>NUCB1|NM_006184|3'UTR
   1 TCCTCCGGGACCCCAGCCCTCAGGATTCCTGATGCTCCAAGGCGACTGATGGGCGCTGGATGAAGTGGCACAGTCAGCTT
  81 CCCTGGGGGCTGGTGTCATGTTGGGCTCCTGGGGCGGGGGCACGGCCTGGCATTTCACGCATTGCTGCCACCCCAGGTCC
 161 ACCTGTCTCCACTTTCACAGCCTCCAAGTCTGTGGCTCTTCCCTTCTGTCCTCCGAGGGGCTTGCCTTCTCTCGTGTCCA
 241 GTGAGGTGCTCAGTGATCGGCTTAACTTAGAGAAGCCCGCCCCCTCCCCTTCTCCGTCTGTCCCAAGAGGGTCTGCTCTG
 321 AGCCTGCGTTCCTAGGTGGCTCGGCCTCAGCTGCCTGGGTTGTGGCCGCCCTAGCATCCTGTATGCCCACAGCTACTGGA
 401 ATCCCCGCTGCTGCTCCGGGCCAAGCTTCTGGTTGATTAATGAGGGCATGGGGTGGTCCCTCAAGACCTTCCCCTACCTT
 481 TTGTGGAACCAGTGATGCCTCAAAGACAGTGTCCCCTCCACAGCTGGGTGCCAGGGGCAGGGGATCCTCAGTATAGCCGG
 561 TGAACCCTGATACCAGGAGCCTGGGCCTCCCTGAACCCCTGGCTTCCAGCCATCTCATCGCCAGCCTCCTCCTGGACCTC
 641 TTGGCCCCCAGCCCCTTCCCCACACAGCCCCAGAAGGGTCCCAGAGCTGACCCCACTCCAGGACCTAGGCCCAGCCCCTC
 721 AGCCTCATCTGGAGCCCCTGAAGACCAGTCCCACCCACCTTTCTGGCCTCATCTGACACTGCTCCGCATCCTGCTGTGTG
 801 TCCTGTTCCATGTTCCGGTTCCATCCAAATACACTTTCTGGAACAAATGCATGGCTCCAAAAAAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' ucUCGUUCUGGGGC----AGAGAUUu 5' | ||:|| ||:| || ||:| Target 5' atACCAGGAGCCTGGGCCTCCCTGAa 3'	570 - 595	114.00	-14.90
2	miRNA 3' ucuCGUUCUGG--GGCAGAGAuuu 5' | ::|:|: || ||||| Target 5' tccGAGGGGCTTGCCTTCTCTcgt 3'	212 - 235	113.00	-13.30
3	miRNA 3' ucucGUUCUG--GGGCAGAGAUuu 5' ||:| | ||:||||| | Target 5' acccCAGGTCCACCTGTCTCCAct 3'	150 - 173	112.00	-15.46

