ID	Duplex structure	Position	Score	MFE
1	miRNA 3' uuUUC-AU--UAA---UGUCAAAaa 5' ||| |: ||| ||| || Target 5' atAAGCTGGCATTTCGCCAGCTTgt 3'	718 - 742	91.00	-13.60
2	miRNA 3' uuuucauuaAUGUCAAaaa 5' |:|:||| Target 5' ccgccgcccTGCGGTTggg 3'	428 - 446	90.00	-6.80
3	miRNA 3' uuUUCAUUAAUGUCaaaaa 5' ::| || ||| Target 5' agGGGCCATACCAGggcgc 3'	339 - 357	65.00	-5.40

Mutant ID	Mutant Position	Mutant Source
rs767712037	2	dbSNP
rs753032455	7	dbSNP
rs755955303	8	dbSNP
rs755767509	10	dbSNP
rs777757865	13	dbSNP
rs749204158	16	dbSNP
rs755608626	18	dbSNP
rs930031396	26	dbSNP
rs1267660288	28	dbSNP
rs745321576	36	dbSNP
rs1166240424	37	dbSNP
rs1178275277	37	dbSNP
rs1378155847	39	dbSNP
rs1461397707	44	dbSNP
rs771552016	46	dbSNP
rs775111460	48	dbSNP
rs752177738	67	dbSNP
rs755817753	67	dbSNP
rs781606175	67	dbSNP
rs192249335	76	dbSNP
rs1356187068	77	dbSNP
rs1263787655	78	dbSNP
rs78591831	80	dbSNP
rs1416659096	81	dbSNP
rs76217664	82	dbSNP
rs1350156796	84	dbSNP
rs1224513982	85	dbSNP
rs1226078231	85	dbSNP
rs1344118070	87	dbSNP
rs1297985695	88	dbSNP
rs1364993142	89	dbSNP
rs1436624987	105	dbSNP
rs1168579285	115	dbSNP
rs1353413041	115	dbSNP
rs1286865023	117	dbSNP
rs1004201441	120	dbSNP
rs1392426032	121	dbSNP
rs1428321189	121	dbSNP
rs769454034	125	dbSNP
rs1257059831	131	dbSNP
rs1485724826	143	dbSNP
rs772768826	145	dbSNP
rs1251151670	146	dbSNP
rs1189504043	161	dbSNP
rs1202952483	161	dbSNP
rs1483956374	165	dbSNP
rs1275117579	168	dbSNP
rs1232324867	169	dbSNP
rs1047582651	171	dbSNP
rs1303041696	173	dbSNP
rs1219438085	174	dbSNP
rs1472097655	179	dbSNP
rs1177408987	196	dbSNP
rs748742853	202	dbSNP
rs1349354583	203	dbSNP
rs1016957576	206	dbSNP
rs1408574751	207	dbSNP
rs1372890626	214	dbSNP
rs962929688	220	dbSNP
rs1465887967	229	dbSNP
rs770437312	234	dbSNP
rs1178575909	238	dbSNP
rs1431171668	243	dbSNP
rs886254383	260	dbSNP
rs574351078	263	dbSNP
rs1016173350	265	dbSNP
rs759460075	269	dbSNP
rs1252502696	272	dbSNP
rs1482188025	275	dbSNP
rs1257484283	282	dbSNP
rs900378115	290	dbSNP
rs1436481563	291	dbSNP
rs926751645	297	dbSNP
rs960899338	302	dbSNP
rs1350531015	307	dbSNP
rs1308417773	308	dbSNP
rs774465747	313	dbSNP
rs995861040	314	dbSNP
rs1304888354	317	dbSNP
rs1443279539	318	dbSNP
rs767406073	321	dbSNP
rs1388242604	327	dbSNP
rs1029975975	332	dbSNP
rs954473663	335	dbSNP
rs762281078	336	dbSNP
rs1041336915	342	dbSNP
rs1020912437	343	dbSNP
rs1420755994	352	dbSNP
rs1329308845	358	dbSNP
rs1264287736	361	dbSNP
rs1350728338	385	dbSNP
rs1339185958	387	dbSNP
rs935886853	389	dbSNP
rs968908502	390	dbSNP
rs1364919192	391	dbSNP
rs775326850	401	dbSNP
rs1318855322	413	dbSNP
rs899785501	414	dbSNP
rs760420345	418	dbSNP
rs765451012	429	dbSNP
rs933819497	431	dbSNP
