ID	Duplex structure	Position	Score	MFE
1	miRNA 3' uuaCCAUUACC--AAGAGAACGAu 5' ||| :| | ||:||||||| Target 5' ctcGGTTGTCGTTTTTTCTTGCTg 3'	330 - 353	161.00	-13.20
2	miRNA 3' uuACC---AUUACCAAGAGAACGAu 5' ||| ||| | ||| |||| Target 5' ttTGGCCTTAACG---CTCCTGCTg 3'	401 - 422	121.00	-9.59
3	miRNA 3' uuACCAUUACCAAG--------AGAACgau 5' || || || ||| ||||| Target 5' gcTGCTATTGATTCAGGGTCTGTCTTGgag 3'	820 - 849	114.00	-8.50

Mutant ID	Mutant Position	Mutant Source
COSN16469414	42	COSMIC
COSN31492178	52	COSMIC
COSN31780378	90	COSMIC
COSN30671312	155	COSMIC
COSN8904564	618	COSMIC
COSN31607667	784	COSMIC
COSN31486623	843	COSMIC
COSN20117392	901	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs772613650	1	dbSNP
rs1267422323	3	dbSNP
rs373892212	5	dbSNP
rs981721985	6	dbSNP
rs1250870633	7	dbSNP
rs370562083	8	dbSNP
rs781173026	8	dbSNP
rs757121535	16	dbSNP
rs748130722	17	dbSNP
rs751574645	17	dbSNP
rs767091362	18	dbSNP
rs190660961	20	dbSNP
rs749437346	24	dbSNP
rs1222676068	25	dbSNP
rs780386723	29	dbSNP
rs756133021	37	dbSNP
rs1405530845	38	dbSNP
rs1043954	39	dbSNP
rs1395641976	40	dbSNP
rs745901218	43	dbSNP
rs1295707403	45	dbSNP
rs781254076	45	dbSNP
rs988873522	45	dbSNP
rs957424152	47	dbSNP
rs757721033	48	dbSNP
rs763940160	48	dbSNP
rs752110353	49	dbSNP
rs1257763966	54	dbSNP
rs764411173	56	dbSNP
rs759601970	59	dbSNP
rs1316762838	64	dbSNP
rs1033124724	67	dbSNP
rs753421419	74	dbSNP
rs370967729	76	dbSNP
rs1434321211	78	dbSNP
rs564133279	79	dbSNP
rs1258671429	82	dbSNP
rs1194166701	85	dbSNP
rs760252426	86	dbSNP
rs772743341	88	dbSNP
rs1203215752	93	dbSNP
rs1321646113	94	dbSNP
rs1242433638	95	dbSNP
rs1264812396	96	dbSNP
rs889666362	102	dbSNP
rs756817655	105	dbSNP
rs145910827	106	dbSNP
rs774467193	108	dbSNP
rs1157374529	110	dbSNP
rs1365865886	112	dbSNP
rs1392659780	113	dbSNP
rs888840637	114	dbSNP
rs565757766	117	dbSNP
rs555286659	119	dbSNP
rs776717426	121	dbSNP
rs946424732	121	dbSNP
rs914875842	123	dbSNP
rs1466821457	124	dbSNP
rs775159475	132	dbSNP
rs1180235130	133	dbSNP
rs1420978804	134	dbSNP
rs1238920149	138	dbSNP
rs769990904	139	dbSNP
rs746107012	142	dbSNP
rs764054898	143	dbSNP
rs757367185	144	dbSNP
rs9956	148	dbSNP
rs1349635618	151	dbSNP
rs1258917030	153	dbSNP
rs778311383	155	dbSNP
rs1317416420	156	dbSNP
rs937468978	157	dbSNP
rs758846093	158	dbSNP
rs1449820061	161	dbSNP
rs753041772	163	dbSNP
rs982074026	164	dbSNP
rs112124795	165	dbSNP
rs913499359	166	dbSNP
rs1420093082	167	dbSNP
rs1176153522	171	dbSNP
rs1397004616	172	dbSNP
rs553278213	173	dbSNP
rs142338374	174	dbSNP
rs1157170384	176	dbSNP
rs1178008209	180	dbSNP
rs16989329	181	dbSNP
rs952109913	185	dbSNP
rs1425478202	186	dbSNP
rs192748127	188	dbSNP
rs985544123	191	dbSNP
rs14034	192	dbSNP
rs1256437558	193	dbSNP
rs112588915	196	dbSNP
rs1307041245	198	dbSNP
rs1200710274	199	dbSNP
rs1319053568	204	dbSNP
rs1481074059	205	dbSNP
rs993752178	212	dbSNP
rs962232571	213	dbSNP
rs1019081776	214	dbSNP
rs1200842279	216	dbSNP
rs759811950	217	dbSNP
rs1419391964	223	dbSNP
rs1312871443	228	dbSNP
rs1390346696	235	dbSNP
