ID	Duplex structure	Position	Score	MFE
1	miRNA 3' acGGUCGGA--GCGGGUCg 5' ||| ||| :|||::| Target 5' ccCCA-CCTCATGCCTGGc 3'	118 - 135	104.00	-17.60
2	miRNA 3' acGGUCGGAGCGGGUcg 5' ||| || :|||:| Target 5' gtCCA-CC-TGCCTAtc 3'	17 - 31	97.00	-12.40
3	miRNA 3' acGGUCGGAGCGGGucg 5' |||| :|||| Target 5' ctCCAGGGCTGCCCctg 3'	61 - 77	95.00	-12.50

Mutant ID	Mutant Position	Mutant Source
1192804	150	ClinVar
COSN31593193	8	COSMIC
COSN5853221	26	COSMIC
COSN26966431	37	COSMIC
COSN30524141	39	COSMIC
COSN28809870	41	COSMIC
COSN26966429	60	COSMIC
COSN19699555	72	COSMIC
COSN30447161	141	COSMIC
COSN30161517	150	COSMIC
rs5128	41	GWAS

Mutant ID	Mutant Position	Mutant Source
rs1303323958	4	dbSNP
rs980623602	5	dbSNP
rs1333003201	6	dbSNP
rs548741530	9	dbSNP
rs1369165982	10	dbSNP
rs748747574	11	dbSNP
rs1446566018	18	dbSNP
rs756891658	19	dbSNP
rs758179886	19	dbSNP
rs201402310	22	dbSNP
rs927467188	23	dbSNP
rs930776786	25	dbSNP
rs1265313409	26	dbSNP
rs745586339	27	dbSNP
rs1186999885	30	dbSNP
rs1175319729	31	dbSNP
rs1315935892	32	dbSNP
rs772397071	35	dbSNP
rs201360025	36	dbSNP
rs5128	41	dbSNP
rs1235861534	46	dbSNP
rs769165532	47	dbSNP
rs776707156	49	dbSNP
rs761832101	50	dbSNP
rs765406427	51	dbSNP
rs773273781	52	dbSNP
rs763333861	53	dbSNP
rs907124040	59	dbSNP
rs1282860322	64	dbSNP
rs1377177486	69	dbSNP
rs900866832	70	dbSNP
rs4225	72	dbSNP
rs1224054370	90	dbSNP
rs1306748259	95	dbSNP
rs577085953	97	dbSNP
rs1268243427	99	dbSNP
rs539003433	100	dbSNP
rs1356038581	101	dbSNP
rs1314713789	108	dbSNP
rs1428347433	110	dbSNP
rs999953122	113	dbSNP
rs1267319833	117	dbSNP
rs1032811450	119	dbSNP
rs570839541	120	dbSNP
rs1354408383	124	dbSNP
rs1209316927	125	dbSNP
rs1402675635	126	dbSNP
rs1258996011	131	dbSNP
rs752681827	133	dbSNP
rs995893452	135	dbSNP
rs1475790219	137	dbSNP
rs1237908709	139	dbSNP
rs187628630	140	dbSNP
rs1243071828	145	dbSNP
rs1190149618	149	dbSNP
rs11540884	150	dbSNP
rs1024296488	152	dbSNP
rs1019701320	159	dbSNP
rs1232127855	161	dbSNP
rs971827928	163	dbSNP
rs980146319	174	dbSNP
rs1334964101	182	dbSNP
rs113565160	185	dbSNP
rs541512801	188	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.

- 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.