Publications
2021
Alghoul F, Eriani G, Martin F
RNA Secondary Structure Study by Chemical Probing Methods Using DMS and CMCT Chapitre d'ouvrage
Dans: Rederstorff, M (Ed.): Methods Mol Biol, vol. 2300, p. 241-250, Springer Protocols, Humana Press, New York, NY, 2021, ISBN: 978-1-0716-1385-6/ISSN, (1940-6029 (Electronic) 1064-3745 (Linking) Journal Article).
Résumé | Liens | BibTeX | Étiquettes: Capillary electrophoresis, chemical probing, CMCT, DMS, ERIANI, Primer extension, QuSHAPE, RNA secondary structure, Unité ARN
@inbook{Alghoul2021,
title = {RNA Secondary Structure Study by Chemical Probing Methods Using DMS and CMCT},
author = {F Alghoul and G Eriani and F Martin},
editor = {M Rederstorff},
url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=33792883},
doi = {10.1007/978-1-0716-1386-3_18},
isbn = {978-1-0716-1385-6/ISSN},
year = {2021},
date = {2021-01-01},
booktitle = {Methods Mol Biol},
volume = {2300},
pages = {241-250},
publisher = {Springer Protocols, Humana Press},
address = {New York, NY},
series = {Methods in Molecular Biology},
abstract = {RNA folds into secondary structures that can serve in understanding various RNA functions (Weeks KM. Curr Opin Struct Biol 20(3):295-304, 2010). Chemical probing is a method that enables the characterization of RNA secondary structures using chemical reagents that specifically modify RNA nucleotides that are located in single-stranded areas. In our protocol, we used Dimethyl Sulfate (DMS) and Cyclohexyl-3-(2-Morpholinoethyl) Carbodiimide metho-p-Toluene sulfonate (CMCT) that are both base-specific modifying reagents (Behm-Ansmant I, et al. J Nucleic Acids 2011:408053, 2011). These modifications are mapped by primer extension arrests using 5' fluorescently labeled primers. In this protocol, we show a comprehensive method to identify RNA secondary structures in vitro using fluorescently labeled oligos. To demonstrate the efficiency of the method, we give an example of a structure we have designed which corresponds to a part of the 5'-UTR regulatory element called Translation Inhibitory Element (TIE) from Hox a3 mRNA (Xue S, et al. Nature 517(7532):33-38, 2015).},
note = {1940-6029 (Electronic)
1064-3745 (Linking)
Journal Article},
keywords = {Capillary electrophoresis, chemical probing, CMCT, DMS, ERIANI, Primer extension, QuSHAPE, RNA secondary structure, Unité ARN},
pubstate = {published},
tppubtype = {inbook}
}
2020
Li B, Cao Y, Westhof E, Miao Z
Advances in RNA 3D Structure Modeling Using Experimental Data Article de journal
Dans: Front Genet ., vol. 11, no. 574485, 2020.
Résumé | Liens | BibTeX | Étiquettes: 3D shape, chemical probing, RNA structure, RNA-puzzles, structure prediction, Unité ARN, WESTHOF
@article{B2020b,
title = {Advances in RNA 3D Structure Modeling Using Experimental Data},
author = {B Li and Y Cao and E Westhof and Z Miao},
doi = {https://doi.org/10.3389/fgene.2020.574485},
year = {2020},
date = {2020-11-23},
journal = {Front Genet .},
volume = {11},
number = {574485},
abstract = {RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.},
keywords = {3D shape, chemical probing, RNA structure, RNA-puzzles, structure prediction, Unité ARN, WESTHOF},
pubstate = {published},
tppubtype = {article}
}