ID	Duplex structure	Position	Score	MFE
1	miRNA 3' guUUGUGGU-AAC-AGUGUGAGGu 5' || |||| ||| |||||||:: Target 5' ttAAGACCAGTTGTTCACACTTTg 3'	1190 - 1213	144.00	-16.70
2	miRNA 3' guUUGUGGUAACAGUGUGAGgu 5' || | ::|| |:|||||| Target 5' ccAAAAATGTT-TTACACTCac 3'	360 - 380	139.00	-10.20
3	miRNA 3' guuUGUGGUAACAGUGUGAGGu 5' :|||| |||||||: Target 5' agtGCACC---CCCACACTCTg 3'	149 - 167	132.00	-14.20

Mutant ID	Mutant Position	Mutant Source
COSN30155822	16	COSMIC
COSN30507290	23	COSMIC
COSN31570612	37	COSMIC
COSN30503424	43	COSMIC
COSN30105203	58	COSMIC
COSN31499287	62	COSMIC
COSN28675627	100	COSMIC
COSN30140384	121	COSMIC
COSN30115137	130	COSMIC
COSN30595677	130	COSMIC
COSN30493084	182	COSMIC
COSN30149122	187	COSMIC
COSN1946277	319	COSMIC
COSN15450188	718	COSMIC
COSN28631948	749	COSMIC
COSN8366156	846	COSMIC
COSN26562415	912	COSMIC
COSN31553393	1203	COSMIC
COSN31523457	1221	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1177894888	3	dbSNP
rs1436055523	5	dbSNP
rs754832857	8	dbSNP
rs751539558	13	dbSNP
rs143168802	16	dbSNP
rs1278390123	18	dbSNP
rs1219098150	20	dbSNP
rs1354814806	26	dbSNP
rs773211510	29	dbSNP
rs764401600	31	dbSNP
rs1217680219	32	dbSNP
rs1342844850	33	dbSNP
rs760986551	35	dbSNP
rs775640855	42	dbSNP
rs763380509	48	dbSNP
rs1310650702	51	dbSNP
rs972581556	54	dbSNP
rs775780310	56	dbSNP
rs547990260	58	dbSNP
rs1383146239	63	dbSNP
rs1300492509	68	dbSNP
rs949172874	71	dbSNP
rs1384649460	87	dbSNP
rs935539006	92	dbSNP
rs11058	100	dbSNP
rs1220057260	101	dbSNP
rs982283249	113	dbSNP
rs533322113	121	dbSNP
rs1305840341	122	dbSNP
rs568561464	125	dbSNP
rs1406241275	130	dbSNP
rs1034388459	132	dbSNP
rs1258697297	132	dbSNP
rs959547149	132	dbSNP
rs1254687820	136	dbSNP
rs978698295	142	dbSNP
rs1185584592	153	dbSNP
rs181674663	157	dbSNP
rs991610643	159	dbSNP
rs866200643	162	dbSNP
rs1461407667	165	dbSNP
rs773461320	167	dbSNP
rs1324410232	175	dbSNP
rs1397161151	176	dbSNP
rs529443889	181	dbSNP
rs191691275	198	dbSNP
rs1193763386	199	dbSNP
rs1216452905	205	dbSNP
rs1278887560	214	dbSNP
rs1334196981	218	dbSNP
rs768585415	220	dbSNP
rs564458427	221	dbSNP
rs1014819544	224	dbSNP
rs1008731158	226	dbSNP
rs890319827	227	dbSNP
rs1484357398	230	dbSNP
rs1263878682	236	dbSNP
rs1193885010	238	dbSNP
rs546340765	256	dbSNP
rs186851865	259	dbSNP
rs1020198729	263	dbSNP
rs1163410995	267	dbSNP
rs1420645643	270	dbSNP
rs1406375218	282	dbSNP
rs1158807988	284	dbSNP
rs1007177485	286	dbSNP
rs1298973698	289	dbSNP
rs996626179	290	dbSNP
rs890002654	291	dbSNP
rs1412937751	300	dbSNP
rs1203091800	301	dbSNP
rs1295118646	315	dbSNP
rs1321440955	331	dbSNP
rs181095231	336	dbSNP
rs1281929926	343	dbSNP
rs1318454251	350	dbSNP
rs995149361	372	dbSNP
rs542003892	379	dbSNP
rs1228706323	380	dbSNP
rs1279085193	389	dbSNP
rs1326219806	398	dbSNP
rs1293860296	407	dbSNP
rs746895392	408	dbSNP
rs896922555	408	dbSNP
rs574875446	425	dbSNP
rs1036809793	430	dbSNP
rs556628357	433	dbSNP
rs13078246	436	dbSNP
rs138727047	437	dbSNP
rs1467806454	445	dbSNP
rs924186365	448	dbSNP
rs1314799894	451	dbSNP
rs1341103087	455	dbSNP
rs1055356147	459	dbSNP
rs937951046	460	dbSNP
rs1168443652	475	dbSNP
rs758120803	480	dbSNP
rs1240599254	489	dbSNP
rs925162456	490	dbSNP
rs1461408785	491	dbSNP
rs1047119543	496	dbSNP
rs949667038	500	dbSNP
rs558594792	505	dbSNP
rs1166612404	509	dbSNP
rs1278748366	509	dbSNP
rs533948686	511	dbSNP
rs913218750	519	dbSNP
rs1231600238	530	dbSNP
rs1442001927	531	dbSNP
rs1179629065	532	dbSNP
rs1394752558	534	dbSNP
rs1452848034	543	dbSNP
rs1174489607	545	dbSNP
