Euclidean Distance Analysis Enables Nucleotide Skew Analysis in Viral Genomes
Joint Authors
Berkhout, Ben
van Hemert, Formijn
Jebbink, Maarten
van der Ark, Andries
Scholer, Frits
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-30
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Nucleotide skew analysis is a versatile method to study the nucleotide composition of RNA/DNA molecules, in particular to reveal characteristic sequence signatures.
For instance, skew analysis of the nucleotide bias of several viral RNA genomes indicated that it is enriched in the unpaired, single-stranded genome regions, thus creating an even more striking virus-specific signature.
The comparison of skew graphs for many virus isolates or families is difficult, time-consuming, and nonquantitative.
Here, we present a procedure for a more simple identification of similarities and dissimilarities between nucleotide skew data of coronavirus, flavivirus, picornavirus, and HIV-1 RNA genomes.
Window and step sizes were normalized to correct for differences in length of the viral genome.
Cumulative skew data are converted into pairwise Euclidean distance matrices, which can be presented as neighbor-joining trees.
We present skew value trees for the four virus families and show that closely related viruses are placed in small clusters.
Importantly, the skew value trees are similar to the trees constructed by a “classical” model of evolutionary nucleotide substitution.
Thus, we conclude that the simple calculation of Euclidean distances between nucleotide skew data allows an easy and quantitative comparison of characteristic sequence signatures of virus genomes.
These results indicate that the Euclidean distance analysis of nucleotide skew data forms a nice addition to the virology toolbox.
American Psychological Association (APA)
van Hemert, Formijn& Jebbink, Maarten& van der Ark, Andries& Scholer, Frits& Berkhout, Ben. 2018. Euclidean Distance Analysis Enables Nucleotide Skew Analysis in Viral Genomes. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132091
Modern Language Association (MLA)
van Hemert, Formijn…[et al.]. Euclidean Distance Analysis Enables Nucleotide Skew Analysis in Viral Genomes. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1132091
American Medical Association (AMA)
van Hemert, Formijn& Jebbink, Maarten& van der Ark, Andries& Scholer, Frits& Berkhout, Ben. Euclidean Distance Analysis Enables Nucleotide Skew Analysis in Viral Genomes. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1132091
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132091