JoVE Logo
Faculty Resource Center

Sign In

Summary

Abstract

Introduction

Protocol

Representative Results

Discussion

Acknowledgements

Materials

References

Genetics

Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA

Published: July 9th, 2021

DOI:

10.3791/62475

1Faculté des Sciences Médicales et Paramédicales, Aix Marseille Univ, CNRS, INP
* These authors contributed equally

An easy-to-use RNA pull-down protocol is designed for the identification of RNAs engaged in direct RNA/RNA interaction with a long non-coding RNA. The protocol uses psoralen as a fixative to cross-link only RNA/RNA interactions and provides the whole direct RNA interactome of a long non-coding RNA when coupled with RNA sequencing.

The growing role attributed nowadays to long non-coding RNAs (lncRNA) in physiology and pathophysiology makes it crucial to characterize their interactome by identifying their molecular partners, DNA, proteins and/or RNAs. The latter can interact with lncRNA through networks involving proteins, but they can also be engaged in direct RNA/RNA interactions. We, therefore, developed an easy-to-use RNA pull-down procedure that allowed identification of RNAs engaged in direct RNA/RNA interaction with a lncRNA using psoralen, a molecule that cross-links only RNA/RNA interactions. Bioinformatics modeling of the lncRNA secondary structure allowed the selection of several specific antisense DNA oligonucleotide probes with a strong affinity for regions displaying a low probability of internal base pairing. Since the specific probes that were designed targeted accessible regions throughout the length of the lncRNA, the RNA-interaction zones could be delineated in the sequence of the lncRNA. When coupled with a high throughput RNA sequencing, this protocol can be used for the whole direct RNA interactome studies of a lncRNA of interest.

Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts longer than 200 nucleotides in length. Their number is ever increasing, more than 58,000 in humans. Furthermore, their crucial role in physiology and pathophysiology makes it essential to characterize their molecular partners that allow them to implement their regulatory functions. Actually, one approach to understand the functions of lncRNAs is the detection of the interacting molecular partners of each lncRNA.

The molecular targets of lncRNAs can be DNA, proteins, or RNAs, and various techniques have been developed to identify them. In this regard, the identification o....

Log in or to access full content. Learn more about your institution’s access to JoVE content here

1. Probe design

  1. Generate the secondary structure of the lncRNA using a specialized free web server software : RNAstructure software7 or Vienna RNA web suite8. Select regions that display a low probability of internal base pairing and design 25 bases long antisense oligonucleotide probes for different regions of this lncRNA.
  2. Check all the oligonucleotides designed with the free academic software, AmplifX (https://inp.univ-amu.fr/en/amplifx-manage-test-a.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

The elucidation of the lncRNA interactome i.e., the cellular components that interact with lncRNAs, proteins, RNA, and DNA, is of key importance for understanding the functions of lncRNAs. Various techniques have been developed to characterize the lncRNA interactome, including RIP, CHART, ChIRP, and RNA pull-down. While the latter has been shown to be powerful in identifying RNA targets of lncRNAs, these procedures do not indicate whether the RNA partners interact indirectly via a protein network or directly via direct R.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

Numerous lncRNAs carry out their function through complementary base pairing to mRNAs. It is, therefore, important to develop procedures that allow characterizing the direct RNA interactome of the lncRNAs. Therefore, a procedure was developed that combines the use of psoralen as cross-linking reagent with RNA pull-down technique.

In the RNA pull-down protocol described, the design and the selection of the antisense DNA biotinylated oligonucleotide probes are based on bioinformatics modeling of.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

This work was supported by Aix-Marseille University and Centre National Recherche Scientifique and funded by a grant from Sandoz Laboratories.

Funding for open access charge: Aix-Marseille University and Centre National Recherche Scientifique

....

