Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA): messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three RNA types consist of a...
RNA Stability01:53

RNA Stability

Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
RNA Stability01:53

RNA Stability

Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
RNA Structure01:19

RNA Structure

The basic structure of RNA consists of a string of ribonucleotides attached by phosphodiester bonds. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
There are three main types of ribonucleic acid (RNA) involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). All three...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Suitability of machine learning models for prediction of clinically defined Stage III/IV periodontitis from questionnaires and demographic data in Danish cohorts.

Journal of clinical periodontology·2023
Same author

Incidental Coronary Artery Calcification Seen on Low-Dose Computed Tomography Is a Risk Factor for Obstructive Coronary Artery Disease in Patients Undergoing Liver Transplant.

Transplantation proceedings·2018
Same author

Antibacterial isoeugenol coating on stainless steel and polyethylene surfaces prevents biofilm growth.

Journal of applied microbiology·2017
Same author

Circular RNAs in cancer: opportunities and challenges in the field.

Oncogene·2017
Same author

POSITIVE CORRELATIONS BETWEEN SELFING RATE AND POLLEN-OVULE RATIO WITHIN PLANT POPULATIONS.

Evolution; international journal of organic evolution·2017
Same author

Urinary tract infections associated with ureteral stents: A Review.

Archivos espanoles de urologia·2016

Related Experiment Video

Updated: Jul 12, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Evolutionary rate variation and RNA secondary structure prediction.

B Knudsen1, E S Andersen, C Damgaard

  • 1Bioinformatics Research Center, Høegh Guldbergsgade 10, University of Aarhus, DK-8000 Arhus C, Denmark.

Computational Biology and Chemistry
|July 21, 2004
PubMed
Summary

Predicting RNA secondary structure is improved by using evolutionary rates from related RNA families. This method accurately forecasts HIV-1 RNA structure, even with accelerated evolutionary rates.

More Related Videos

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
09:12

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

Related Experiment Videos

Last Updated: Jul 12, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
10:34

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae
09:12

Comparative RNA Structure Analysis of Nascent and Mature Transcripts in Saccharomyces cerevisiae

Published on: February 27, 2026

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Evolution

Background:

  • Predicting RNA secondary structure relies on evolutionary history from aligned RNA sequences.
  • Accurate determination of evolutionary substitution rates for RNA is crucial but challenging without large, annotated alignments.
  • Existing methods often use rates from well-characterized RNA families like tRNA and rRNA.

Purpose of the Study:

  • To investigate the applicability of evolutionary rates from tRNA and rRNA for predicting the structure of rapidly evolving RNA.
  • To assess the accuracy of RNA secondary structure prediction for the 5'-region of HIV-1 using cross-family evolutionary rates.
  • To evaluate the robustness of structure prediction models to variations in evolutionary rate matrices.

Main Methods:

  • Applied evolutionary substitution rates derived from transfer RNA (tRNA) and ribosomal RNA (rRNA) datasets.
  • Utilized these rates to predict the secondary structure of the 5'-region of Human Immunodeficiency Virus type 1 (HIV-1).
  • Introduced randomized noise into rate matrices to test prediction stability.

Main Results:

  • RNA secondary structure predictions for HIV-1 showed agreement with experimental data.
  • Observed significantly increased evolutionary rates between A and G in both stem and loop regions of HIV-1.
  • Generated an improved alignment for the HIV-1 5' region, more consistent with its structure than existing database alignments.
  • Predictions remained reliable even with considerable variations in the evolutionary rate matrices.

Conclusions:

  • Transferring evolutionary rates from established RNA families (tRNA, rRNA) is a valid approach for predicting secondary structures of other RNA sequences, including rapidly evolving ones like HIV-1.
  • The method is robust to variations in evolutionary rates, suggesting broad applicability.
  • The study provides a more accurate structural alignment for the HIV-1 5' region.