ID	Duplex structure	Position	Score	MFE
1	miRNA 3' ccUCUUCUAAC-----GUCUCAUUUAa 5' ||:|| ||| |:||||| || Target 5' tcAGGAG-TTGGAGAACGGAGTACATt 3'	343 - 368	131.00	-15.40
2	miRNA 3' ccucuucuaacgucuCAUUUAa 5' |||||| Target 5' cattactgcacagttGTAAATa 3'	767 - 788	120.00	-5.60
3	miRNA 3' ccucUUCUAACGUCUCAUUUAa 5' || | | ||||| ||| Target 5' ttgaAACACTACAGAGCCAATa 3'	653 - 674	102.00	-5.41

Mutant ID	Mutant Position	Mutant Source
1205362	207	ClinVar
1189812	225	ClinVar
COSM5424762	39	COSMIC
COSM5427469	99	COSMIC
COSM5790278	103	COSMIC
COSN31584188	490	COSMIC
COSN31532932	497	COSMIC
COSN28824180	524	COSMIC
COSN28824628	525	COSMIC
COSN30165619	536	COSMIC
COSN31552212	591	COSMIC
COSN28776344	616	COSMIC
COSN31487997	665	COSMIC
COSN24982073	681	COSMIC
COSN31593566	694	COSMIC
COSN26640277	782	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1421058390	1	dbSNP
rs571869070	4	dbSNP
rs774845437	5	dbSNP
rs766692111	6	dbSNP
rs763056793	7	dbSNP
rs553564829	8	dbSNP
rs1401104607	10	dbSNP
rs1012817707	11	dbSNP
rs1360556102	12	dbSNP
rs1213469232	14	dbSNP
rs769786860	16	dbSNP
rs752625416	21	dbSNP
rs761812880	26	dbSNP
rs1305826644	28	dbSNP
rs1488495952	29	dbSNP
rs1217789631	31	dbSNP
rs1240272815	34	dbSNP
rs1475082371	35	dbSNP
rs1396166494	36	dbSNP
rs878864180	39	dbSNP
rs1315359053	40	dbSNP
rs1413418688	41	dbSNP
rs1420675351	43	dbSNP
rs1375247298	45	dbSNP
rs1159590339	48	dbSNP
rs1430704207	48	dbSNP
rs1302867430	50	dbSNP
rs1455649704	52	dbSNP
rs1362335771	54	dbSNP
rs776562670	58	dbSNP
rs1424475309	60	dbSNP
rs1056974225	66	dbSNP
rs535148880	67	dbSNP
rs1485280743	68	dbSNP
rs1263773470	69	dbSNP
rs1206726656	70	dbSNP
rs1484763905	73	dbSNP
rs1225255099	80	dbSNP
rs1281936281	81	dbSNP
rs1446338393	82	dbSNP
rs1259852072	84	dbSNP
rs1244980450	85	dbSNP
rs1181882814	86	dbSNP
rs1336328645	89	dbSNP
rs1384837520	91	dbSNP
rs1290855243	92	dbSNP
rs1232036942	93	dbSNP
rs1355430703	97	dbSNP
rs1251676549	98	dbSNP
rs1299328954	98	dbSNP
rs9635535	99	dbSNP
rs934513588	101	dbSNP
rs1288521136	102	dbSNP
rs1458559596	107	dbSNP
rs1377143020	109	dbSNP
rs1396820949	112	dbSNP
rs746872342	114	dbSNP
rs1043568899	115	dbSNP
rs1162926339	115	dbSNP
rs1474907391	117	dbSNP
rs1321408790	121	dbSNP
rs1424321051	121	dbSNP
rs1195235029	122	dbSNP
rs1426524645	123	dbSNP
rs947495759	125	dbSNP
rs1242658065	126	dbSNP
rs1438561121	130	dbSNP
rs1184289215	131	dbSNP
rs1241116230	139	dbSNP
rs1260707660	140	dbSNP
rs1210090113	141	dbSNP
rs1469504310	143	dbSNP
rs1270853482	155	dbSNP
rs373649971	158	dbSNP
rs1317993272	161	dbSNP
rs556116225	166	dbSNP
rs1396624963	168	dbSNP
rs1230183214	172	dbSNP
rs1325071739	174	dbSNP