Log in or to access full content. Learn more about your institution’s access to JoVE content here

Name Company Catalog Number Comments
4′-Aminomethyltrioxsalen hydrochloride Sigma A4330 Crosslinker reagent
Bioruptor Plus Diagenode B01020001 Sonicator
Biotynilated probes IDT Oligonucleotide probes
CFX96 Real Time System BioRad 4351107 qPCR apparatus
DNA Olignucleotides IDT Primers for qPCR
Dynabeads My One Thermo-Fisher 65001 Magnetic streptavidin beads
Formamide Thermo-Fisher 15515-026 Formamide
iTaq Universal SYBR Green Supermix BioRad 1725124 qPCR reagent
Proteinase K Sigma P2308 Proteinase K
RNA to DNA Thermo-Fisher 4387405 Reverse transcription kit
RNA XS purification kit Macherey-Nagel 740902 RNA purificationkit
RNAseOUT Thermo-Fisher 10777-019 RNAse inhibitor
Tube Rotator Stuart SB2 Eppendorf tube rotator
UV Stratalinker 1800 Stratagene #400072 UV crosslinker

  1. Chen, L. -. L., Zhao, J. C. functional analysis of long non-coding RNAs in development and disease. Systems Biology of RNA Binding Proteins. 825, 129-158 (2014).
  2. Simon, M. D. capture hybridization analysis of rna targets (CHART). Current Protocols in Molecular Biology. 101 (1), 2125 (2013).
  3. Chu, C., Quinn, J., Chang, H. Y. Chromatin Isolation by RNA Purification (ChIRP). Journal of Visualized Experiments. (61), e3912 (2012).
  4. Torres, M., et al. RNA pull-down procedure to identify RNA targets of a long non-coding RNA. Journal of Visualized Experiments. (134), e57379 (2018).
  5. Engreitz, J. M., et al. RNA-RNA interactions enable specific targeting of non-coding RNAs to nascent pre-mRNAs and chromatin sites. Cell. 159 (1), 188-199 (2014).
  6. Cimino, G. D., Gamper, H. B., Isaacs, S. T., Hearst, J. E. Psoralens as photoactive probes of nucleic acid structure and function: Organic chemistry, photochemistry, and biochemistry. Annual Review of Biochemistry. 54 (1), 1151-1193 (1985).
  7. Reuter, J. S., Mathews, D. H. RNAstructure: Software for RNA secondary structure prediction and analysis. BMC Bioinformatics. 11 (1), 129 (2010).
  8. Gruber, A. R., Lorenz, R., Bernhart, S. H., Neuböck, R., Hofacker, I. L. The Vienna RNA websuite. Nucleic Acids Research. 36, 70-74 (2008).
  9. Jacq, A., et al. Direct RNA-RNA interaction between Neat1 and RNA targets, as a mechanism for RNAs paraspeckle retention. RNA Biology. , 1-12 (2021).
  10. Dobin, A., et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 29 (1), 15-21 (2013).
  11. Kim, D., Langmead, B., Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nature Methods. 12 (4), 357-360 (2015).
  12. Liao, Y., Smyth, G. K., Shi, W. FeatureCounts: An efficient general-purpose program for assigning sequence reads to genomic features. Bioinformatics. 30 (7), 923-930 (2014).
  13. Anders, S., Pyl, P. T., Huber, W. HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics. 31 (2), 166-169 (2015).
  14. Fox, A. H., et al. Paraspeckles: a novel nuclear domain. Current Biology. 12 (1), 13-25 (2002).
  15. Torres, M., et al. Circadian RNA expression elicited by 3'-UTR IRAlu-paraspeckle associated elements. eLife. 5, 14837 (2016).
  16. Jacq, A., et al. Direct RNA-RNA interaction between Neat1 and RNA targets, as a mechanism for RNAs paraspeckle retention. BioRxiv. , 354712 (2020).
  17. Lu, Z., et al. Psoralen Analysis of RNA Interactions and Structures with High Throughput and Resolution. Methods in Molecular Biology. 1649, 59-84 (2018).
  18. Aw, J. G. A., Shen, Y., Nagarajan, N., Wan, Y. Mapping RNA-RNA interactions globally using biotinylated psoralen. Journal of Visualized Experiments. (123), e55255 (2017).

This article has been published

Video Coming Soon

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2024 MyJoVE Corporation. All rights reserved