English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Serial interactome capture of the human cell nucleus

MPS-Authors
/persons/resource/persons144853

Conrad,  Thomas
Long non-coding RNA (Ulf Andersson Ørom), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50427

Meierhofer,  David
Mass Spectrometry (Head: David Meierhofer), Scientific Service (Head: Christoph Krukenkamp), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons73949

Ørom,  Ulf Andersson
Long non-coding RNA (Ulf Andersson Ørom), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

Conrad.pdf
(Publisher version), 779KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Conrad, T., Albrecht, A.-S., Rodrigues de Melo Costa, V., Sauer, S., Meierhofer, D., & Ørom, U. A. (2016). Serial interactome capture of the human cell nucleus. Nature Communications, 7: 7:11212. doi:10.1038/ncomms11212.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-1373-4
Abstract
Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present ‘serial RNA interactome capture’ (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)–RNA–protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA–RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs.