>EMC7|NM_020154|3'UTR
   1 TCAGGCCGTCCAGAGCTGGCATTTGCACAAACACGGCAACACTGGGTGGCATCCAAGTCTTGGAAAACCGTGTGAAGCAA
  81 CTACTATAAACTTGAGTCATCCCGACGTTGATCTCTTACAACTGTGTATGTTAACTTTTTAGCACATGTTTTGTACTTGG
 161 TACACGAGAAAACCCAGCTTTCATCTTTTGTCTGTATGAGGTCAATATTGATGTCACTGAATTAATTACAGTGTCCTATA
 241 GAAAATGCCATTAATAAATTATATGAACTACTATACATTATGTATATTAATTAAAACATCTTAATCCAGAAAAAAAAAAA
 321 AAAAAAAAAAAAA

ID	Duplex structure	Position	Score	MFE
1	miRNA 3' agGACCUAC-----GUUUAAAAu 5' ||||:|| |||:| || Target 5' caCTGGGTGGCATCCAAGTCTTg 3'	40 - 62	112.00	-11.30
2	miRNA 3' aggaccuacguuUAAAau 5' |||| Target 5' tccagagctggcATTTgc 3'	9 - 26	80.00	-6.16

Mutant ID	Mutant Position	Mutant Source
COSN30190655	8	COSMIC
COSN21907173	35	COSMIC
COSN30516944	35	COSMIC
COSN30109572	36	COSMIC
COSN31593865	37	COSMIC
COSN30487985	62	COSMIC
COSN31518030	69	COSMIC
COSN28193943	70	COSMIC
COSN30448844	103	COSMIC
COSN30132515	106	COSMIC
COSN30162965	115	COSMIC
COSN31487811	182	COSMIC
COSN31591538	200	COSMIC
COSN31486094	219	COSMIC
COSN5859969	300	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs1264212783	2	dbSNP
rs764800614	7	dbSNP
rs201960302	8	dbSNP
rs763640178	11	dbSNP
rs1224522380	14	dbSNP
rs189947179	15	dbSNP
rs1301610390	17	dbSNP
rs746866414	18	dbSNP
rs778532651	24	dbSNP
rs766720002	25	dbSNP
rs775268525	27	dbSNP
rs763244343	28	dbSNP
rs773419602	29	dbSNP
rs372289953	34	dbSNP
rs200013278	35	dbSNP
rs1207493525	36	dbSNP
rs768519905	38	dbSNP
rs761905243	39	dbSNP
rs776831428	40	dbSNP
rs1179604609	42	dbSNP
rs768897338	46	dbSNP
rs914527059	47	dbSNP
rs746939025	48	dbSNP
rs780152685	49	dbSNP
rs771832394	50	dbSNP
rs1226272656	54	dbSNP
rs1289084663	56	dbSNP
rs964461483	65	dbSNP
rs988679696	69	dbSNP
rs749087670	70	dbSNP
rs1382743970	83	dbSNP
rs1247314950	102	dbSNP
rs1351938527	103	dbSNP
rs1035489323	106	dbSNP
rs572998974	107	dbSNP
rs952966508	122	dbSNP
rs1025816227	129	dbSNP
rs554598808	138	dbSNP
rs143031568	143	dbSNP
rs1006675922	146	dbSNP
rs757144639	148	dbSNP
rs1185332909	153	dbSNP
rs1378329311	163	dbSNP
rs755834337	165	dbSNP
rs896023147	166	dbSNP
rs1166245678	177	dbSNP
rs1346625532	177	dbSNP
rs1036247723	180	dbSNP
rs1464199860	194	dbSNP
rs1301799560	195	dbSNP
rs575560716	196	dbSNP
rs745373032	200	dbSNP
rs879161155	203	dbSNP
rs1040954537	207	dbSNP
rs1007713048	208	dbSNP
rs548791107	208	dbSNP
rs1471580615	209	dbSNP
rs557390608	209	dbSNP
rs1239006553	210	dbSNP
rs1187921970	212	dbSNP
rs386782867	212	dbSNP
rs568905541	212	dbSNP
rs889557336	214	dbSNP
rs1208242449	215	dbSNP
rs185186630	224	dbSNP
rs753743349	231	dbSNP
rs1049487458	252	dbSNP
rs1437165629	268	dbSNP
rs1248315426	270	dbSNP
rs1203173807	271	dbSNP
rs1461824030	272	dbSNP
rs1205570301	277	dbSNP
rs1236303767	278	dbSNP
rs947073361	282	dbSNP
rs1177605219	284	dbSNP
rs1042765448	295	dbSNP
rs1275399951	295	dbSNP
rs11638774	309	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.

- 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.

- Genes & development, 2011

MicroRNAs are important regulators in many cellular processes, including stem cell self-renewal. Recent studies demonstrated their function as pluripotency factors with the capacity for somatic cell reprogramming. However, their role in human embryonic stem (ES) cells (hESCs) remains poorly understood, partially due to the lack of genome-wide strategies to identify their targets. Here, we performed comprehensive microRNA profiling in hESCs and in purified neural and mesenchymal derivatives. Using a combination of AGO cross-linking and microRNA perturbation experiments, together with computational prediction, we identified the targets of the miR-302/367 cluster, the most abundant microRNAs in hESCs. Functional studies identified novel roles of miR-302/367 in maintaining pluripotency and regulating hESC differentiation. We show that in addition to its role in TGF-beta signaling, miR-302/367 promotes bone morphogenetic protein (BMP) signaling by targeting BMP inhibitors TOB2, DAZAP2, and SLAIN1. This study broadens our understanding of microRNA function in hESCs and is a valuable resource for future studies in this area.

- Nature, 2013

Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.