rs1370168119	432	dbSNP
rs927568595	459	dbSNP
rs143804380	463	dbSNP
rs992799074	465	dbSNP
rs917234016	468	dbSNP
rs930083782	471	dbSNP
rs1190123396	479	dbSNP
rs1465015524	481	dbSNP
rs1266089617	489	dbSNP
rs1207501961	494	dbSNP
rs1487398027	497	dbSNP
rs1047132181	498	dbSNP
rs1267824348	500	dbSNP
rs1247335005	514	dbSNP
rs1341917272	515	dbSNP
rs758484637	520	dbSNP
rs886304459	528	dbSNP
rs1327199257	531	dbSNP
rs773615107	533	dbSNP
rs1323122919	538	dbSNP
rs1190459931	543	dbSNP
rs1395424256	563	dbSNP
rs766562096	566	dbSNP
rs1164194132	574	dbSNP
rs372834283	595	dbSNP
rs183405109	597	dbSNP
rs1166628496	600	dbSNP
rs755518226	601	dbSNP
rs900431056	607	dbSNP
rs996082026	614	dbSNP
rs1410562497	630	dbSNP
rs1196302237	632	dbSNP
rs1452891426	650	dbSNP
rs1268908498	659	dbSNP
rs1223888762	660	dbSNP
rs1331153710	662	dbSNP
rs781586836	667	dbSNP
rs1231142124	669	dbSNP
rs868150292	670	dbSNP
rs1030028347	674	dbSNP
rs868109699	675	dbSNP
rs1373624828	677	dbSNP
rs924814209	680	dbSNP
rs1297422703	681	dbSNP
rs1219004829	689	dbSNP
rs1338218979	695	dbSNP
rs1214601010	696	dbSNP
rs1303765848	697	dbSNP
rs1409166163	699	dbSNP
rs1368576174	700	dbSNP
rs866918780	701	dbSNP
rs1043814	702	dbSNP
rs867401491	707	dbSNP
rs1212677116	708	dbSNP
rs1170459319	709	dbSNP
rs1180762941	712	dbSNP
rs1478767484	712	dbSNP
rs1471309750	713	dbSNP
rs1253457743	723	dbSNP
rs1469603609	727	dbSNP
rs1438817283	738	dbSNP
rs1186628024	742	dbSNP
rs1247285659	745	dbSNP
rs1198955450	755	dbSNP
rs1347349586	758	dbSNP
rs1475687950	759	dbSNP
rs1227916558	765	dbSNP
rs1348675099	772	dbSNP
rs1290201177	774	dbSNP
rs890124471	778	dbSNP
rs1358364396	783	dbSNP
rs9887	788	dbSNP
rs1411708874	797	dbSNP
rs887159778	798	dbSNP
rs1415839835	801	dbSNP
rs753062489	832	dbSNP
rs780021977	857	dbSNP
rs1157911897	859	dbSNP
rs1004315963	862	dbSNP
rs1010025654	863	dbSNP
rs1455253701	867	dbSNP
rs1165851440	875	dbSNP
rs756453681	876	dbSNP
rs1470762036	880	dbSNP
rs1237300132	886	dbSNP
rs1016907833	887	dbSNP
rs1264034693	888	dbSNP
rs1462918692	888	dbSNP
rs768586680	888	dbSNP
rs898509471	891	dbSNP
rs12832786	892	dbSNP
rs1327180326	896	dbSNP
rs761042790	904	dbSNP
rs1433301613	907	dbSNP
rs1224300307	909	dbSNP
rs968831613	930	dbSNP
rs1320503123	932	dbSNP
rs1033935549	937	dbSNP
rs961272498	938	dbSNP
rs777423451	941	dbSNP
rs978968955	943	dbSNP
rs1327585061	944	dbSNP
rs1319547658	945	dbSNP
rs878900871	958	dbSNP
rs1034900972	960	dbSNP
rs748938960	962	dbSNP
rs1159147368	967	dbSNP
rs1401820665	981	dbSNP
rs1021554668	986	dbSNP
rs1232316653	995	dbSNP
rs967078742	1010	dbSNP
rs958974628	1013	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.

- 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.