RNA covariation at helix-level resolution for the identification of evolutionarily conserved RNA structure

Many biologically important RNAs fold into specific 3D structures conserved through evolution. Knowing when an RNA sequence includes a conserved RNA structure that could lead to new biology is not trivial and depends on clues left behind by conservation in the form of covariation and variation. For...

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Bibliographic Details
Published in:PLoS computational biology Vol. 19; no. 7; p. e1011262
Main Author: Rivas, Elena
Format: Journal Article
Language:English
Published: United States Public Library of Science 01.07.2023
Subjects:
Alignment
Base pairs
Benchmarks
Biology and life sciences
Computer and Information Sciences
Conserved sequence
Datasets
Evolution
Gene sequencing
Helices
Hypotheses
Methods
Non-coding RNA
Nucleotide sequence
Phylogeny
Physical Sciences
Physiological aspects
Power
Protein structure
Research and Analysis Methods
Ribonucleic acid
RNA
Secondary structure
Sensitivity
Statistical analysis
Statistical tests
Structure
United States
ISSN:1553-7358, 1553-734X, 1553-7358
Online Access:Get full text
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Summary:Many biologically important RNAs fold into specific 3D structures conserved through evolution. Knowing when an RNA sequence includes a conserved RNA structure that could lead to new biology is not trivial and depends on clues left behind by conservation in the form of covariation and variation. For that purpose, the R-scape statistical test was created to identify from alignments of RNA sequences, the base pairs that significantly covary above phylogenetic expectation. R-scape treats base pairs as independent units. However, RNA base pairs do not occur in isolation. The Watson-Crick (WC) base pairs stack together forming helices that constitute the scaffold that facilitates the formation of the non-WC base pairs, and ultimately the complete 3D structure. The helix-forming WC base pairs carry most of the covariation signal in an RNA structure. Here, I introduce a new measure of statistically significant covariation at helix-level by aggregation of the covariation significance and covariation power calculated at base-pair-level resolution. Performance benchmarks show that helix-level aggregated covariation increases sensitivity in the detection of evolutionarily conserved RNA structure without sacrificing specificity. This additional helix-level sensitivity reveals an artifact that results from using covariation to build an alignment for a hypothetical structure and then testing the alignment for whether its covariation significantly supports the structure. Helix-level reanalysis of the evolutionary evidence for a selection of long non-coding RNAs (lncRNAs) reinforces the evidence against these lncRNAs having a conserved secondary structure.
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The author has declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1011262