rs1295252601	177	dbSNP
rs986107567	187	dbSNP
rs1387676704	189	dbSNP
rs1326454577	190	dbSNP
rs1397018515	192	dbSNP
rs1324121525	195	dbSNP
rs1461050082	196	dbSNP
rs1401038010	197	dbSNP
rs1169592455	198	dbSNP
rs1436923509	200	dbSNP
rs1460362669	202	dbSNP
rs1372323662	203	dbSNP
rs1199360239	206	dbSNP
rs1455406213	207	dbSNP
rs1250821709	208	dbSNP
rs1262541917	209	dbSNP
rs1192541739	210	dbSNP
rs1457830907	212	dbSNP
rs1274434860	213	dbSNP
rs1271129590	215	dbSNP
rs1198111674	217	dbSNP
rs1200564824	219	dbSNP
rs1156955418	220	dbSNP
rs1338060251	220	dbSNP
rs1251222362	223	dbSNP
rs1235547589	225	dbSNP
rs1463083579	226	dbSNP
rs1165712429	232	dbSNP
rs3915649	233	dbSNP
rs1395277341	235	dbSNP
rs933559441	237	dbSNP
rs1373644308	240	dbSNP
rs1301533837	241	dbSNP
rs1440374395	244	dbSNP
rs923547032	245	dbSNP
rs1330935593	246	dbSNP
rs1389715737	247	dbSNP
rs1187259532	248	dbSNP
rs1229698635	252	dbSNP
rs1395752022	259	dbSNP
rs1268533345	261	dbSNP
rs1173080093	265	dbSNP
rs1436356021	266	dbSNP
rs1294356419	267	dbSNP
rs1392970042	268	dbSNP
rs1222327353	270	dbSNP
rs1172646201	271	dbSNP
rs1188226705	274	dbSNP
rs1439881017	275	dbSNP
rs1372019164	279	dbSNP
rs1234224637	280	dbSNP
rs1165090130	281	dbSNP
rs1281510801	283	dbSNP
rs1179109277	284	dbSNP
rs1436708344	286	dbSNP
rs972252904	289	dbSNP
rs1212143238	295	dbSNP
rs1206447502	296	dbSNP
rs1350523289	300	dbSNP
rs1387009964	302	dbSNP
rs1380510230	303	dbSNP
rs1264815175	304	dbSNP
rs1364587840	310	dbSNP
rs1278571283	312	dbSNP
rs962555997	313	dbSNP
rs1351728727	314	dbSNP
rs1357634999	316	dbSNP
rs1016442527	319	dbSNP
rs1261727921	321	dbSNP
rs1487106088	326	dbSNP
rs1357136071	327	dbSNP
rs1281470986	330	dbSNP
rs1184960469	332	dbSNP
rs1237049948	338	dbSNP
rs1335174760	339	dbSNP
rs1443674502	345	dbSNP
rs1313419669	350	dbSNP
rs1365347282	358	dbSNP
rs984239899	359	dbSNP
rs952460448	363	dbSNP
rs1373425596	366	dbSNP
rs1453459508	368	dbSNP
rs1338862387	370	dbSNP
rs1022610244	372	dbSNP
rs1312093953	372	dbSNP
rs1012617887	375	dbSNP
rs1308104244	376	dbSNP
rs1409780906	382	dbSNP
rs1319108124	386	dbSNP
rs1237442734	396	dbSNP
rs895718313	397	dbSNP
rs1324968638	402	dbSNP
rs1204982623	408	dbSNP
rs1240781396	408	dbSNP
rs1415611015	409	dbSNP
rs1460563594	410	dbSNP
rs1177460108	412	dbSNP
rs1326134896	415	dbSNP
rs1252326304	416	dbSNP
rs1417099801	423	dbSNP
rs1180896716	430	dbSNP
rs1429906814	431	dbSNP
rs1036056044	433	dbSNP
rs1399812914	433	dbSNP
rs1404035947	434	dbSNP
rs1465669771	435	dbSNP
rs1160178820	437	dbSNP
rs537491492	438	dbSNP
rs998691866	441	dbSNP
rs1379658221	442	dbSNP
rs1158102349	443	dbSNP
rs1437973277	446	dbSNP
