Evolutionary rate variation and RNA secondary structure prediction

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Evolutionary rate variation and RNA secondary structure prediction. / Knudsen, B; Andersen, E S; Damgaard, Christian Kroun; Kjems, Jørgen; Gorodkin, Jan.

In: Computational Biology and Chemistry, Vol. 28, No. 3, 07.2004, p. 219-26.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

APA

CBE

MLA

Vancouver

Author

Knudsen, B ; Andersen, E S ; Damgaard, Christian Kroun ; Kjems, Jørgen ; Gorodkin, Jan. / Evolutionary rate variation and RNA secondary structure prediction. In: Computational Biology and Chemistry. 2004 ; Vol. 28, No. 3. pp. 219-26.

Bibtex

@article{1ffba570f2734b8397da4044d46f8c7b,
title = "Evolutionary rate variation and RNA secondary structure prediction",
abstract = "Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type of approach. Determining these rates can be hard to do reliably without a large and accurate initial alignment, which ideally also has structural annotation. Hence, one must often apply rates extracted from other RNA families with trusted alignments and structures. Here, we investigate this problem by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions. In addition we obtained an alignment of the 5' HIV-1 region that is more consistent with the structure than that currently in the database. We added randomized noise to the original values of the rates to investigate the stability of predictions to rate matrix deviations. We find that changes within a fairly large range still produce reliable predictions and conclude that using rates from a limited set of RNA sequences is valid over a broader range of sequences.",
keywords = "Algorithms, Base Pairing, Databases, Nucleic Acid, Evolution, Molecular, HIV-1, Kinetics, Models, Genetic, Nucleic Acid Conformation, Point Mutation, RNA, RNA, Ribosomal, RNA, Transfer, RNA, Viral, Sequence Alignment",
author = "B Knudsen and Andersen, {E S} and Damgaard, {Christian Kroun} and J{\o}rgen Kjems and Jan Gorodkin",
year = "2004",
month = "7",
doi = "10.1016/j.compbiolchem.2004.04.001",
language = "English",
volume = "28",
pages = "219--26",
journal = "Computational Biology and Chemistry",
issn = "1476-9271",
publisher = "Elsevier Ltd",
number = "3",

}

RIS

TY - JOUR

T1 - Evolutionary rate variation and RNA secondary structure prediction

AU - Knudsen, B

AU - Andersen, E S

AU - Damgaard, Christian Kroun

AU - Kjems, Jørgen

AU - Gorodkin, Jan

PY - 2004/7

Y1 - 2004/7

N2 - Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type of approach. Determining these rates can be hard to do reliably without a large and accurate initial alignment, which ideally also has structural annotation. Hence, one must often apply rates extracted from other RNA families with trusted alignments and structures. Here, we investigate this problem by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions. In addition we obtained an alignment of the 5' HIV-1 region that is more consistent with the structure than that currently in the database. We added randomized noise to the original values of the rates to investigate the stability of predictions to rate matrix deviations. We find that changes within a fairly large range still produce reliable predictions and conclude that using rates from a limited set of RNA sequences is valid over a broader range of sequences.

AB - Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type of approach. Determining these rates can be hard to do reliably without a large and accurate initial alignment, which ideally also has structural annotation. Hence, one must often apply rates extracted from other RNA families with trusted alignments and structures. Here, we investigate this problem by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions. In addition we obtained an alignment of the 5' HIV-1 region that is more consistent with the structure than that currently in the database. We added randomized noise to the original values of the rates to investigate the stability of predictions to rate matrix deviations. We find that changes within a fairly large range still produce reliable predictions and conclude that using rates from a limited set of RNA sequences is valid over a broader range of sequences.

KW - Algorithms

KW - Base Pairing

KW - Databases, Nucleic Acid

KW - Evolution, Molecular

KW - HIV-1

KW - Kinetics

KW - Models, Genetic

KW - Nucleic Acid Conformation

KW - Point Mutation

KW - RNA

KW - RNA, Ribosomal

KW - RNA, Transfer

KW - RNA, Viral

KW - Sequence Alignment

U2 - 10.1016/j.compbiolchem.2004.04.001

DO - 10.1016/j.compbiolchem.2004.04.001

M3 - Journal article

VL - 28

SP - 219

EP - 226

JO - Computational Biology and Chemistry

JF - Computational Biology and Chemistry

SN - 1476-9271

IS - 3

ER -