>TULP1|NM_003322|3'UTR
   1 CCCCAGCAGCCCCTCAGCGCCCCCAGAGCCCGTCAGCGTGGGGGAAAGGATTCAGTGGAGGCTGGCAGGGTCCCTCCAGC
  81 AAAGCTCCCGCGGAAAACTGCTCCTGTGTCGGGGCTGACCTCTCACTGCCTCTCGGTGACCTCCGTCCTCTCCCCAGCCT
 161 GGCACAGGCCGAGGCAGGAGGAGCCCGGACGGCGGGTAGGACGGAGATGAAGAACATCTGGAGTTGGAGCCGCACATCTG
 241 GTCTCGGAGCTCGCCTGCGCCGCTGTGCCCCCCTCCTCCCCGCGCCCCAGTCACTTCCTGTCCGGGAGCAGTAGTCATTG
 321 TTGTTTTAACCTCCCCTCTCCCCGGGACCGCGCTAGGGCTCCGAGGAGCTGGGGCGGGCTAGGAGGAGGGGGTAGGTGAT
 401 GGGGGACGAGGGCCAGGCACCCACATCCCCAATAAAGCCGCGTCCTTGGCCAAAAAAAAAAAAAAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' cuACGGGACCGGA-CAGGGGCGu 5' ||||| ||| ||||||| Target 5' tgTGCCC--CCCTCCTCCCCGCg 3'	264 - 284	156.00	-26.10
2	miRNA 3' cuacgGGACCGGACAGGGGCgu 5' ||| ||| |||||| Target 5' tttaaCCTCCCCTCTCCCCGgg 3'	325 - 346	141.00	-20.30
3	miRNA 3' cuACGGGA--CCGGACAGGGG-CGu 5' || ||| | ||| ||||| || Target 5' ggTGACCTCCGTCCTCTCCCCAGCc 3'	135 - 159	134.00	-19.50

Mutant ID	Mutant Position	Mutant Source
356465	31	ClinVar
356464	268	ClinVar
905194	272	ClinVar
356463	274	ClinVar
356462	278	ClinVar
356461	305	ClinVar
356460	318	ClinVar
COSN30495167	2	COSMIC
COSN14223709	19	COSMIC
COSN28873961	21	COSMIC
COSN30163856	28	COSMIC
COSN31538395	37	COSMIC
COSN31612369	48	COSMIC
COSN31602900	55	COSMIC
COSN30125797	69	COSMIC
COSN30154031	76	COSMIC
COSN30117404	91	COSMIC
COSN31527501	110	COSMIC
COSN14708044	268	COSMIC
COSN23653228	342	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1178636343	1	dbSNP
rs1456811027	6	dbSNP
rs1275452394	7	dbSNP
rs746702315	8	dbSNP
rs1320773925	10	dbSNP
rs1287247487	11	dbSNP
rs777972090	13	dbSNP
rs1377051389	16	dbSNP
rs758850066	17	dbSNP
rs986795982	18	dbSNP
rs1444548948	19	dbSNP
rs377662962	20	dbSNP
rs779352838	20	dbSNP
rs753245203	23	dbSNP
rs765914874	25	dbSNP
rs1365564991	26	dbSNP
rs1425846493	27	dbSNP
rs755548574	30	dbSNP
rs886061336	31	dbSNP
rs1347878685	32	dbSNP
rs199634715	33	dbSNP
rs1024629063	36	dbSNP
rs760768786	37	dbSNP
rs762892498	38	dbSNP
rs763782284	40	dbSNP
rs762801376	41	dbSNP
rs775265314	42	dbSNP
rs1270374161	43	dbSNP
rs769659127	44	dbSNP
rs1488388186	46	dbSNP
rs1245315230	48	dbSNP
rs745824313	49	dbSNP
rs1363460861	50	dbSNP
rs1356853983	55	dbSNP
rs1313718877	59	dbSNP
rs1034024489	69	dbSNP
rs773083501	72	dbSNP
rs1243405050	78	dbSNP
rs1283649137	84	dbSNP
rs559973202	85	dbSNP
rs994539776	87	dbSNP
rs765015183	90	dbSNP
rs955387398	99	dbSNP
rs1355415378	100	dbSNP
rs1425571371	103	dbSNP
rs1486962809	111	dbSNP
rs551687970	113	dbSNP
rs1309287323	125	dbSNP
rs1384658104	134	dbSNP
rs918821632	135	dbSNP
rs1445432025	144	dbSNP
rs1165972072	155	dbSNP
rs898913478	162	dbSNP
rs540373546	165	dbSNP
rs1400425569	167	dbSNP
rs1335645513	183	dbSNP
rs1346657649	185	dbSNP
rs1449973282	187	dbSNP
rs1335557480	195	dbSNP
rs1382820345	200	dbSNP
rs528194992	213	dbSNP
rs1248118796	214	dbSNP
rs1388865323	217	dbSNP
rs761640813	218	dbSNP
rs548534254	224	dbSNP
rs1224183242	233	dbSNP
rs1162884572	241	dbSNP
rs1286076981	244	dbSNP
rs545744658	245	dbSNP
rs1051948	250	dbSNP
rs1318999978	258	dbSNP
rs1201989088	259	dbSNP
rs1242636920	261	dbSNP
rs890645334	264	dbSNP
rs114707578	268	dbSNP
rs386700132	270	dbSNP
rs1231614922	272	dbSNP
rs112061946	274	dbSNP
rs886061335	278	dbSNP
rs1017067024	280	dbSNP
rs1410588690	287	dbSNP
rs1002110957	288	dbSNP
rs969808452	289	dbSNP
rs1051950	294	dbSNP
rs1439193388	303	dbSNP
rs1406176375	304	dbSNP
rs149035389	305	dbSNP
rs1024486413	317	dbSNP
rs1051952	318	dbSNP
rs764755541	320	dbSNP
rs891492621	324	dbSNP
rs1489039476	330	dbSNP
rs1053023661	333	dbSNP
rs1286326579	334	dbSNP
rs1262675345	335	dbSNP
rs1000149543	336	dbSNP
rs574332142	338	dbSNP
rs989430143	343	dbSNP
rs936713780	348	dbSNP
rs1270969653	349	dbSNP
rs924002134	351	dbSNP
rs1278281377	354	dbSNP
rs1183102904	363	dbSNP
rs978229191	373	dbSNP
rs967586224	377	dbSNP
rs559343621	382	dbSNP
rs552746401	383	dbSNP
rs534796159	384	dbSNP
rs1198251756	385	dbSNP
rs1429624285	389	dbSNP
rs1332183055	390	dbSNP
rs1038828059	391	dbSNP
rs990698551	393	dbSNP
rs1395119486	396	dbSNP
rs577224839	402	dbSNP
rs1330767108	404	dbSNP
rs1302861204	405	dbSNP
rs1283672851	407	dbSNP
rs1024145659	411	dbSNP
rs1346463745	412	dbSNP
rs558694509	415	dbSNP
rs1268513945	417	dbSNP
rs1362645348	424	dbSNP
rs958604516	432	dbSNP
rs554643340	445	dbSNP
rs994488766	447	dbSNP
rs537421924	448	dbSNP
rs1400183441	454	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.