>BARHL1|NM_020064|3'UTR
   1 GGCGCCCGTCGGCTCCGGGGCCTCCTCCCGCGGGCTCGGCGTGGCCCCTTCCGCCCGCCTTTCTGAGGGCGCAGGTTCGA
  81 CGCCCTTTCCCGGGAGGGGGCCCTGCCCGGCCCTCCCTGGCGCCCCAGCCCAGTGCCCCCCGAAGGGCCAAATGCCAAGT
 161 CCACTGAGGCCCGGACCCCGGACTGCGTCTCCCCAGCCCCCCTCGGCGTCCTCTCTCGCGGCCGCTCTGTCCGGGAGCCA
 241 TCCCCACCCGCCGGGTGTACATACGCGTCTCTGCCACTCCCCACCCCCAGCCTCTGCCGGCTCCCCTAGGCAACCCCTTT
 321 CTCCCCAGGAGCGGGTGCGGCTGATTCCCAGGCTTCGCTCTCTCCCACGCCCCTTCTACGCTCCAGGTGGAGAACAGCCC
 401 CTCTCCCCGCGCCCCCGCCAGGGAGAGAAGGGGAGTGCGGAGCCCCGTCTCCCTACCCCTCGAGCACCTGGGCCAGCGGC
 481 TGAGCTGTACATACCGTGTGCAAAGTGTATATGAAGTTATTTATTCGTGACCCATGAGCCCGTGACCGTGTCCGTGGATT
 561 AGTGAGTCTGTGGCCTGTGCCCTCCCCACTCCCAGGCGGGGCAGGAAGGGGCCAAGGGGGCTTGCCCACCCACCCCGACC
 641 CCAGCCCCCAGCCTCAGCCCCGGTCCGGGGGCAGCCAGGCCTCTCGGGTTCTCTCTTTTTTAAATGTCGAAATAAACTTC
 721 TTACAAATGAC

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' guGCAGUCACUGACGCGGGGGa 5' | || | | |||||||| Target 5' ccCCTC--TCCCCGCGCCCCCg 3'	398 - 417	148.00	-17.60
2	miRNA 3' gugCAGUCACU-GACGCGGGGGa 5' ||| |||: |||:||||:| Target 5' tgaGTCTGTGGCCTGTGCCCTCc 3'	563 - 585	143.00	-26.40
3	miRNA 3' gugcagucaCUGACGCGGGGGa 5' |||||||:|:|| Target 5' cggaccccgGACTGCGTCTCCc 3'	172 - 193	133.00	-22.00

