The “Observer Effect” in Genome-wide Surveys of Protein-RNA Interactions

Riley, Kasandra; Steitz, Joan A.

doi:10.1016/j.molcel.2013.01.030

Cited by 69 publications

(60 citation statements)

References 30 publications

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“…S3D). This latter low number likely reflects differences between cell types, the high stringency used in the ΔSHAPE analysis (17), and the high background of CLIP experiments (38).…”

Section: Resultsmentioning

confidence: 99%

SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells

Smola

Christy

Inoue

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

206

306

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The 18-kb Xist long noncoding RNA (lncRNA) is essential for X-chromosome inactivation during female eutherian mammalian development. Global structural architecture, cell-induced conformational changes, and protein-RNA interactions within Xist are poorly understood. We used selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) to examine these features of Xist at single-nucleotide resolution both in living cells and ex vivo. The Xist RNA forms complex welldefined secondary structure domains and the cellular environment strongly modulates the RNA structure, via motifs spanning onehalf of all Xist nucleotides. The Xist RNA structure modulates protein interactions in cells via multiple mechanisms. For example, repeatcontaining elements adopt accessible and dynamic structures that function as landing pads for protein cofactors. Structured RNA motifs create interaction domains for specific proteins and also sequester other motifs, such that only a subset of potential binding sites forms stable interactions. This work creates a broad quantitative framework for understanding structure-function interrelationships for Xist and other lncRNAs in cells.ong noncoding RNAs (lncRNAs) play central roles in the regulation of gene expression through interactions with numerous protein partners (1) and are necessary for normal health and development (2, 3). The 18-kb Xist lncRNA is essential for X-chromosome inactivation during female eutherian mammalian development and is an archetype of gene-silencing lncRNAs. During the early stages of X inactivation, Xist accumulates in cis around the future inactive X chromosome and recruits protein complexes that apply repressive chromatin modifications, leading to stable gene silencing (3,4).Genetic deletion studies have demarcated several broad regions of function within Xist. Several tandem repeat regions (labeled A-F in the mouse) show moderate conservation (5-7), and at least two of these, repeat A and the rodent-specific repeat C, are implicated in silencing and localization to the inactive X. Deletion of the final 7.5-kb exon of Xist causes a defect in its localization (8), and the 1.5-kb region encompassing repeats F and B is required for accumulation of heterochromatic marks over the inactive X (4); however, beyond these initial characterizations, the mechanisms by which gene silencing, heterochromatinization, and localization of Xist on the X chromosome occur are not well understood. In particular, the role of RNA structure in orchestrating these distinct functions remains unclear.Several previous studies have suggested the importance of RNA structures in specific regions of Xist (9-12), but overall, the locations and structures of functional domains within Xist are poorly defined. Detailed structural maps of other functional RNAs, such as ribosomal RNAs (13) and the HIV RNA genome (14-16), have been fundamental to understanding the mechanisms by which individual domains within large RNAs execute discrete cellular functions. A detailed an...

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“…S3D). This latter low number likely reflects differences between cell types, the high stringency used in the ΔSHAPE analysis (17), and the high background of CLIP experiments (38).…”

Section: Resultsmentioning

confidence: 99%

SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells

Smola

Christy

Inoue

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

206

306

View full text Add to dashboard Cite

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“…This presents a problem because most applications of in vivo SHAPE require measurement of RNA structure in live, healthy cells. Several recent reports have demonstrated that after cell lysis, RNA molecules can reassociate with trans-acting RNAs and proteins (Mili and Steitz 2004;Riley et al 2012;Riley and Steitz 2013), which would likely alter the RNA structures of such RNAs. Such reasons underscore the concern that 1M7 may be preferentially modifying RNAs in nonnative contexts.…”

Section: Resultsmentioning

confidence: 99%

Comparison of SHAPE reagents for mapping RNA structures inside living cells

Lee

Flynn

Kadina

et al. 2016

RNA

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Recent advances in SHAPE technology have converted the classic primer extension method to next-generation sequencing platforms, allowing transcriptome-level analysis of RNA secondary structure. In particular, icSHAPE and SHAPE-MaP, using NAI-N 3 and 1M7 reagents, respectively, are methods that claim to measure in vivo structure with high-throughput sequencing. However, these compounds have not been compared on an unbiased, raw-signal level. Here, we directly compare several in vivo SHAPE acylation reagents using the simple primer extension assay. We conclude that while multiple SHAPE technologies are effective at measuring purified RNAs in vitro, acylimidazole reagents NAI and NAI-N 3 give markedly greater signals with lower background than 1M7 for in vivo measurement of the RNA structurome.

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“…Recently, however, new experimental approaches have been used to interrogate RNA-protein complexes and interaction networks. For example, high-throughput in vivo and in vitro experiments have been used to identify cellular RNA molecules that bind a protein of interest [11][12][13]. Global proteomic approaches have been applied to identify the entire mRNA-bound proteome [14].…”

Section: Introductionmentioning

confidence: 99%

Computational Tools for Investigating RNA-Protein Interaction Partners

Muppirala¹,

Lewis

Dobbs

2013

J Comput Sci Syst Biol

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RNA-protein interactions are important in a wide variety of cellular and developmental processes. Recently, high-throughput experiments have begun to provide valuable information about RNA partners and binding sites for many RNA-binding proteins (RBPs), but these experiments are expensive and time consuming. Thus, computational methods for predicting RNA-Protein interactions (RPIs) can be valuable tools for identifying potential interaction partners of a given protein or RNA, and for identifying likely interfacial residues in RNAprotein complexes. This review focuses on the "partner prediction" problem and summarizes available computational methods, web servers and databases that are devoted to it. New computational tools for addressing the related "interface prediction" problem are also discussed. Together, these computational methods for investigating RNA-protein interactions provide the basis for new strategies for integrating RNAprotein interactions into existing genetic and developmental regulatory networks, an important goal of future research.

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The “Observer Effect” in Genome-wide Surveys of Protein-RNA Interactions

Cited by 69 publications

References 30 publications

SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells

SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells

Comparison of SHAPE reagents for mapping RNA structures inside living cells

Computational Tools for Investigating RNA-Protein Interaction Partners

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