ID	Duplex structure	Position	Score	MFE
1	miRNA 3' uugAUACGUUGGAU-----GAUGGAGa 5' ||| : :|||: ||||||| Target 5' tagTATATTGCCTGTATTTCTACCTCt 3'	460 - 486	151.00	-14.50
2	miRNA 3' uugaUAC---GUUGG-AU--GAUGG-AGa 5' ||| :||:| || ||||| || Target 5' tgtaATGTCTTAATCATAGTCTACCATCa 3'	163 - 191	120.00	-7.50
3	miRNA 3' uugAUACGUUGGAU---GAUGGAga 5' ||| || :|| ||||:| Target 5' tagTATTGAAATTAAGTCTACTTaa 3'	670 - 694	119.00	-6.09

Mutant ID	Mutant Position	Mutant Source
COSN30678412	25	COSMIC
COSN22788322	28	COSMIC
COSN31560484	63	COSMIC
COSN30189637	70	COSMIC
COSN19701840	74	COSMIC
COSN8730816	80	COSMIC
COSN30613888	87	COSMIC
COSN13299256	88	COSMIC
COSN24399160	120	COSMIC
COSN31603967	123	COSMIC
COSN30532318	129	COSMIC
COSN30518038	142	COSMIC
COSN31488628	276	COSMIC
COSN16603573	282	COSMIC
COSN16602273	323	COSMIC
COSN30175300	339	COSMIC
COSN23141153	368	COSMIC
COSN26488310	452	COSMIC
COSN1126152	517	COSMIC
COSN31482470	556	COSMIC
COSN30161810	593	COSMIC
COSN22118609	601	COSMIC
COSN22249072	619	COSMIC
COSN31607277	645	COSMIC
COSN26602444	741	COSMIC
COSN26464681	748	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1383411799	1	dbSNP
rs1332956810	4	dbSNP
rs1412228751	5	dbSNP
rs1308369795	6	dbSNP
rs11542383	11	dbSNP
rs1398195997	14	dbSNP
rs765586511	22	dbSNP
rs1428693377	27	dbSNP
rs1295129955	33	dbSNP
rs762114043	35	dbSNP
rs777055660	37	dbSNP
rs1022240963	38	dbSNP
rs769165275	41	dbSNP
rs73417794	42	dbSNP
rs1159871397	44	dbSNP
rs976968537	47	dbSNP
rs1459879058	53	dbSNP
rs1259897890	64	dbSNP
rs1199108816	67	dbSNP
rs965926267	68	dbSNP
rs1306673622	69	dbSNP
rs900380817	75	dbSNP
rs911344393	79	dbSNP
rs1295154546	80	dbSNP
rs878950347	87	dbSNP
rs187488944	88	dbSNP
rs1326446952	94	dbSNP
rs1227316948	95	dbSNP
rs1273351320	102	dbSNP
rs1336510504	107	dbSNP
rs1219047241	119	dbSNP
rs1021649714	123	dbSNP
rs944798371	124	dbSNP
rs1249595596	128	dbSNP
rs1471647049	129	dbSNP
rs756469432	145	dbSNP
rs1418789089	148	dbSNP
rs956633257	150	dbSNP
rs1349641318	159	dbSNP
rs1443456669	176	dbSNP
rs746176685	177	dbSNP
rs929349380	186	dbSNP
rs1408624950	188	dbSNP
rs571711753	192	dbSNP
rs1404626143	195	dbSNP
rs1336440981	197	dbSNP
rs1317890781	206	dbSNP
rs1226226526	215	dbSNP
rs973685695	217	dbSNP
rs948948209	219	dbSNP
rs1462863807	220	dbSNP
rs1272300284	227	dbSNP
rs1482702654	238	dbSNP
rs757496109	240	dbSNP
rs1354257404	241	dbSNP
rs557907156	245	dbSNP
rs184263734	247	dbSNP
rs1044867493	249	dbSNP
rs1180323397	250	dbSNP
rs1413432288	253	dbSNP
rs757374245	255	dbSNP
rs1170891447	260	dbSNP
rs1369193122	264	dbSNP
rs1182507875	265	dbSNP
rs1429706850	267	dbSNP
rs565954508	273	dbSNP
rs916085568	278	dbSNP
rs929623917	281	dbSNP
rs1239985921	297	dbSNP
rs775672840	299	dbSNP
rs764256258	307	dbSNP
rs1362227836	308	dbSNP
rs918885089	311	dbSNP
rs960461725	316	dbSNP
rs1041686464	328	dbSNP
rs944268147	336	dbSNP
rs1211483581	338	dbSNP
rs1282459395	345	dbSNP
rs911381362	349	dbSNP
rs1208118594	350	dbSNP
rs985618205	352	dbSNP
rs1475876547	362	dbSNP
rs1179154181	368	dbSNP
rs1480205352	382	dbSNP
rs1249336902	384	dbSNP
rs1034798947	388	dbSNP
rs978232618	392	dbSNP
rs1292778994	395	dbSNP
rs1245393415	401	dbSNP
rs1380654475	407	dbSNP
rs552501756	408	dbSNP
rs1332942058	417	dbSNP
rs1312121464	419	dbSNP
rs1318193974	420	dbSNP
rs532653246	420	dbSNP
rs1392436161	423	dbSNP
rs1364180035	428	dbSNP
rs1276476721	430	dbSNP
rs966436357	438	dbSNP
rs1217497154	439	dbSNP
rs1278042282	442	dbSNP
rs1447695405	449	dbSNP
rs538216675	455	dbSNP
rs563816054	456	dbSNP
rs1464721959	460	dbSNP
rs1488999934	471	dbSNP
rs1194655789	476	dbSNP
rs1379816372	477	dbSNP
rs1296749634	488	dbSNP
rs1477345898	499	dbSNP
rs1172549614	514	dbSNP
rs964562902	518	dbSNP
rs550286925	519	dbSNP
rs1017406064	521	dbSNP
rs569472513	522	dbSNP
rs1008662857	526	dbSNP
rs11929	530	dbSNP
rs1387461022	540	dbSNP
rs1441292474	543	dbSNP
rs1325306607	550	dbSNP
rs191776533	565	dbSNP
rs1435631963	581	dbSNP
rs1280115209	584	dbSNP
rs1047838898	585	dbSNP
rs993982037	589	dbSNP
rs1329917950	596	dbSNP
rs1012020387	598	dbSNP
rs899204205	599	dbSNP
rs1328767016	610	dbSNP
rs1381583963	617	dbSNP
rs1269878139	618	dbSNP
rs529518715	621	dbSNP
rs1450296148	623	dbSNP
rs561841151	630	dbSNP
rs1198763921	632	dbSNP
rs1037667155	633	dbSNP
rs993827205	637	dbSNP
rs1418373021	640	dbSNP
rs1473248804	645	dbSNP
rs896820228	659	dbSNP
rs567021870	661	dbSNP
rs1461668253	668	dbSNP
rs944305339	670	dbSNP
rs1388281909	672	dbSNP
rs1248313876	674	dbSNP
rs541775170	682	dbSNP
rs573054698	683	dbSNP
rs890031439	683	dbSNP
rs1352254650	684	dbSNP
rs1411672332	684	dbSNP
rs1049946449	685	dbSNP
rs1488669200	693	dbSNP
rs1349997089	695	dbSNP
rs1245771081	700	dbSNP
rs547210150	706	dbSNP
rs1354687918	707	dbSNP
rs938892106	709	dbSNP
rs559089883	715	dbSNP
rs111321631	718	dbSNP
rs1357405508	725	dbSNP
rs988904602	727	dbSNP
rs150014705	728	dbSNP
rs1179339573	730	dbSNP
rs1250382921	732	dbSNP
rs1804746	732	dbSNP
rs1288164121	734	dbSNP
rs1240400991	735	dbSNP
rs924765778	743	dbSNP
rs1366420964	751	dbSNP
rs1457156951	752	dbSNP
rs1168291957	759	dbSNP
rs977905290	762	dbSNP
rs1372274551	763	dbSNP