Mutant ID	Mutant Position	Mutant Source
COSN20964551	83	COSMIC
COSN26509569	424	COSMIC
COSN28768821	462	COSMIC
COSN30172818	463	COSMIC
COSN26549256	615	COSMIC
COSN25814135	629	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1382175105	3	dbSNP
rs1015427045	4	dbSNP
rs1317560337	5	dbSNP
rs770089340	7	dbSNP
rs1348653007	8	dbSNP
rs1255945251	9	dbSNP
rs775809318	13	dbSNP
rs1309945806	14	dbSNP
rs1462943343	17	dbSNP
rs751962982	18	dbSNP
rs573017447	19	dbSNP
rs1182449699	20	dbSNP
rs1180928027	23	dbSNP
rs534482691	24	dbSNP
rs1246126711	25	dbSNP
rs921819410	27	dbSNP
rs985384907	31	dbSNP
rs930599713	35	dbSNP
rs925782870	36	dbSNP
rs1177333871	41	dbSNP
rs1488103625	53	dbSNP
rs1049357281	54	dbSNP
rs957433513	58	dbSNP
rs1161306287	61	dbSNP
rs1322049324	63	dbSNP
rs886309801	66	dbSNP
rs1004632799	67	dbSNP
rs1412796758	69	dbSNP
rs988553342	71	dbSNP
rs1392087766	83	dbSNP
rs896246788	84	dbSNP
rs912984461	85	dbSNP
rs949856674	86	dbSNP
rs1023320773	88	dbSNP
rs766910569	91	dbSNP
rs926984432	92	dbSNP
rs1342721783	94	dbSNP
rs937567927	99	dbSNP
rs956853942	102	dbSNP
rs569663757	109	dbSNP
rs1284041602	110	dbSNP
rs1206653896	114	dbSNP
rs1049348275	117	dbSNP
rs1270201522	122	dbSNP
rs887913359	123	dbSNP
rs1311615131	130	dbSNP
rs879268651	137	dbSNP
rs1299283882	139	dbSNP
rs1221431321	141	dbSNP
rs1372434997	142	dbSNP
rs1005480780	149	dbSNP
rs1230922224	161	dbSNP
rs552896782	163	dbSNP
rs183364605	164	dbSNP
rs975365320	175	dbSNP
rs1375363839	177	dbSNP
rs577830460	182	dbSNP
rs1454649910	188	dbSNP
rs1389534969	191	dbSNP
rs1201051886	197	dbSNP
rs919968991	197	dbSNP
rs930548772	197	dbSNP
rs1258335461	198	dbSNP
rs544968589	200	dbSNP
rs984764256	201	dbSNP
rs1254317435	202	dbSNP
rs1213173858	203	dbSNP
rs1349191516	209	dbSNP
rs1297463928	216	dbSNP
rs901911676	217	dbSNP
rs907787204	218	dbSNP
rs997583167	219	dbSNP
rs1028949972	221	dbSNP
rs1296748386	223	dbSNP
rs940474544	227	dbSNP
rs1056326137	230	dbSNP
rs953414761	234	dbSNP
rs1006722285	236	dbSNP
rs1033360027	238	dbSNP
rs1166573025	242	dbSNP
rs947811203	244	dbSNP
rs557272579	245	dbSNP
rs1186646094	247	dbSNP
rs1387861469	248	dbSNP
rs1461052919	249	dbSNP
rs989035326	250	dbSNP
rs1274033541	251	dbSNP
rs913089095	251	dbSNP
rs1403711913	254	dbSNP
rs1394853934	256	dbSNP
rs1342166254	261	dbSNP
rs1252242537	262	dbSNP
rs971133945	263	dbSNP
rs575107312	265	dbSNP
rs926910972	278	dbSNP
rs1415030322	283	dbSNP
rs1349261537	285	dbSNP
rs1305711531	286	dbSNP
rs1031217014	291	dbSNP
rs1366420510	299	dbSNP
rs892732950	300	dbSNP
rs1162401182	306	dbSNP
rs1008326265	314	dbSNP
rs542676027	319	dbSNP
rs1295696850	333	dbSNP
rs1049320115	339	dbSNP
rs394916	342	dbSNP
rs560928442	350	dbSNP
rs909468544	357	dbSNP
rs1180182934	367	dbSNP
rs1440041555	369	dbSNP
rs1257879197	373	dbSNP
rs1342929522	374	dbSNP
rs1209805048	375	dbSNP
rs757690165	381	dbSNP
rs1275442781	383	dbSNP
rs1262388154	387	dbSNP
rs1465186193	393	dbSNP
rs1328120038	396	dbSNP
rs1190200774	397	dbSNP
rs940981543	398	dbSNP
rs1427622741	401	dbSNP
rs565807034	404	dbSNP
rs1385020800	409	dbSNP
rs1027399053	413	dbSNP
rs1165468387	415	dbSNP
rs952705283	423	dbSNP
rs1411572619	428	dbSNP
rs1176347498	434	dbSNP
rs1471179868	435	dbSNP
rs983197047	437	dbSNP
rs1364484535	442	dbSNP
rs1389945762	444	dbSNP
rs1459272978	447	dbSNP
rs1450457875	452	dbSNP
rs907758156	457	dbSNP
rs940608971	459	dbSNP
rs1319043293	465	dbSNP
rs1464136482	470	dbSNP
rs1265805211	471	dbSNP
rs991976392	475	dbSNP
rs1350691419	477	dbSNP
rs1273738349	479	dbSNP
rs1230973557	485	dbSNP
rs1373178066	494	dbSNP
rs1326311389	497	dbSNP
rs757097445	501	dbSNP
rs1197553325	502	dbSNP
rs947781793	505	dbSNP
rs1316437085	510	dbSNP
rs902051950	519	dbSNP
rs755294565	521	dbSNP
rs1044779785	526	dbSNP
rs1408797856	528	dbSNP
rs1172121657	532	dbSNP
rs1477312103	535	dbSNP
rs933401132	549	dbSNP
rs1397472311	555	dbSNP
rs1194837612	585	dbSNP
rs903605928	587	dbSNP
rs1246588834	588	dbSNP
rs540781604	589	dbSNP
rs936319266	592	dbSNP
rs1329448207	593	dbSNP
rs1050479490	594	dbSNP
rs892700357	611	dbSNP
rs1349930254	612	dbSNP
rs1008461515	614	dbSNP
rs381977	615	dbSNP
rs1362701127	616	dbSNP
rs532780927	617	dbSNP
rs1271779283	621	dbSNP
rs1210504606	624	dbSNP
rs1443869209	625	dbSNP
rs900050786	627	dbSNP
rs1266051601	628	dbSNP
rs891414940	629	dbSNP
rs58476421	631	dbSNP
rs945727408	633	dbSNP
rs1174751700	634	dbSNP
rs1430970045	638	dbSNP
rs1388702620	639	dbSNP
rs1198137428	640	dbSNP
rs1412061210	643	dbSNP
rs1473881678	644	dbSNP
rs1157562941	645	dbSNP
rs1344993996	650	dbSNP
rs1458695509	651	dbSNP
rs1295506264	652	dbSNP
rs565775176	654	dbSNP
rs1404552248	655	dbSNP
rs1289139496	657	dbSNP
rs1352378331	658	dbSNP
rs1486341356	662	dbSNP
rs530003920	668	dbSNP
rs1230202628	670	dbSNP
rs1032371153	687	dbSNP
rs893022482	688	dbSNP
rs1015628653	690	dbSNP
rs1283765801	695	dbSNP
rs1413182420	697	dbSNP
rs961944299	701	dbSNP
rs992114197	718	dbSNP
rs1010192929	726	dbSNP
rs1429658204	729	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.

- 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.

- 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.