>PER1|NM_002616|3'UTR
   1 ACTCCATTCTGGGACCATCTCCAGGAGTCCATGAGAGGCTTTCTTCTCCTATGTCCCAATTCTCAGAACTCAGATGTGGC
  81 TAGACCAACCAGTGGGAAACTGCCCCAGCTTCTCCCACCATAGGGGGCCGGACCCCCATCACCAGCCTAGGATCCAGGGG
 161 CTGCCTCTGGCCTCTTAGGGAGCAGAGAGCAGAACTCCGCAGCCCAGCCCAGAGGAGTGTCACCTCCCACCTTTGGAGAG
 241 GAATCCTTCCCTCCCCTGGACAAAGTTGCTGACAAGCTGCTGAAGTGGCCTCTCCATATTCCAGCTGAGCCTGAATCTGA
 321 CTCTTGAGGGTTGGGGCTGCACTTATTTATTGCGGGGAGACAGCTCTCTCTCCCACCTCCTCCCCAGATGGGAGGAGAGC
 401 CTGAGGCCCAAGCAGGACCCGGGGGTTCCAGCCCCTAGCTGCTCTGGAGTGGGGGAGGTTGGTGGACCATGGAGTCCCTG
 481 GTGCTGCCCCTCAGGTGGGACCCAGGCGTTCTCAGCTGTACCCTCTGCCGATGGCATTTGTGTTTTTGATATTTGTGTCT
 561 GTTACTACTTTTTTAATACAAAAAGATAAAAACGCCCAAAAAAAAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' ucaucaaGAAACCAGAGUGUCu 5' || ||| ||| :|| Target 5' gggctgcCTCTGGCCTCTTAGg 3'	158 - 179	111.00	-10.50
2	miRNA 3' ucaUCAAGAAACCAGAGUGUcu 5' | |||| | |||| | Target 5' cccAATTCTCAGAACTCAGAtg 3'	55 - 76	103.00	-5.29
3	miRNA 3' ucaucAAGAAACC----AGAGUGUCu 5' ||| | || |||| ||| Target 5' ctccaTTC-TGGGACCATCTC-CAGg 3'	2 - 25	98.00	-10.20

