Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch–probe arrays

We describe a DNA-array-based method to infer intramolecular connections in a population of RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, and then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between regions of the RNA sequence, from which we infer connections as well as their prevalences in the population, without reference to folding models. We validate this patch-probe method using the 1058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has been shown to have multiple long-range connections. Our results not only indicate long-range connections that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that multiple structures with different connectivity coexist in solution. Furthermore, we show that the prevalence of certain connections changes when pseudouridine, an important component of natural and synthetic RNAs, is substituted for uridine in STMV RNA, and that the connectivity of STMV minus strands is qualitatively distinct from that of plus strands. Finally, we use a simplified version of the method to validate a predicted 317-nucleotide connection within the 3569-nucleotide RNA genome of bacteriophage MS2.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-05-21
DOI
https://doi.org/10.1093/nar/gkaf469
Citations
1
Primary Topic
Plant Virus Research Studies
Type
article
Field-Weighted Citation Impact
1.75

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article

Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch–probe arrays

Michael P. Brenner, Ofer Kimchi, Rees F. Garmann, Daniel A. Villarreal et al.
1 citations
Nucleic Acids Research
Plant Virus Research Studies
1.75
article

Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch–probe arrays

Michael P. Brenner, Ofer Kimchi, Rees F. Garmann, Daniel A. Villarreal, Vinothan Manoharan, Herman K. Dhaliwal, Fernando F. Vasquez, T M Chiang
article en
1 citations

Abstract

We describe a DNA-array-based method to infer intramolecular connections in a population of RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, and then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between regions of the RNA sequence, from which we infer connections as well as their prevalences in the population, without reference to folding models. We validate this patch-probe method using the 1058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has been shown to have multiple long-range connections. Our results not only indicate long-range connections that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that multiple structures with different connectivity coexist in solution. Furthermore, we show that the prevalence of certain connections changes when pseudouridine, an important component of natural and synthetic RNAs, is substituted for uridine in STMV RNA, and that the connectivity of STMV minus strands is qualitatively distinct from that of plus strands. Finally, we use a simplified version of the method to validate a predicted 317-nucleotide connection within the 3569-nucleotide RNA genome of bacteriophage MS2.

Nucleic Acids ResearchVol. 53(11)
Harvard University (US), Princeton University (US), San Diego State University (US), Harvard University Press (US)
National Science Foundation, Simons Foundation, Ionis Pharmaceuticals, Materials Research Science and Engineering Center, Harvard University, Office of Naval Research, National Institute of General Medical Sciences
Good health and well-being
Openalex Percentile: Top 15%
Plant Virus Research Studies
1.75
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