rs902976260	450	dbSNP
rs1204713051	451	dbSNP
rs1239431895	452	dbSNP
rs1188516920	456	dbSNP
rs1442150180	459	dbSNP
rs1481352204	460	dbSNP
rs1197193218	461	dbSNP
rs570431705	467	dbSNP
rs1171303992	472	dbSNP
rs1219297696	473	dbSNP
rs1460702245	475	dbSNP
rs1355018359	481	dbSNP
rs889227019	484	dbSNP
rs1407225974	486	dbSNP
rs552556068	487	dbSNP
rs751112582	490	dbSNP
rs933361670	497	dbSNP
rs3852752	498	dbSNP
rs1305381798	499	dbSNP
rs534341577	500	dbSNP
rs1292142512	501	dbSNP
rs1490782627	510	dbSNP
rs1220049722	515	dbSNP
rs1246049802	515	dbSNP
rs1036986225	519	dbSNP
rs1187160720	521	dbSNP
rs1421769133	525	dbSNP
rs1426921458	527	dbSNP
rs1168205841	528	dbSNP
rs1484604439	529	dbSNP
rs1299777513	530	dbSNP
rs548830025	534	dbSNP
rs1359811142	538	dbSNP
rs1301757340	540	dbSNP
rs940957049	542	dbSNP
rs909350634	543	dbSNP
rs1290071746	544	dbSNP
rs984991418	546	dbSNP
rs1227136052	547	dbSNP
rs1361238159	549	dbSNP
rs1416072704	549	dbSNP
rs1164006926	553	dbSNP
rs1243456499	554	dbSNP
rs1288939449	555	dbSNP
rs1317393144	557	dbSNP
rs1217904384	558	dbSNP
rs952428603	561	dbSNP
rs1472572403	562	dbSNP
rs530199713	563	dbSNP
rs991151565	567	dbSNP
rs1488859520	569	dbSNP
rs563008497	570	dbSNP
rs1161808222	575	dbSNP
rs1413556805	577	dbSNP
rs550948278	578	dbSNP
rs1161926054	580	dbSNP
rs532354087	580	dbSNP
rs1336861862	581	dbSNP
rs1290009448	589	dbSNP
rs1283342096	591	dbSNP
rs1351138802	599	dbSNP
rs1021863923	601	dbSNP
rs1282050855	602	dbSNP
rs1328484032	606	dbSNP
rs1208155664	614	dbSNP
rs1263890428	616	dbSNP
rs1462789259	636	dbSNP
rs1185690924	638	dbSNP
rs1237202183	648	dbSNP
rs1470707914	662	dbSNP
rs1179385410	663	dbSNP
rs1353794259	680	dbSNP
rs1410356468	681	dbSNP
rs1011386930	682	dbSNP
rs1219011736	683	dbSNP
rs1176457089	687	dbSNP
rs1339605052	689	dbSNP
rs1333112855	691	dbSNP
rs1336044482	694	dbSNP
rs557062401	695	dbSNP
rs889194367	700	dbSNP
rs1349777927	701	dbSNP
rs1050502629	702	dbSNP
rs1283963801	719	dbSNP
rs1276165253	720	dbSNP
rs55681374	726	dbSNP
rs1278178541	737	dbSNP
rs1438646061	738	dbSNP
rs1207036529	744	dbSNP
rs1250092033	745	dbSNP
rs1472527907	752	dbSNP
rs1200787845	753	dbSNP
rs997562240	768	dbSNP
rs1476749311	769	dbSNP
rs1171558231	770	dbSNP
rs9652637	782	dbSNP
rs1411357477	786	dbSNP
rs1187042517	794	dbSNP
rs1405415552	794	dbSNP
rs760895886	796	dbSNP
rs901803808	804	dbSNP
rs567192174	813	dbSNP
rs1036385658	819	dbSNP
rs565289288	827	dbSNP
rs1392545107	834	dbSNP
rs940912986	836	dbSNP
rs1049677721	840	dbSNP
rs751136608	840	dbSNP
rs948241796	840	dbSNP
rs1482941527	842	dbSNP
rs554067405	847	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.