Title |
RNase-mediated protein footprint sequencing reveals protein-binding sites throughout the human transcriptome
|
---|---|
Published in |
Genome Biology, January 2014
|
DOI | 10.1186/gb-2014-15-1-r3 |
Pubmed ID | |
Authors |
Ian M Silverman, Fan Li, Anissa Alexander, Loyal Goff, Cole Trapnell, John L Rinn, Brian D Gregory |
Abstract |
Although numerous approaches have been developed to map RNA-binding sites of individual RNA-binding proteins (RBPs), few methods exist that allow assessment of global RBP-RNA interactions. Here, we describe PIP-seq, a universal, high-throughput, ribonuclease-mediated protein footprint sequencing approach that reveals RNA-protein interaction sites throughout a transcriptome of interest. We apply PIP-seq to the HeLa transcriptome and compare binding sites found using different cross-linkers and ribonucleases. From this analysis, we identify numerous putative RBP-binding motifs, reveal novel insights into co-binding by RBPs, and uncover a significant enrichment for disease-associated polymorphisms within RBP interaction sites. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 67% |
United Kingdom | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 2% |
Japan | 2 | <1% |
France | 2 | <1% |
Sweden | 2 | <1% |
South Africa | 1 | <1% |
Germany | 1 | <1% |
United Kingdom | 1 | <1% |
Switzerland | 1 | <1% |
India | 1 | <1% |
Other | 1 | <1% |
Unknown | 215 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 71 | 31% |
Researcher | 68 | 29% |
Student > Master | 15 | 6% |
Professor > Associate Professor | 10 | 4% |
Student > Bachelor | 9 | 4% |
Other | 31 | 13% |
Unknown | 28 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 103 | 44% |
Biochemistry, Genetics and Molecular Biology | 62 | 27% |
Medicine and Dentistry | 14 | 6% |
Computer Science | 8 | 3% |
Neuroscience | 6 | 3% |
Other | 10 | 4% |
Unknown | 29 | 13% |