rs1167690833	241	dbSNP
rs1355935548	243	dbSNP
rs1373950198	249	dbSNP
rs537166993	255	dbSNP
rs1302340161	264	dbSNP
rs1343352637	273	dbSNP
rs568129622	277	dbSNP
rs1406516361	278	dbSNP
rs532850581	281	dbSNP
rs1050211890	282	dbSNP
rs1212940474	283	dbSNP
rs62237834	284	dbSNP
rs1162508951	285	dbSNP
rs1459420415	287	dbSNP
rs564521196	288	dbSNP
rs548858129	292	dbSNP
rs371086916	293	dbSNP
rs927838123	294	dbSNP
rs1223688335	296	dbSNP
rs1046283208	297	dbSNP
rs777285508	299	dbSNP
rs1184259638	303	dbSNP
rs547314330	311	dbSNP
rs769004602	312	dbSNP
rs146860075	314	dbSNP
rs1162585707	315	dbSNP
rs947936260	319	dbSNP
rs113834145	320	dbSNP
rs1323952936	323	dbSNP
rs991624263	325	dbSNP
rs1252828041	328	dbSNP
rs150235206	333	dbSNP
rs1358861783	336	dbSNP
rs1366086995	338	dbSNP
rs544164247	339	dbSNP
rs1313280647	347	dbSNP
rs1361849795	351	dbSNP
rs935949432	352	dbSNP
rs1238886557	354	dbSNP
rs1445803273	362	dbSNP
rs111353864	363	dbSNP
rs1310804218	364	dbSNP
rs1240493556	365	dbSNP
rs1182439324	370	dbSNP
rs562235098	372	dbSNP
rs1369754744	375	dbSNP
rs1163625921	377	dbSNP
rs1406916741	388	dbSNP
rs1398718696	402	dbSNP
rs1321383430	407	dbSNP
rs1389283958	410	dbSNP
rs985919611	410	dbSNP
rs770455980	412	dbSNP
rs1288234192	413	dbSNP
rs541952690	414	dbSNP
rs1009547874	419	dbSNP
rs141548250	424	dbSNP
rs368523375	424	dbSNP
rs573034129	425	dbSNP
rs1440603482	431	dbSNP
rs8461	436	dbSNP
rs1202495897	437	dbSNP
rs1010658535	438	dbSNP
rs1240653412	438	dbSNP
rs893511636	444	dbSNP
rs1187879776	450	dbSNP
rs1231923829	450	dbSNP
rs1468471078	458	dbSNP
rs1160075872	461	dbSNP
rs1052114293	464	dbSNP
rs1469171426	469	dbSNP
rs745519052	473	dbSNP
rs1174413073	475	dbSNP
rs546121487	483	dbSNP
rs1408325470	485	dbSNP
rs1396653505	488	dbSNP
rs17833937	490	dbSNP
rs756728392	491	dbSNP
rs1444886742	496	dbSNP
rs1289312775	500	dbSNP
rs947960143	501	dbSNP
rs1222177451	506	dbSNP
rs916459347	507	dbSNP
rs952354596	509	dbSNP
rs557012184	511	dbSNP
rs1002303947	515	dbSNP
rs537079763	517	dbSNP
rs184099760	521	dbSNP
rs1480080525	526	dbSNP
rs1197244733	528	dbSNP
rs920654166	529	dbSNP
rs1014423794	531	dbSNP
rs9287	548	dbSNP
rs1394621836	550	dbSNP
rs1234892922	551	dbSNP
rs1411801959	552	dbSNP
rs772033089	552	dbSNP
rs1309051648	554	dbSNP
rs562190455	555	dbSNP
rs534412537	560	dbSNP
rs1398136826	567	dbSNP
rs151056328	568	dbSNP
rs1332167066	569	dbSNP
rs1233362255	576	dbSNP
rs1300160401	580	dbSNP
rs925921058	581	dbSNP
rs1420406234	589	dbSNP
rs1401513187	593	dbSNP
rs987779654	595	dbSNP
rs2273263	596	dbSNP
rs1490135361	598	dbSNP
rs1219968844	601	dbSNP
rs1269442410	610	dbSNP
rs1049731819	613	dbSNP
rs2273262	614	dbSNP
rs1371365216	618	dbSNP
rs1479126010	619	dbSNP
rs778734873	620	dbSNP
rs1193365316	624	dbSNP
rs1365183540	626	dbSNP
rs1423200386	632	dbSNP
rs1477148904	636	dbSNP
rs142815539	639	dbSNP
rs1217933731	643	dbSNP
rs1392092560	654	dbSNP
rs1485069206	655	dbSNP
rs570841953	667	dbSNP
rs1382119566	668	dbSNP
rs1294263346	674	dbSNP
rs922700344	675	dbSNP
rs990025054	676	dbSNP
rs1229927060	677	dbSNP