- Journal of translational medicine, 2009

BACKGROUND: MicroRNAs are approximately 22nt-long small non-coding RNAs that negatively regulate protein expression through mRNA degradation or translational repression in eukaryotic cells. Based upon their importance in regulating development and terminal differentiation in model systems, erythrocyte microRNA profiles were examined at birth and in adults to determine if changes in their abundance coincide with the developmental phenomenon of hemoglobin switching. METHODS: Expression profiling of microRNA was performed using total RNA from four adult peripheral blood samples compared to four cord blood samples after depletion of plasma, platelets, and nucleated cells. Labeled RNAs were hybridized to custom spotted arrays containing 474 human microRNA species (miRBase release 9.1). Total RNA from Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines provided a hybridization reference for all samples to generate microRNA abundance profile for each sample. RESULTS: Among 206 detected miRNAs, 79% of the microRNAs were present at equivalent levels in both cord and adult cells. By comparison, 37 microRNAs were up-regulated and 4 microRNAs were down-regulated in adult erythroid cells (fold change > 2; p < 0.01). Among the up-regulated subset, the let-7 miRNA family consistently demonstrated increased abundance in the adult samples by array-based analyses that were confirmed by quantitative PCR (4.5 to 18.4 fold increases in 6 of 8 let-7 miRNA). Profiling studies of messenger RNA (mRNA) in these cells additionally demonstrated down-regulation of ten let-7 target genes in the adult cells. CONCLUSION: These data suggest that a consistent pattern of up-regulation among let-7 miRNA in circulating erythroid cells occurs in association with hemoglobin switching during the fetal-to-adult developmental transition in humans.

- 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.

- 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.

- 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.