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A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science

Reconstructing and visualizing phylogenetic relationships among living organisms is a fundamental challenge because not all organisms share the same genes. As a result, the first phylogenetic visualizations employed a single gene, e.g., rRNA genes, sufficiently conserved to be present in all organis...

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Detalles Bibliográficos
Autores principales: Khaledian, Ehdieh, Brayton, Kelly A., Broschat, Shira L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074868/
https://www.ncbi.nlm.nih.gov/pubmed/32102454
http://dx.doi.org/10.3390/microorganisms8020312
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author Khaledian, Ehdieh
Brayton, Kelly A.
Broschat, Shira L.
author_facet Khaledian, Ehdieh
Brayton, Kelly A.
Broschat, Shira L.
author_sort Khaledian, Ehdieh
collection PubMed
description Reconstructing and visualizing phylogenetic relationships among living organisms is a fundamental challenge because not all organisms share the same genes. As a result, the first phylogenetic visualizations employed a single gene, e.g., rRNA genes, sufficiently conserved to be present in all organisms but divergent enough to provide discrimination between groups. As more genome data became available, researchers began concatenating different combinations of genes or proteins to construct phylogenetic trees believed to be more robust because they incorporated more information. However, the genes or proteins chosen were based on ad hoc approaches. The large number of complete genome sequences available today allows the use of whole genomes to analyze relationships among organisms rather than using an ad hoc set of genes. We present a systematic approach for constructing a phylogenetic tree based on simultaneously clustering the complete proteomes of 360 bacterial species. From the homologous clusters, we identify 49 protein sequences shared by 99% of the organisms to build a tree. Of the 49 sequences, 47 have homologous sequences in both archaea and eukarya. The clusters are also used to create a network from which bacterial species with horizontally-transferred genes from other phyla are identified.
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spelling pubmed-70748682020-03-20 A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science Khaledian, Ehdieh Brayton, Kelly A. Broschat, Shira L. Microorganisms Article Reconstructing and visualizing phylogenetic relationships among living organisms is a fundamental challenge because not all organisms share the same genes. As a result, the first phylogenetic visualizations employed a single gene, e.g., rRNA genes, sufficiently conserved to be present in all organisms but divergent enough to provide discrimination between groups. As more genome data became available, researchers began concatenating different combinations of genes or proteins to construct phylogenetic trees believed to be more robust because they incorporated more information. However, the genes or proteins chosen were based on ad hoc approaches. The large number of complete genome sequences available today allows the use of whole genomes to analyze relationships among organisms rather than using an ad hoc set of genes. We present a systematic approach for constructing a phylogenetic tree based on simultaneously clustering the complete proteomes of 360 bacterial species. From the homologous clusters, we identify 49 protein sequences shared by 99% of the organisms to build a tree. Of the 49 sequences, 47 have homologous sequences in both archaea and eukarya. The clusters are also used to create a network from which bacterial species with horizontally-transferred genes from other phyla are identified. MDPI 2020-02-24 /pmc/articles/PMC7074868/ /pubmed/32102454 http://dx.doi.org/10.3390/microorganisms8020312 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Khaledian, Ehdieh
Brayton, Kelly A.
Broschat, Shira L.
A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title_full A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title_fullStr A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title_full_unstemmed A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title_short A Systematic Approach to Bacterial Phylogeny Using Order Level Sampling and Identification of HGT Using Network Science
title_sort systematic approach to bacterial phylogeny using order level sampling and identification of hgt using network science
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074868/
https://www.ncbi.nlm.nih.gov/pubmed/32102454
http://dx.doi.org/10.3390/microorganisms8020312
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