
pmid: 17406249
RNA targets of multitargeted RNA-binding proteins (RBPs) can be studied by various methods including mobility shift assays, iterative in vitro selection techniques and computational approaches. These techniques, however, cannot be used to identify the cellular context within which mRNAs associate, nor can they be used to elucidate the dynamic composition of RNAs in ribonucleoprotein (RNP) complexes in response to physiological stimuli. But by combining biochemical and genomics procedures to isolate and identify RNAs associated with RNA-binding proteins, information regarding RNA-protein and RNA-RNA interactions can be examined more directly within a cellular context. Several protocols--including the yeast three-hybrid system and immunoprecipitations that use physical or chemical cross-linking--have been developed to address this issue. Cross-linking procedures in general, however, are limited by inefficiency and sequence biases. The approach outlined here, termed RNP immunoprecipitation-microarray (RIP-Chip), allows the identification of discrete subsets of RNAs associated with multi-targeted RNA-binding proteins and provides information regarding changes in the intracellular composition of mRNPs in response to physical, chemical or developmental inducements of living systems. Thus, RIP-Chip can be used to identify subsets of RNAs that have related functions and are potentially co-regulated, as well as proteins that are associated with them in RNP complexes. Using RIP-Chip, the identification and/or quantification of RNAs in RNP complexes can be accomplished within a few hours or days depending on the RNA detection method used.
Cell Extracts, MicroRNAs, Ribonucleoproteins, Immunoprecipitation, RNA, Messenger, Oligonucleotide Array Sequence Analysis
Cell Extracts, MicroRNAs, Ribonucleoproteins, Immunoprecipitation, RNA, Messenger, Oligonucleotide Array Sequence Analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 536 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
