28	dbSNP
rs775230234	30	dbSNP
rs914626221	31	dbSNP
rs1337371845	32	dbSNP
rs762637649	32	dbSNP
rs375702426	33	dbSNP
rs74733706	35	dbSNP
rs1428767400	39	dbSNP
rs774072074	40	dbSNP
rs200893583	41	dbSNP
rs767544315	43	dbSNP
rs1287878134	46	dbSNP
rs775792458	46	dbSNP
rs750300458	50	dbSNP
rs755970480	51	dbSNP
rs766042973	52	dbSNP
rs536517684	53	dbSNP
rs143376339	56	dbSNP
rs1261600670	58	dbSNP
rs1395781253	62	dbSNP
rs939215801	63	dbSNP
rs1003443086	68	dbSNP
rs375779217	68	dbSNP
rs1165071364	73	dbSNP
rs575619466	77	dbSNP
rs1369683383	84	dbSNP
rs765741190	84	dbSNP
rs1458538804	89	dbSNP
rs1388934673	103	dbSNP
rs1054864734	105	dbSNP
rs1056096766	107	dbSNP
rs544649053	111	dbSNP
rs1468183175	116	dbSNP
rs1162213589	117	dbSNP
rs895086091	118	dbSNP
rs1370068214	119	dbSNP
rs146159099	120	dbSNP
rs527900755	123	dbSNP
rs1422996746	125	dbSNP
rs571763925	126	dbSNP
rs1267751334	129	dbSNP
rs1401566621	136	dbSNP
rs1296300126	137	dbSNP
rs1016639651	138	dbSNP
rs1266511888	139	dbSNP
rs962465982	142	dbSNP
rs752452051	143	dbSNP
rs997438212	146	dbSNP
rs1436282995	153	dbSNP
rs1339807688	158	dbSNP
rs1028479281	159	dbSNP
rs1415302184	160	dbSNP
rs1392308539	163	dbSNP
rs541133856	167	dbSNP
rs1163768213	174	dbSNP
rs1424005165	184	dbSNP
rs1383323684	187	dbSNP
rs1190201104	188	dbSNP
rs955840036	190	dbSNP
rs987070429	191	dbSNP
rs1191368818	194	dbSNP
rs1453392851	195	dbSNP
rs924640685	197	dbSNP
rs1357853282	198	dbSNP
rs1313613511	202	dbSNP
rs1277425173	206	dbSNP
rs1229547072	207	dbSNP
rs1323507340	209	dbSNP
rs1341946604	211	dbSNP
rs956033361	216	dbSNP
rs1428283811	218	dbSNP
rs1332313484	222	dbSNP
rs902137247	226	dbSNP
rs1323566350	229	dbSNP
rs1403811156	249	dbSNP
rs187238769	251	dbSNP
rs1170443674	257	dbSNP
rs1430128443	260	dbSNP
rs914678726	263	dbSNP
rs138978188	267	dbSNP
rs549789033	269	dbSNP
rs751030286	274	dbSNP
rs563614280	275	dbSNP

- Cell, 2010

RNA transcripts are subject to posttranscriptional gene regulation involving hundreds of RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs) expressed in a cell-type dependent fashion. We developed a cell-based crosslinking approach to determine at high resolution and transcriptome-wide the binding sites of cellular RBPs and miRNPs. The crosslinked sites are revealed by thymidine to cytidine transitions in the cDNAs prepared from immunopurified RNPs of 4-thiouridine-treated cells. We determined the binding sites and regulatory consequences for several intensely studied RBPs and miRNPs, including PUM2, QKI, IGF2BP1-3, AGO/EIF2C1-4 and TNRC6A-C. Our study revealed that these factors bind thousands of sites containing defined sequence motifs and have distinct preferences for exonic versus intronic or coding versus untranslated transcript regions. The precise mapping of binding sites across the transcriptome will be critical to the interpretation of the rapidly emerging data on genetic variation between individuals and how these variations contribute to complex genetic diseases.

- Nature methods, 2011

Cross-linking and immunoprecipitation (CLIP) is increasingly used to map transcriptome-wide binding sites of RNA-binding proteins. We developed a method for CLIP data analysis, and applied it to compare CLIP with photoactivatable ribonucleoside-enhanced CLIP (PAR-CLIP) and to uncover how differences in cross-linking and ribonuclease digestion affect the identified sites. We found only small differences in accuracies of these methods in identifying binding sites of HuR, which binds low-complexity sequences, and Argonaute 2, which has a complex binding specificity. We found that cross-link-induced mutations led to single-nucleotide resolution for both PAR-CLIP and CLIP. Our results confirm the expectation from original CLIP publications that RNA-binding proteins do not protect their binding sites sufficiently under the denaturing conditions used during the CLIP procedure, and we show that extensive digestion with sequence-specific RNases strongly biases the recovered binding sites. This bias can be substantially reduced by milder nuclease digestion conditions.