rs958417958	550	dbSNP
rs920375873	551	dbSNP
rs566554112	552	dbSNP
rs748060419	553	dbSNP
rs1402356978	560	dbSNP
rs1447305056	568	dbSNP
rs1339308415	574	dbSNP
rs1196939641	583	dbSNP
rs1236064322	585	dbSNP
rs1014837894	588	dbSNP
rs1275015355	594	dbSNP
rs1338186070	595	dbSNP
rs1009196561	596	dbSNP
rs554648498	600	dbSNP
rs536006127	603	dbSNP
rs145907759	605	dbSNP
rs1271573474	609	dbSNP
rs1459460362	610	dbSNP
rs954340229	612	dbSNP
rs1467374577	614	dbSNP
rs754861817	614	dbSNP
rs753522701	631	dbSNP
rs1378422240	635	dbSNP
rs1027212688	640	dbSNP
rs3805075	643	dbSNP
rs1425734733	649	dbSNP
rs996037836	668	dbSNP
rs893875743	675	dbSNP
rs1325078987	679	dbSNP
rs1449943836	682	dbSNP
rs149482251	685	dbSNP
rs999516384	689	dbSNP
rs1323880063	690	dbSNP
rs570766556	694	dbSNP
rs902481315	695	dbSNP
rs1325473381	696	dbSNP
rs1428091346	700	dbSNP
rs1271463407	707	dbSNP
rs1046395237	708	dbSNP
rs1219798540	711	dbSNP
rs1273036542	725	dbSNP
rs376128346	732	dbSNP
rs77579635	738	dbSNP
rs1268381767	739	dbSNP
rs1446604307	749	dbSNP
rs1317883395	753	dbSNP
rs1128199	754	dbSNP
rs1265451118	756	dbSNP
rs1478153465	758	dbSNP
rs1295169248	759	dbSNP
rs868218169	762	dbSNP
rs1054968276	764	dbSNP
rs1163597999	773	dbSNP
rs1055689593	779	dbSNP
rs931506074	781	dbSNP
rs1380192433	793	dbSNP
rs1425098957	803	dbSNP
rs920343222	809	dbSNP
rs1413629046	812	dbSNP
rs766956181	814	dbSNP
rs1293280809	818	dbSNP
rs1339207537	821	dbSNP
rs1247492172	833	dbSNP
rs1163192066	848	dbSNP
rs1442991290	855	dbSNP
rs200700819	860	dbSNP
rs925214244	860	dbSNP
rs1491091234	861	dbSNP
rs1488696507	864	dbSNP
rs866863414	867	dbSNP
rs1187293979	871	dbSNP
rs940454366	871	dbSNP
rs1255377472	878	dbSNP
rs1437807771	881	dbSNP
rs1425520778	883	dbSNP
rs763473927	891	dbSNP
rs753238754	895	dbSNP
rs1249077015	904	dbSNP
rs987175031	947	dbSNP
rs1363025139	952	dbSNP
rs1225285486	962	dbSNP
rs945294303	963	dbSNP
rs913269624	964	dbSNP
rs527881377	967	dbSNP
rs1310512140	968	dbSNP
rs1403667397	980	dbSNP
rs1028932398	981	dbSNP
rs1313986905	983	dbSNP
rs544281374	1000	dbSNP
rs1238425574	1005	dbSNP
rs1311810187	1011	dbSNP
rs1354655673	1014	dbSNP
rs965496334	1019	dbSNP
rs549969873	1024	dbSNP
rs1484244742	1031	dbSNP
rs1200969933	1036	dbSNP
rs564465617	1040	dbSNP
rs551001672	1041	dbSNP
rs1180256225	1046	dbSNP
rs1380574496	1050	dbSNP
rs1453450122	1053	dbSNP
rs1171304692	1059	dbSNP
rs999571739	1061	dbSNP
rs1360397739	1062	dbSNP
rs1466041225	1064	dbSNP
rs1304000459	1069	dbSNP
rs114485182	1071	dbSNP
rs1445090547	1072	dbSNP
rs530245840	1074	dbSNP
rs1333749515	1075	dbSNP
rs1325449349	1076	dbSNP
rs1405418959	1080	dbSNP
rs1364796097	1087	dbSNP
rs954387454	1088	dbSNP
rs1233864806	1094	dbSNP
rs1299382533	1096	dbSNP
rs1027135297	1098	dbSNP
rs762066527	1101	dbSNP
rs1387382896	1106	dbSNP
rs1013615074	1124	dbSNP
rs1456363672	1127	dbSNP
rs895370508	1138	dbSNP
rs995797107	1140	dbSNP
rs1238582423	1141	dbSNP
rs1159312255	1150	dbSNP
rs1469699121	1154	dbSNP
rs562992219	1155	dbSNP
rs1191360900	1158	dbSNP
rs1426820187	1160	dbSNP
rs879930615	1180	dbSNP
rs931474886	1180	dbSNP
rs1015273929	1182	dbSNP
rs1373048263	1184	dbSNP
rs530042078	1192	dbSNP
rs1173385336	1199	dbSNP
rs896255103	1203	dbSNP
rs1033816770	1205	dbSNP
rs1292062081	1206	dbSNP
rs1001946646	1214	dbSNP
rs1449051614	1220	dbSNP
rs1395771382	1221	dbSNP
rs1294989852	1232	dbSNP
rs898634807	1233	dbSNP
rs544583385	1236	dbSNP
rs1204114765	1237	dbSNP
rs1347938122	1239	dbSNP
rs1043534135	1247	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.

