| Title |
miR-CLIP capture of a miRNA targetome uncovers a lincRNA H19–miR-106a interaction
|
|---|---|
| Published in |
Nature Chemical Biology, December 2014
|
| DOI | 10.1038/nchembio.1713 |
| Pubmed ID | |
| Authors | |
| Abstract |
Identifying the interaction partners of noncoding RNAs is essential for elucidating their functions. We have developed an approach, termed microRNA crosslinking and immunoprecipitation (miR-CLIP), using pre-miRNAs modified with psoralen and biotin to capture their targets in cells. Photo-crosslinking and Argonaute 2 immunopurification followed by streptavidin affinity purification of probe-linked RNAs provided selectivity in the capture of targets, which were identified by deep sequencing. miR-CLIP with pre-miR-106a, a miR-17-5p family member, identified hundreds of putative targets in HeLa cells, many carrying conserved sequences complementary to the miRNA seed but also many that were not predicted computationally. miR-106a overexpression experiments confirmed that miR-CLIP captured functional targets, including H19, a long noncoding RNA that is expressed during skeletal muscle cell differentiation. We showed that miR-17-5p family members bind H19 in HeLa cells and myoblasts. During myoblast differentiation, levels of H19, miR-17-5p family members and mRNA targets changed in a manner suggesting that H19 acts as a 'sponge' for these miRNAs. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| France | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Norway | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| United Kingdom | 1 | <1% |
| Finland | 1 | <1% |
| Denmark | 1 | <1% |
| Germany | 1 | <1% |
| China | 1 | <1% |
| Chile | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 238 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 59 | 24% |
| Researcher | 56 | 22% |
| Student > Master | 35 | 14% |
| Student > Bachelor | 15 | 6% |
| Professor > Associate Professor | 15 | 6% |
| Other | 40 | 16% |
| Unknown | 29 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 82 | 33% |
| Agricultural and Biological Sciences | 78 | 31% |
| Chemistry | 20 | 8% |
| Medicine and Dentistry | 14 | 6% |
| Neuroscience | 8 | 3% |
| Other | 15 | 6% |
| Unknown | 32 | 13% |