rs1297961220	679	dbSNP
rs1201892680	693	dbSNP
rs961154365	694	dbSNP
rs957792743	696	dbSNP
rs1345268611	698	dbSNP
rs1204428421	700	dbSNP
rs1250600242	704	dbSNP
rs1466363544	706	dbSNP
rs777635611	710	dbSNP
rs1030781085	715	dbSNP
rs1384863481	720	dbSNP
rs908398131	721	dbSNP
rs999262904	723	dbSNP
rs1453475854	730	dbSNP
rs373454574	741	dbSNP
rs1391460022	742	dbSNP
rs1436715768	751	dbSNP
rs1320569437	754	dbSNP
rs980456360	761	dbSNP
rs970839000	762	dbSNP
rs755687162	763	dbSNP
rs573748053	770	dbSNP
rs906232907	771	dbSNP
rs1258951917	774	dbSNP
rs1331062915	778	dbSNP
rs1414019283	782	dbSNP
rs1009739675	784	dbSNP
rs1460171647	786	dbSNP
rs1183872388	787	dbSNP
rs1025060924	790	dbSNP
rs1257090848	792	dbSNP
rs1418923731	799	dbSNP
rs754883184	801	dbSNP
rs891939891	801	dbSNP
rs113604273	802	dbSNP
rs1000389755	804	dbSNP
rs895023268	805	dbSNP
rs1464085776	814	dbSNP
rs530857652	826	dbSNP
rs1379428353	829	dbSNP
rs1390620937	836	dbSNP
rs561925561	839	dbSNP
rs931161451	840	dbSNP
rs1416425868	849	dbSNP
rs543265158	859	dbSNP
rs932664191	861	dbSNP
rs1228882865	863	dbSNP
rs528529904	865	dbSNP
rs559520500	872	dbSNP
rs901170573	877	dbSNP
rs754073862	878	dbSNP
rs1044085	879	dbSNP
rs577097646	881	dbSNP
rs1480395871	889	dbSNP
rs940128375	890	dbSNP
rs940774425	897	dbSNP
rs1254367307	899	dbSNP
rs192033326	904	dbSNP
rs57244207	904	dbSNP
rs796405513	904	dbSNP
rs1427776844	910	dbSNP
rs11556540	912	dbSNP
rs987843843	913	dbSNP
rs1359388011	918	dbSNP
rs1461139309	923	dbSNP
rs1442683575	934	dbSNP
rs368948625	937	dbSNP
rs932264641	938	dbSNP
rs1319745032	940	dbSNP
rs979924491	942	dbSNP
rs981100869	942	dbSNP
rs922152910	943	dbSNP
rs970385821	966	dbSNP
rs1221026870	979	dbSNP
rs989730867	986	dbSNP
rs1025073979	992	dbSNP
rs1202632637	993	dbSNP
rs958222471	994	dbSNP
rs987864017	995	dbSNP
rs956424658	1000	dbSNP
rs1032122885	1002	dbSNP
rs1031167752	1005	dbSNP
rs1232660970	1005	dbSNP
rs1479252691	1006	dbSNP
rs534592837	1007	dbSNP
rs1425201951	1010	dbSNP
rs1427389438	1011	dbSNP
rs1166376885	1013	dbSNP
rs1391630704	1014	dbSNP
rs747705743	1019	dbSNP
rs1282537451	1023	dbSNP
rs1430226767	1023	dbSNP
rs904729383	1024	dbSNP
rs1414768071	1025	dbSNP
rs1028534742	1030	dbSNP
rs1294216171	1031	dbSNP
rs997513489	1031	dbSNP
rs15086	1033	dbSNP
rs1341086866	1036	dbSNP
rs901152194	1043	dbSNP
rs1330954406	1048	dbSNP
rs1404094416	1049	dbSNP
rs977877040	1051	dbSNP
rs1245707720	1052	dbSNP
rs1288122074	1054	dbSNP
rs1453859592	1056	dbSNP
rs1444754918	1057	dbSNP
rs1041426712	1061	dbSNP
rs970428524	1062	dbSNP
rs1171819913	1069	dbSNP
rs887187279	1074	dbSNP
rs1449623316	1075	dbSNP
rs147874911	1077	dbSNP
rs1165466870	1078	dbSNP
rs1406854600	1079	dbSNP
rs1165446622	1080	dbSNP
rs1344529791	1083	dbSNP
rs562756194	1085	dbSNP
rs1322560079	1089	dbSNP
rs1236961811	1090	dbSNP
rs187527449	1102	dbSNP
rs1458804207	1108	dbSNP
rs1238612308	1110	dbSNP
rs1282623972	1110	dbSNP
rs1229248504	1117	dbSNP
rs1284253499	1120	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, 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.