Cargando…

Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes

A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method “BLSOM” for di-, tri-, and tetranucleo...

Descripción completa

Detalles Bibliográficos
Autores principales: Abe, Takashi, Hamano, Yuta, Ikemura, Toshimichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967822/
https://www.ncbi.nlm.nih.gov/pubmed/24741568
http://dx.doi.org/10.1155/2014/985706
_version_ 1782309069023870976
author Abe, Takashi
Hamano, Yuta
Ikemura, Toshimichi
author_facet Abe, Takashi
Hamano, Yuta
Ikemura, Toshimichi
author_sort Abe, Takashi
collection PubMed
description A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method “BLSOM” for di-, tri-, and tetranucleotide compositions in genome sequences, which can characterize sequence characteristics (genome signatures) of a wide range of species. In the present study, we generated BLSOMs for tetra- and pentanucleotide compositions in approximately one million sequence fragments derived from 101 eukaryotes, for which almost complete genome sequences were available. BLSOM recognized phylotype-specific characteristics (e.g., key combinations of oligonucleotide frequencies) in the genome sequences, permitting phylotype-specific clustering of the sequences without any information regarding the species. In our detailed examination of 12 Drosophila species, the correlation between their phylogenetic classification and the classification on the BLSOMs was observed to visualize oligonucleotides diagnostic for species-specific clustering.
format Online
Article
Text
id pubmed-3967822
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-39678222014-04-16 Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes Abe, Takashi Hamano, Yuta Ikemura, Toshimichi Biomed Res Int Research Article A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method “BLSOM” for di-, tri-, and tetranucleotide compositions in genome sequences, which can characterize sequence characteristics (genome signatures) of a wide range of species. In the present study, we generated BLSOMs for tetra- and pentanucleotide compositions in approximately one million sequence fragments derived from 101 eukaryotes, for which almost complete genome sequences were available. BLSOM recognized phylotype-specific characteristics (e.g., key combinations of oligonucleotide frequencies) in the genome sequences, permitting phylotype-specific clustering of the sequences without any information regarding the species. In our detailed examination of 12 Drosophila species, the correlation between their phylogenetic classification and the classification on the BLSOMs was observed to visualize oligonucleotides diagnostic for species-specific clustering. Hindawi Publishing Corporation 2014 2014-03-11 /pmc/articles/PMC3967822/ /pubmed/24741568 http://dx.doi.org/10.1155/2014/985706 Text en Copyright © 2014 Takashi Abe et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Abe, Takashi
Hamano, Yuta
Ikemura, Toshimichi
Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title_full Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title_fullStr Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title_full_unstemmed Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title_short Visualization of Genome Signatures of Eukaryote Genomes by Batch-Learning Self-Organizing Map with a Special Emphasis on Drosophila Genomes
title_sort visualization of genome signatures of eukaryote genomes by batch-learning self-organizing map with a special emphasis on drosophila genomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3967822/
https://www.ncbi.nlm.nih.gov/pubmed/24741568
http://dx.doi.org/10.1155/2014/985706
work_keys_str_mv AT abetakashi visualizationofgenomesignaturesofeukaryotegenomesbybatchlearningselforganizingmapwithaspecialemphasisondrosophilagenomes
AT hamanoyuta visualizationofgenomesignaturesofeukaryotegenomesbybatchlearningselforganizingmapwithaspecialemphasisondrosophilagenomes
AT ikemuratoshimichi visualizationofgenomesignaturesofeukaryotegenomesbybatchlearningselforganizingmapwithaspecialemphasisondrosophilagenomes