- Genes & development, 2013

When adapting to environmental stress, cells attenuate and reprogram their translational output. In part, these altered translation profiles are established through changes in the interactions between RNA-binding proteins and mRNAs. The Argonaute 2 (Ago2)/microRNA (miRNA) machinery has been shown to participate in stress-induced translational up-regulation of a particular mRNA, CAT-1; however, a detailed, transcriptome-wide understanding of the involvement of Ago2 in the process has been lacking. Here, we profiled the overall changes in Ago2-mRNA interactions upon arsenite stress by cross-linking immunoprecipitation (CLIP) followed by high-throughput sequencing (CLIP-seq). Ago2 displayed a significant remodeling of its transcript occupancy, with the majority of 3' untranslated region (UTR) and coding sequence (CDS) sites exhibiting stronger interaction. Interestingly, target sites that were destined for release from Ago2 upon stress were depleted in miRNA complementarity signatures, suggesting an alternative mode of interaction. To compare the changes in Ago2-binding patterns across transcripts with changes in their translational states, we measured mRNA profiles on ribosome/polysome gradients by RNA sequencing (RNA-seq). Increased Ago2 occupancy correlated with stronger repression of translation for those mRNAs, as evidenced by a shift toward lighter gradient fractions upon stress, while release of Ago2 was associated with the limited number of transcripts that remained translated. Taken together, these data point to a role for Ago2 and the mammalian miRNAs in mediating the translational component of the stress response.

- 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.

- 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.