Mutant ID	Mutant Position	Mutant Source
COSN32067905	3	COSMIC
COSN31516681	56	COSMIC
COSN30485366	59	COSMIC
COSN30498097	67	COSMIC
COSN31554680	78	COSMIC
COSN30175260	93	COSMIC
COSN4893051	97	COSMIC
COSN28190229	118	COSMIC
COSN31610392	123	COSMIC
COSN31604079	259	COSMIC
COSN21641984	384	COSMIC
COSN15915144	677	COSMIC
COSN15143795	912	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs755339454	3	dbSNP
rs1217835072	4	dbSNP
rs1240265708	5	dbSNP
rs377591728	7	dbSNP
rs199991235	8	dbSNP
rs779291640	10	dbSNP
rs769545177	12	dbSNP
rs777518221	14	dbSNP
rs1234345315	15	dbSNP
rs748743231	20	dbSNP
rs1281883428	22	dbSNP
rs1400457893	26	dbSNP
rs1316619681	27	dbSNP
rs1223011795	30	dbSNP
rs201809235	31	dbSNP
rs1437725987	32	dbSNP
rs1283219966	36	dbSNP
rs774097374	38	dbSNP
rs1351162523	43	dbSNP
rs759476127	44	dbSNP
rs771816758	45	dbSNP
rs547115352	46	dbSNP
rs775285869	50	dbSNP
rs1297410000	51	dbSNP
rs1470065025	54	dbSNP
rs773237969	56	dbSNP
rs149462138	61	dbSNP
rs886943299	74	dbSNP
rs34635096	81	dbSNP
rs1363869060	82	dbSNP
rs1241540054	90	dbSNP
rs1532704	92	dbSNP
rs538145418	93	dbSNP
rs1249293815	94	dbSNP
rs1201416190	99	dbSNP
rs1038160391	116	dbSNP
rs899485668	117	dbSNP
rs1449832277	123	dbSNP
rs996892779	124	dbSNP
rs1287383125	125	dbSNP
rs1236900448	127	dbSNP
rs550065430	139	dbSNP
rs568488835	140	dbSNP
rs1453164592	141	dbSNP
rs1334272963	142	dbSNP
rs894319559	146	dbSNP
rs535876615	150	dbSNP
rs1429319602	153	dbSNP
rs1385504553	155	dbSNP
rs879263261	156	dbSNP
rs1058491	158	dbSNP
rs765051904	163	dbSNP
rs112789614	171	dbSNP
rs1031373367	173	dbSNP
rs539546729	179	dbSNP
rs979471564	185	dbSNP
rs990403674	188	dbSNP
rs921501913	191	dbSNP
rs1183578590	192	dbSNP
rs1465758170	198	dbSNP
rs932824811	201	dbSNP
rs1203501319	204	dbSNP
rs1034202636	207	dbSNP
rs1219974297	208	dbSNP
rs959504205	215	dbSNP
rs558335982	216	dbSNP
rs1384793891	219	dbSNP
rs188688760	230	dbSNP
rs1315196540	231	dbSNP
rs912720486	234	dbSNP
rs940143005	235	dbSNP
rs1163903438	236	dbSNP
rs543724986	241	dbSNP
rs1037044403	242	dbSNP
rs1426154375	254	dbSNP
rs898506169	259	dbSNP
rs931291836	260	dbSNP
rs1163347542	262	dbSNP
rs982738391	276	dbSNP
rs1244358260	279	dbSNP
rs1446564513	280	dbSNP
rs562018840	280	dbSNP
rs144101432	285	dbSNP
rs1013230309	287	dbSNP
rs941205067	290	dbSNP
rs1038227593	295	dbSNP
rs1045605440	296	dbSNP
rs777292209	297	dbSNP
rs998612128	299	dbSNP
rs1031386288	328	dbSNP
rs11544982	329	dbSNP
rs1302090474	334	dbSNP
rs1410928492	336	dbSNP
rs59040968	342	dbSNP
rs770839066	343	dbSNP
rs1324314610	344	dbSNP
rs1201718349	345	dbSNP
rs954359872	345	dbSNP
rs1489865393	360	dbSNP
rs1268505978	367	dbSNP
rs1333124495	368	dbSNP
rs1437541694	369	dbSNP
rs987451259	371	dbSNP
rs1274846447	382	dbSNP
rs180757925	385	dbSNP
rs1230274150	387	dbSNP
rs1021191046	395	dbSNP
rs904010443	396	dbSNP
rs1343073637	398	dbSNP
rs111400103	400	dbSNP
rs1329802745	407	dbSNP
rs972812724	408	dbSNP
rs551944405	409	dbSNP
rs1271107902	418	dbSNP
rs7028	419	dbSNP
rs1055153552	422	dbSNP
rs916564544	424	dbSNP
rs948695773	428	dbSNP
rs1025395526	436	dbSNP
rs1046024752	441	dbSNP
rs1428682112	442	dbSNP
rs1178057001	445	dbSNP
rs907037365	447	dbSNP
rs998665869	456	dbSNP
rs1231331876	457	dbSNP
rs950730874	460	dbSNP
rs982684756	469	dbSNP
rs1263733475	474	dbSNP
rs1205451574	475	dbSNP
rs1231920072	477	dbSNP
rs534449219	484	dbSNP
rs1223789782	489	dbSNP
rs1052867509	490	dbSNP
rs1375114251	495	dbSNP
rs185371465	496	dbSNP
rs962631082	499	dbSNP
rs1011739770	515	dbSNP
rs865987014	516	dbSNP
rs921107576	519	dbSNP
rs932388626	529	dbSNP
rs1411981124	530	dbSNP
rs1405923991	531	dbSNP
rs1028024413	539	dbSNP
rs1461381451	544	dbSNP
rs1163400702	552	dbSNP
rs771890840	553	dbSNP
rs751966552	559	dbSNP
rs1393407731	560	dbSNP
rs1243513872	566	dbSNP
rs1008482537	574	dbSNP
rs1042053617	580	dbSNP
rs1236789964	587	dbSNP
rs1406297910	590	dbSNP
rs1019803741	591	dbSNP
rs904085985	598	dbSNP
rs961539559	600	dbSNP
rs1238967835	604	dbSNP
rs1289083947	611	dbSNP
rs1360693360	613	dbSNP
rs1354892957	618	dbSNP
rs972905687	620	dbSNP
rs1232659166	621	dbSNP
rs1289914970	632	dbSNP
rs1058594	641	dbSNP
rs1282331622	645	dbSNP
rs1343478751	651	dbSNP
rs920073442	668	dbSNP
rs549979965	669	dbSNP
rs536562792	677	dbSNP
rs991302220	678	dbSNP
rs1271961905	681	dbSNP
rs1442494796	687	dbSNP
rs916591495	690	dbSNP
rs1187001687	695	dbSNP
rs949373048	699	dbSNP
rs568395109	703	dbSNP
rs1435728554	713	dbSNP
rs12463009	716	dbSNP
rs1058666	730	dbSNP
rs1251992798	735	dbSNP
rs1490413943	737	dbSNP
rs1293446901	748	dbSNP
rs928505896	760	dbSNP
rs1058672	764	dbSNP
rs764253177	770	dbSNP
rs1296971778	774	dbSNP
rs1052980654	776	dbSNP
rs1016278808	780	dbSNP
rs1297661398	782	dbSNP
rs892967977	785	dbSNP
rs146255034	786	dbSNP
rs78972220	787	dbSNP
rs1301495975	788	dbSNP
rs921089259	797	dbSNP
rs1167723973	804	dbSNP
rs77919001	807	dbSNP
rs1430254273	808	dbSNP
rs45520632	808	dbSNP
rs912289094	809	dbSNP
rs1308847056	812	dbSNP
rs1192344729	813	dbSNP
rs1374974837	815	dbSNP
rs945142395	816	dbSNP
rs372318925	817	dbSNP
rs76779666	818	dbSNP
rs994374659	835	dbSNP
rs1488398131	841	dbSNP
rs537276046	844	dbSNP
rs936916841	845	dbSNP
rs765762446	846	dbSNP
rs1306298424	852	dbSNP
rs1278068921	853	dbSNP
rs895293640	860	dbSNP
rs952955369	864	dbSNP
rs555526776	866	dbSNP
rs1230237255	867	dbSNP
rs886487246	870	dbSNP
rs1024115282	884	dbSNP
rs1298540594	885	dbSNP
rs191157915	892	dbSNP
rs1169845456	893	dbSNP
rs982137218	902	dbSNP
rs923919431	903	dbSNP
rs899196089	904	dbSNP
rs995816409	909	dbSNP
rs751039569	914	dbSNP
rs1179343406	925	dbSNP
rs1443515474	929	dbSNP
rs758806407	934	dbSNP
rs541324996	943	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.

