>PCNA|NM_002592|3'UTR
   1 GCATTCTTAAAATTCAAGAAAATAAAACTAAGCTCTTTGAGAACTGCTTCTAAGATGCCAGCATATACTGAAGTCTTTTC
  81 TGTCACCAAATTTGTACCTCTAAGTACATATGTAGATATTGTTTTCTGTAAATAACCTATTTTTTTCTCTATTCTCTGCA
 161 ATTTGTTTAAAGAATAAAGTCCAAAGTCAGATCTGGTCTAGTTAACCTAGAAGTATTTTTGTCTCTTAGAAATACTTGTG
 241 ATTTTTATAATACAAAAGGGTCTTGACTCTAAATGCAGTTTTAAGAATTGTTTTTGAATTTAAATAAAGTTACTTGAATT
 321 TCAAACATCA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' uggUCAACGG----AGAUG---UCAGAAAu 5' || |||| | ||| ||||||| Target 5' ctaAGATGCCAGCATATACTGAAGTCTTTt 3'	50 - 79	158.00	-14.50
2	miRNA 3' uggucAACGGAGAU----GUCAGAAau 5' ||| ||||| ||||:|| Target 5' gggtcTTGACTCTAAATGCAGTTTTaa 3'	258 - 284	132.00	-9.70
3	miRNA 3' ugGUCAACGGAGAU-GUCAGAAAu 5' :|||| | ||| ||| ||| Target 5' tcTAGTTAAC-CTAGAAGTATTTt 3'	197 - 219	124.00	-9.60

Mutant ID	Mutant Position	Mutant Source
COSN30112718	154	COSMIC
COSN30164158	169	COSMIC
COSN31558041	172	COSMIC
COSN10017666	190	COSMIC
COSN27190338	222	COSMIC
COSN31607171	229	COSMIC
COSN31606686	285	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs751963812	2	dbSNP
rs764607894	5	dbSNP
rs763207665	6	dbSNP
rs1375801067	7	dbSNP
rs771120963	13	dbSNP
rs1415784168	14	dbSNP
rs775582825	15	dbSNP
rs541397756	17	dbSNP
rs759559882	21	dbSNP
rs1029779948	24	dbSNP
rs1354889205	28	dbSNP
rs1462455834	30	dbSNP
rs997757307	35	dbSNP
rs1226077539	38	dbSNP
rs776825639	40	dbSNP
rs1157419404	51	dbSNP
rs764617171	69	dbSNP
rs577316337	75	dbSNP
rs564379564	78	dbSNP
rs1363087648	80	dbSNP
rs1188421403	82	dbSNP
rs902102178	83	dbSNP
rs892045969	84	dbSNP
rs1032656898	91	dbSNP
rs545798337	94	dbSNP
rs1408886276	98	dbSNP
rs1039181449	100	dbSNP
rs575383335	101	dbSNP
rs556902668	102	dbSNP
rs1157007949	111	dbSNP
rs535170945	116	dbSNP
rs200747799	119	dbSNP
rs903906399	123	dbSNP
rs1044149724	126	dbSNP
rs1336591370	129	dbSNP
rs949820791	137	dbSNP
rs1448004525	139	dbSNP
rs8632	149	dbSNP
rs534273013	151	dbSNP
rs3626	158	dbSNP
rs1489693827	161	dbSNP
rs1352573414	190	dbSNP
rs1211296490	191	dbSNP
rs1280537027	193	dbSNP
rs1440619350	197	dbSNP
rs552802112	204	dbSNP
rs909807108	206	dbSNP
rs1056398901	207	dbSNP
rs1441556742	209	dbSNP
rs984033253	214	dbSNP
rs14453	217	dbSNP
rs1454900061	221	dbSNP
rs1174653231	223	dbSNP
rs1209847033	223	dbSNP
rs939233585	235	dbSNP
rs1330075526	254	dbSNP
rs926562222	267	dbSNP
rs1403115501	270	dbSNP
rs1448303090	276	dbSNP
rs930629892	279	dbSNP
rs1259475241	285	dbSNP
rs1375670934	286	dbSNP
rs1400571813	286	dbSNP
rs980546234	287	dbSNP
rs941191407	288	dbSNP
rs191891769	290	dbSNP
rs966534931	292	dbSNP
rs1019074254	293	dbSNP
rs909731914	297	dbSNP
rs537378145	309	dbSNP
rs982547821	312	dbSNP
rs951238633	313	dbSNP
rs956288710	314	dbSNP
rs577155052	316	dbSNP
rs976416280	319	dbSNP
rs1000473176	324	dbSNP
rs1426374679	329	dbSNP

- 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.