ID	Duplex structure	Position	Score	MFE
1	miRNA 3' acccgAAAGAUCAGAGUCGAGa 5' ||||| | :||||||| Target 5' tgtcaTTTCT-GCTTCAGCTCt 3'	75 - 95	160.00	-16.20
2	miRNA 3' acccGAAAGAUCA-GAGUCGAga 5' | | |:|| |:|||| Target 5' gtaaCCTGATGGTAATTAGCTgg 3'	122 - 144	110.00	-6.60
3	miRNA 3' acCCGAAAGAUCAG-AGUCGaga 5' ||| || |: || |:||: Target 5' -gGGCCTT-TGTTCTTTAGTatg 3'	1 - 21	87.00	-7.52

Mutant ID	Mutant Position	Mutant Source
COSM7759787	4	COSMIC
COSN26979432	6	COSMIC
COSN30113567	8	COSMIC
COSN30193057	10	COSMIC
COSN26979433	11	COSMIC
COSN30510635	17	COSMIC
COSN30154461	32	COSMIC
COSN14219180	51	COSMIC
COSN32053496	79	COSMIC
COSN30169835	90	COSMIC
COSN20857905	93	COSMIC
COSN21627112	101	COSMIC
COSN30574755	113	COSMIC
COSN1331318	122	COSMIC
COSN30709645	124	COSMIC
COSN30502458	153	COSMIC
COSN31486824	178	COSMIC
COSN31547491	264	COSMIC
COSN18769819	271	COSMIC
COSN8514044	271	COSMIC
COSN25757655	296	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs776661762	3	dbSNP
rs1381457173	4	dbSNP
rs374210554	4	dbSNP
rs1206725726	5	dbSNP
rs1254527597	8	dbSNP
rs1470825022	10	dbSNP
rs372841582	13	dbSNP
rs1472296430	16	dbSNP
rs1379454709	20	dbSNP
rs775184193	21	dbSNP
rs1425766708	22	dbSNP
rs185921924	25	dbSNP
rs763791273	26	dbSNP
rs376092958	28	dbSNP
rs895550052	29	dbSNP
rs141231210	30	dbSNP
rs1218493533	31	dbSNP
rs370072638	31	dbSNP
rs1355006764	35	dbSNP
rs749927695	44	dbSNP
rs1300853557	45	dbSNP
rs1488529722	46	dbSNP
rs1402329325	47	dbSNP
rs756621240	47	dbSNP
rs1228680570	50	dbSNP
rs1285219732	51	dbSNP
rs770756887	51	dbSNP
rs780607464	53	dbSNP
rs1346436683	55	dbSNP
rs1490546012	57	dbSNP
rs1274952613	60	dbSNP
rs1224798121	62	dbSNP
rs1271047574	64	dbSNP
rs1402236515	65	dbSNP
rs1020378280	68	dbSNP
rs1477001976	73	dbSNP
rs1190492622	83	dbSNP
rs967526102	87	dbSNP
rs896809973	88	dbSNP
rs1173200429	91	dbSNP
rs565503358	93	dbSNP
rs146946127	95	dbSNP
rs1427450031	98	dbSNP
rs1033675939	102	dbSNP
rs1359472597	111	dbSNP
rs964359227	114	dbSNP
rs55965437	117	dbSNP
rs77674559	117	dbSNP
rs9281590	117	dbSNP
rs3036297	118	dbSNP
rs1444096883	127	dbSNP
rs1056759343	130	dbSNP
rs896320682	134	dbSNP
rs1199374236	142	dbSNP
rs1342343577	146	dbSNP
rs1279625863	149	dbSNP
rs531028875	159	dbSNP
rs922652254	161	dbSNP
rs1277994912	163	dbSNP
rs955418752	170	dbSNP
rs549822168	171	dbSNP
rs982878795	173	dbSNP
rs866683666	178	dbSNP
rs907677097	188	dbSNP
rs1422604930	191	dbSNP
rs757378302	201	dbSNP
rs1473684834	204	dbSNP
rs1360431140	206	dbSNP
rs1224919215	207	dbSNP
rs564834394	208	dbSNP
rs1459545091	217	dbSNP
rs940510726	221	dbSNP
rs1289700388	222	dbSNP
rs1198838023	228	dbSNP
rs1451056542	245	dbSNP