- Genes & development, 2011

MicroRNAs are important regulators in many cellular processes, including stem cell self-renewal. Recent studies demonstrated their function as pluripotency factors with the capacity for somatic cell reprogramming. However, their role in human embryonic stem (ES) cells (hESCs) remains poorly understood, partially due to the lack of genome-wide strategies to identify their targets. Here, we performed comprehensive microRNA profiling in hESCs and in purified neural and mesenchymal derivatives. Using a combination of AGO cross-linking and microRNA perturbation experiments, together with computational prediction, we identified the targets of the miR-302/367 cluster, the most abundant microRNAs in hESCs. Functional studies identified novel roles of miR-302/367 in maintaining pluripotency and regulating hESC differentiation. We show that in addition to its role in TGF-beta signaling, miR-302/367 promotes bone morphogenetic protein (BMP) signaling by targeting BMP inhibitors TOB2, DAZAP2, and SLAIN1. This study broadens our understanding of microRNA function in hESCs and is a valuable resource for future studies in this area.

- Nature, 2013

Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.

- mBio, 2013

UNLABELLED: The question of how HIV-1 interfaces with cellular microRNA (miRNA) biogenesis and effector mechanisms has been highly controversial. Here, we first used deep sequencing of small RNAs present in two different infected cell lines (TZM-bl and C8166) and two types of primary human cells (CD4(+) peripheral blood mononuclear cells [PBMCs] and macrophages) to unequivocally demonstrate that HIV-1 does not encode any viral miRNAs. Perhaps surprisingly, we also observed that infection of T cells by HIV-1 has only a modest effect on the expression of cellular miRNAs at early times after infection. Comprehensive analysis of miRNA binding to the HIV-1 genome using the photoactivatable ribonucleoside-induced cross-linking and immunoprecipitation (PAR-CLIP) technique revealed several binding sites for cellular miRNAs, a subset of which were shown to be capable of mediating miRNA-mediated repression of gene expression. However, the main finding from this analysis is that HIV-1 transcripts are largely refractory to miRNA binding, most probably due to extensive viral RNA secondary structure. Together, these data demonstrate that HIV-1 neither encodes viral miRNAs nor strongly influences cellular miRNA expression, at least early after infection, and imply that HIV-1 transcripts have evolved to avoid inhibition by preexisting cellular miRNAs by adopting extensive RNA secondary structures that occlude most potential miRNA binding sites. IMPORTANCE: MicroRNAs (miRNAs) are a ubiquitous class of small regulatory RNAs that serve as posttranscriptional regulators of gene expression. Previous work has suggested that HIV-1 might subvert the function of the cellular miRNA machinery by expressing viral miRNAs or by dramatically altering the level of cellular miRNA expression. Using very sensitive approaches, we now demonstrate that neither of these ideas is in fact correct. Moreover, HIV-1 transcripts appear to largely avoid regulation by cellular miRNAs by adopting an extensive RNA secondary structure that occludes the ability of cellular miRNAs to interact with viral mRNAs. Together, these data suggest that HIV-1, rather than seeking to control miRNA function in infected cells, has instead evolved a mechanism to become largely invisible to cellular miRNA effector mechanisms.

- Genome biology, 2014

BACKGROUND: Various microRNAs (miRNAs) are up- or downregulated in tumors. However, the repression of cognate miRNA targets responsible for the phenotypic effects of this dysregulation in patients remains largely unexplored. To define miRNA targets and associated pathways, together with their relationship to outcome in breast cancer, we integrated patient-paired miRNA-mRNA expression data with a set of validated miRNA targets and pathway inference. RESULTS: To generate a biochemically-validated set of miRNA-binding sites, we performed argonaute-2 photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (AGO2-PAR-CLIP) in MCF7 cells. We then defined putative miRNA-target interactions using a computational model, which ranked and selected additional TargetScan-predicted interactions based on features of our AGO2-PAR-CLIP binding-site data. We subselected modeled interactions according to the abundance of their constituent miRNA and mRNA transcripts in tumors, and we took advantage of the variability of miRNA expression within molecular subtypes to detect miRNA repression. Interestingly, our data suggest that miRNA families control subtype-specific pathways; for example, miR-17, miR-19a, miR-25, and miR-200b show high miRNA regulatory activity in the triple-negative, basal-like subtype, whereas miR-22 and miR-24 do so in the HER2 subtype. An independent dataset validated our findings for miR-17 and miR-25, and showed a correlation between the expression levels of miR-182 targets and overall patient survival. Pathway analysis associated miR-17, miR-19a, and miR-200b with leukocyte transendothelial migration. CONCLUSIONS: We combined PAR-CLIP data with patient expression data to predict regulatory miRNAs, revealing potential therapeutic targets and prognostic markers in breast cancer.