Protocol for using TRIBE to study RNA-protein interactions and nuclear organization in mammalian cells.
Protocol for using TRIBE to study RNA-protein interactions and nuclear organization in mammalian cells.
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DOI:
10.1016/j.xpro.2021.100634
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发表时间:
2021-09-17
期刊:
影响因子:
--
通讯作者:
Rahman R
中科院分区:
文献类型:
--
作者:
Biswas J;Rosbash M;Singer RH;Rahman R
Targets of RNA-binding proteins discovered by editing (TRIBE) determines RNA-proteins interactions and nuclear organization with minimal false positives. We detail necessary steps for performing mammalian cell RBP-TRIBE to determine the targets of RNA-binding proteins and MS2-TRIBE to determine RNA-RNA interactions within the nucleus. Necessary steps for performing a TRIBE experiment are detailed, starting with plasmid/cell line generation, cellular transfection, and RNA sequencing library preparation and concluding with bioinformatics analysis of RNA editing sites and identification of target RNAs. For complete details on the use and execution of this protocol, please refer to. TRIBE and HyperTRIBE can be readily used in mammalian systems HyperTRIBE has minimal false positives and false negatives The analysis pipeline has been made more accessible using a virtual machine Targets of RNA-binding proteins discovered by editing (TRIBE) determines RNA-proteins interactions and nuclear organization with minimal false positives. We detail necessary steps for performing mammalian cell RBP-TRIBE to determine the targets of RNA-binding proteins and MS2-TRIBE to determine RNA-RNA interactions within the nucleus. Necessary steps for performing a TRIBE experiment are detailed, starting with plasmid/cell line generation, cellular transfection, and RNA sequencing library preparation and concluding with bioinformatics analysis of RNA editing sites and identification of target RNAs.
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DOI:
10.1093/bioinformatics/btq033
发表时间:
2010-03-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Quinlan AR;Hall IM
通讯作者:
Hall IM
影响因子:
48
作者:
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通讯作者:
Yeo GW
DOI:
10.1093/bioinformatics/btu638
发表时间:
2015-01-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Anders S;Pyl PT;Huber W
通讯作者:
Huber W
影响因子:
48
作者:
Langmead, Ben;Salzberg, Steven L.
通讯作者:
Salzberg, Steven L.
影响因子:
5.8
作者:
Biswas, Jeetayu;Rahman, Reazur;Singer, Robert H.
通讯作者:
Singer, Robert H.