rs1220777326	249	dbSNP
rs1061623	250	dbSNP
rs970168513	251	dbSNP
rs1255810742	253	dbSNP
rs1213168316	258	dbSNP
rs1381883908	260	dbSNP
rs1000261968	261	dbSNP
rs1362279347	262	dbSNP
rs1447966537	262	dbSNP
rs1168683033	263	dbSNP
rs1333482249	263	dbSNP
rs1380611889	263	dbSNP
rs1399810316	263	dbSNP
rs1447664169	263	dbSNP
rs932796547	263	dbSNP
rs1233353386	264	dbSNP
rs1162534393	265	dbSNP
rs1414273360	265	dbSNP
rs1442731145	265	dbSNP
rs1239982341	266	dbSNP
rs1178688227	267	dbSNP
rs1223323952	267	dbSNP
rs1230817281	267	dbSNP
rs1240951280	267	dbSNP
rs1245833421	267	dbSNP
rs1291069273	267	dbSNP
rs1296605074	267	dbSNP
rs1312162299	267	dbSNP
rs1323824582	267	dbSNP
rs1357887181	267	dbSNP
rs1438901175	267	dbSNP
rs530326021	267	dbSNP
rs746474434	267	dbSNP
rs9267570	267	dbSNP
rs1350207908	268	dbSNP
rs1481519659	269	dbSNP
rs55960422	270	dbSNP
rs570618722	270	dbSNP
rs1221054406	271	dbSNP
rs1222191939	271	dbSNP
rs1241520907	271	dbSNP
rs1245814918	271	dbSNP
rs1288693248	271	dbSNP
rs1304993217	271	dbSNP
rs1316361011	271	dbSNP
rs1488623591	271	dbSNP
rs1489979426	271	dbSNP
rs1491147194	271	dbSNP
rs668558	271	dbSNP
rs757877151	271	dbSNP
rs9279427	271	dbSNP
rs920493087	272	dbSNP
rs1444873789	273	dbSNP
rs937296635	273	dbSNP
rs200566756	274	dbSNP
rs28628780	274	dbSNP
rs7740730	275	dbSNP
rs903502904	276	dbSNP
rs955576176	277	dbSNP
rs986067505	278	dbSNP
rs911389750	279	dbSNP
rs41270537	280	dbSNP
rs1331101014	281	dbSNP
rs1013924695	282	dbSNP
rs941139222	283	dbSNP
rs1248470025	284	dbSNP
rs866051184	285	dbSNP
rs1038074304	286	dbSNP
rs1259534439	287	dbSNP
rs1282599051	292	dbSNP
rs1212318935	293	dbSNP
rs1312915632	293	dbSNP
rs1472502063	294	dbSNP
rs1177619895	295	dbSNP
rs1221926642	295	dbSNP
rs1342090229	295	dbSNP
rs1355776151	296	dbSNP
rs1359760780	297	dbSNP
rs34396430	298	dbSNP
rs1431818963	299	dbSNP
rs1273696887	300	dbSNP
rs1468733657	302	dbSNP
rs1173749659	308	dbSNP
rs1309184055	311	dbSNP
rs1466887631	316	dbSNP
rs778921535	318	dbSNP
rs1423941184	319	dbSNP
rs1196608679	320	dbSNP
rs745741102	323	dbSNP
rs1237360824	327	dbSNP
rs1461567631	329	dbSNP
rs1185085493	331	dbSNP
rs1235354486	336	dbSNP
rs547116736	337	dbSNP
rs1167985519	339	dbSNP
rs201449275	340	dbSNP
rs918268391	341	dbSNP
rs1170531230	344	dbSNP
rs1407334601	348	dbSNP
rs1320231693	350	dbSNP
rs1223680605	351	dbSNP
rs929590185	352	dbSNP
rs1332496391	356	dbSNP
rs1340080570	358	dbSNP
rs1226408819	359	dbSNP
rs1000762955	360	dbSNP
rs565973902	364	dbSNP
rs1314700622	370	dbSNP
rs1396556347	373	dbSNP
rs1033211672	375	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.

- 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.