Mutant ID	Mutant Position	Mutant Source
COSN30475836	4	COSMIC
COSN213290	5	COSMIC
COSN30133592	36	COSMIC
COSN31490619	66	COSMIC
COSN30101618	129	COSMIC
COSN24387296	130	COSMIC
COSN30183788	151	COSMIC
COSN31489441	185	COSMIC
COSN31598404	214	COSMIC
COSN1730307	372	COSMIC
COSN26603591	522	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs747785629	2	dbSNP
rs781584121	6	dbSNP
rs1256692255	9	dbSNP
rs755303484	11	dbSNP
rs751878671	12	dbSNP
rs184493993	15	dbSNP
rs758770438	17	dbSNP
rs192450546	20	dbSNP
rs901543265	31	dbSNP
rs372252358	32	dbSNP
rs200753550	42	dbSNP
rs1184914456	46	dbSNP
rs762177991	49	dbSNP
rs199766819	51	dbSNP
rs763719042	51	dbSNP
rs190460119	53	dbSNP
rs141664298	69	dbSNP
rs1432135592	71	dbSNP
rs1408290215	86	dbSNP
rs1456075713	95	dbSNP
rs1445185660	111	dbSNP
rs1260897620	112	dbSNP
rs1318101054	116	dbSNP
rs1346091746	119	dbSNP
rs892696949	127	dbSNP
rs561858829	129	dbSNP
rs1007530712	130	dbSNP
rs1205532294	133	dbSNP
rs540690949	134	dbSNP
rs1325612100	135	dbSNP
rs1159731950	142	dbSNP
rs905353557	143	dbSNP
rs1045188656	144	dbSNP
rs754701694	147	dbSNP
rs572975216	155	dbSNP
rs953491150	159	dbSNP
rs1490239493	161	dbSNP
rs185558493	164	dbSNP
rs1271081045	166	dbSNP
rs1158564530	174	dbSNP
rs998175656	175	dbSNP
rs1402856690	181	dbSNP
rs1455101997	183	dbSNP
rs1163081158	185	dbSNP
rs1363360971	192	dbSNP
rs574749695	198	dbSNP
rs1303239997	199	dbSNP
rs1318205691	210	dbSNP
rs2518020	212	dbSNP
rs1383152827	214	dbSNP
rs972433935	215	dbSNP
rs1278949593	231	dbSNP
rs1041837500	234	dbSNP
rs1424261949	237	dbSNP
rs2518021	238	dbSNP
rs1225296899	246	dbSNP
rs909099769	250	dbSNP
rs984692883	251	dbSNP
rs553236705	255	dbSNP
rs1482148125	256	dbSNP
rs1181145685	257	dbSNP
rs1011297433	259	dbSNP
rs1165566429	260	dbSNP
rs1474430694	262	dbSNP
rs545814876	263	dbSNP
rs1193749199	264	dbSNP
rs1448569592	275	dbSNP
rs975865456	276	dbSNP
rs2735605	285	dbSNP
rs1055455527	290	dbSNP
rs751424398	292	dbSNP
rs1266467589	293	dbSNP
rs937045144	294	dbSNP
rs1490407271	302	dbSNP
rs1355074701	303	dbSNP
rs1293419050	310	dbSNP
rs1312664157	312	dbSNP
rs1381688244	313	dbSNP
rs1019967302	314	dbSNP
rs1317491436	322	dbSNP
rs928286339	327	dbSNP
rs1337657885	329	dbSNP
rs1045682886	330	dbSNP
rs1212296494	335	dbSNP
rs1338130017	336	dbSNP
rs575602122	341	dbSNP
rs1202253004	346	dbSNP
rs557245033	347	dbSNP
rs138015223	353	dbSNP
rs1001072272	354	dbSNP
rs574451005	355	dbSNP
rs905400904	356	dbSNP
rs1301667079	366	dbSNP
rs1404662358	367	dbSNP
rs1366435650	372	dbSNP
rs148525689	373	dbSNP
rs1411595229	382	dbSNP
rs942107000	385	dbSNP
rs552814935	389	dbSNP
rs554358640	392	dbSNP
rs1168463455	393	dbSNP
rs117098829	399	dbSNP
rs1270846496	400	dbSNP
rs1030742090	403	dbSNP
rs1221753765	409	dbSNP
rs2735606	412	dbSNP
rs1427012059	413	dbSNP
rs976371464	417	dbSNP
rs1480601316	418	dbSNP
rs567359051	420	dbSNP
rs78146161	421	dbSNP
rs1436766940	422	dbSNP
rs1373286588	424	dbSNP
rs1049046542	425	dbSNP
rs569213763	429	dbSNP
rs2735607	431	dbSNP
rs1173591912	434	dbSNP
rs1011727381	451	dbSNP
rs761825837	454	dbSNP
rs1382424452	458	dbSNP
rs1034141309	463	dbSNP
rs1319290903	469	dbSNP
rs931853215	469	dbSNP
rs921791885	487	dbSNP
rs1001683786	488	dbSNP
rs906875049	489	dbSNP
rs1225829752	497	dbSNP
rs965836825	500	dbSNP
rs1350493758	503	dbSNP
rs913002746	506	dbSNP
rs2735608	507	dbSNP
rs1045771347	508	dbSNP
rs1048750	511	dbSNP
rs1262042861	516	dbSNP
rs988504586	523	dbSNP
rs1196677460	525	dbSNP
rs879363438	529	dbSNP
rs1032629964	530	dbSNP
rs897046865	534	dbSNP
rs73972700	536	dbSNP
rs1440253226	552	dbSNP
rs1354076776	555	dbSNP
rs1329606497	566	dbSNP
rs146972914	567	dbSNP
rs1422926041	575	dbSNP
rs754029299	578	dbSNP
rs1346160328	585	dbSNP
rs1403819354	587	dbSNP
rs1305568463	588	dbSNP
rs192602532	593	dbSNP
rs986270037	594	dbSNP
rs1262810475	595	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.

- 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, 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.

- Genome research, 2016

DNA damage activates TP53-regulated surveillance mechanisms that are crucial in suppressing tumorigenesis. TP53 orchestrates these responses directly by transcriptionally modulating genes, including microRNAs (miRNAs), and by regulating miRNA biogenesis through interacting with the DROSHA complex. However, whether the association between miRNAs and AGO2 is regulated following DNA damage is not yet known. Here, we show that, following DNA damage, TP53 interacts with AGO2 to induce or reduce AGO2's association of a subset of miRNAs, including multiple let-7 family members. Furthermore, we show that specific mutations in TP53 decrease rather than increase the association of let-7 family miRNAs, reducing their activity without preventing TP53 from interacting with AGO2. This is consistent with the oncogenic properties of these mutants. Using AGO2 RIP-seq and PAR-CLIP-seq, we show that the DNA damage-induced increase in binding of let-7 family members to the RISC complex is functional. We unambiguously determine the global miRNA-mRNA interaction networks involved in the DNA damage response, validating them through the identification of miRNA-target chimeras formed by endogenous ligation reactions. We find that the target complementary region of the let-7 seed tends to have highly fixed positions and more variable ones. Additionally, we observe that miRNAs, whose cellular abundance or differential association with AGO2 is regulated by TP53, are involved in an intricate network of regulatory feedback and feedforward circuits. TP53-mediated regulation of AGO2-miRNA interaction represents a new mechanism of miRNA regulation in carcinogenesis.

- 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.