- 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, 2013

BACKGROUND: In recent years, a variety of small RNAs derived from other RNAs with well-known functions such as tRNAs and snoRNAs, have been identified. The functional relevance of these RNAs is largely unknown. To gain insight into the complexity of snoRNA processing and the functional relevance of snoRNA-derived small RNAs, we sequence long and short RNAs, small RNAs that co-precipitate with the Argonaute 2 protein and RNA fragments obtained in photoreactive nucleotide-enhanced crosslinking and immunoprecipitation (PAR-CLIP) of core snoRNA-associated proteins. RESULTS: Analysis of these data sets reveals that many loci in the human genome reproducibly give rise to C/D box-like snoRNAs, whose expression and evolutionary conservation are typically less pronounced relative to the snoRNAs that are currently cataloged. We further find that virtually all C/D box snoRNAs are specifically processed inside the regions of terminal complementarity, retaining in the mature form only 4-5 nucleotides upstream of the C box and 2-5 nucleotides downstream of the D box. Sequencing of the total and Argonaute 2-associated populations of small RNAs reveals that despite their cellular abundance, C/D box-derived small RNAs are not efficiently incorporated into the Ago2 protein. CONCLUSIONS: We conclude that the human genome encodes a large number of snoRNAs that are processed along the canonical pathway and expressed at relatively low levels. Generation of snoRNA-derived processing products with alternative, particularly miRNA-like, functions appears to be uncommon.

- Neoplasia (New York, N.Y.), 2016

MicroRNA (miRNA) deregulation in prostate cancer (PCa) contributes to PCa initiation and metastatic progression. To comprehensively define the cancer-associated changes in miRNA targeting and function in commonly studied models of PCa, we performed photoactivatable ribonucleoside-enhanced cross-linking immunoprecipitation of the Argonaute protein in a panel of PCa cell lines modeling different stages of PCa progression. Using this comprehensive catalogue of miRNA targets, we analyzed miRNA targeting on known drivers of PCa and examined tissue-specific and stage-specific pathway targeting by miRNAs. We found that androgen receptor is the most frequently targeted PCa oncogene and that miR-148a targets the largest number of known PCa drivers. Globally, tissue-specific and stage-specific changes in miRNA targeting are driven by homeostatic response to active oncogenic pathways. Our findings indicate that, even in advanced PCa, the miRNA pool adapts to regulate continuing alterations in the cancer genome to balance oncogenic molecular changes. These findings are important because they are the first to globally characterize miRNA changes in PCa and demonstrate how the miRNA target spectrum responds to staged tumorigenesis.

- Nucleic acids research, 2016

MicroRNAs (miRs) have emerged as key biological effectors in human health and disease. These small noncoding RNAs are incorporated into Argonaute (Ago) proteins, where they direct post-transcriptional gene silencing via base-pairing with target transcripts. Although miRs have become intriguing biological entities and attractive therapeutic targets, the translational impacts of miR research remain limited by a paucity of empirical miR targeting data, particularly in human primary tissues. Here, to improve our understanding of the diverse roles miRs play in cardiovascular function and disease, we applied high-throughput methods to globally profile miR:target interactions in human heart tissues. We deciphered Ago2:RNA interactions using crosslinking immunoprecipitation coupled with high-throughput sequencing (HITS-CLIP) to generate the first transcriptome-wide map of miR targeting events in human myocardium, detecting 4000 cardiac Ago2 binding sites across >2200 target transcripts. Our initial exploration of this interactome revealed an abundance of miR target sites in gene coding regions, including several sites pointing to new miR-29 functions in regulating cardiomyocyte calcium, growth and metabolism. Also, we uncovered several clinically-relevant interactions involving common genetic variants that alter miR targeting events in cardiomyopathy-associated genes. Overall, these data provide a critical resource for bolstering translational miR research in heart, and likely beyond.