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A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy

Microbial diversity has always presented taxonomic challenges. With the popularity of next-generation sequencing technology, more unculturable bacteria have been sequenced, facilitating the discovery of additional new species and complicated current microbial classification. The major challenge is t...

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Autores principales: Tsai, Ming-Hsin, Liu, Yen-Yi, Soo, Von-Wun, Chen, Chih-Chieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616886/
https://www.ncbi.nlm.nih.gov/pubmed/31163634
http://dx.doi.org/10.3390/microorganisms7060161
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author Tsai, Ming-Hsin
Liu, Yen-Yi
Soo, Von-Wun
Chen, Chih-Chieh
author_facet Tsai, Ming-Hsin
Liu, Yen-Yi
Soo, Von-Wun
Chen, Chih-Chieh
author_sort Tsai, Ming-Hsin
collection PubMed
description Microbial diversity has always presented taxonomic challenges. With the popularity of next-generation sequencing technology, more unculturable bacteria have been sequenced, facilitating the discovery of additional new species and complicated current microbial classification. The major challenge is to assign appropriate taxonomic names. Hence, assessing the consistency between taxonomy and genomic relatedness is critical. We proposed and applied a genome comparison approach to a large-scale survey to investigate the distribution of genomic differences among microorganisms. The approach applies a genome-wide criterion, homologous coverage ratio (HCR), for describing the homology between species. The survey included 7861 microbial genomes that excluded plasmids, and 1220 pairs of genera exhibited ambiguous classification. In this study, we also compared the performance of HCR and average nucleotide identity (ANI). The results indicated that HCR and ANI analyses yield comparable results, but a few examples suggested that HCR has a superior clustering effect. In addition, we used the Genome Taxonomy Database (GTDB), the gold standard for taxonomy, to validate our analysis. The GTDB offers 120 ubiquitous single-copy proteins as marker genes for species classification. We determined that the analysis of the GTDB still results in classification boundary blur between some genera and that the marker gene-based approach has limitations. Although the choice of marker genes has been quite rigorous, the bias of marker gene selection remains unavoidable. Therefore, methods based on genomic alignment should be considered for use for species classification in order to avoid the bias of marker gene selection. On the basis of our observations of microbial diversity, microbial classification should be re-examined using genome-wide comparisons.
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spelling pubmed-66168862019-07-18 A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy Tsai, Ming-Hsin Liu, Yen-Yi Soo, Von-Wun Chen, Chih-Chieh Microorganisms Article Microbial diversity has always presented taxonomic challenges. With the popularity of next-generation sequencing technology, more unculturable bacteria have been sequenced, facilitating the discovery of additional new species and complicated current microbial classification. The major challenge is to assign appropriate taxonomic names. Hence, assessing the consistency between taxonomy and genomic relatedness is critical. We proposed and applied a genome comparison approach to a large-scale survey to investigate the distribution of genomic differences among microorganisms. The approach applies a genome-wide criterion, homologous coverage ratio (HCR), for describing the homology between species. The survey included 7861 microbial genomes that excluded plasmids, and 1220 pairs of genera exhibited ambiguous classification. In this study, we also compared the performance of HCR and average nucleotide identity (ANI). The results indicated that HCR and ANI analyses yield comparable results, but a few examples suggested that HCR has a superior clustering effect. In addition, we used the Genome Taxonomy Database (GTDB), the gold standard for taxonomy, to validate our analysis. The GTDB offers 120 ubiquitous single-copy proteins as marker genes for species classification. We determined that the analysis of the GTDB still results in classification boundary blur between some genera and that the marker gene-based approach has limitations. Although the choice of marker genes has been quite rigorous, the bias of marker gene selection remains unavoidable. Therefore, methods based on genomic alignment should be considered for use for species classification in order to avoid the bias of marker gene selection. On the basis of our observations of microbial diversity, microbial classification should be re-examined using genome-wide comparisons. MDPI 2019-06-03 /pmc/articles/PMC6616886/ /pubmed/31163634 http://dx.doi.org/10.3390/microorganisms7060161 Text en © 2019 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
Tsai, Ming-Hsin
Liu, Yen-Yi
Soo, Von-Wun
Chen, Chih-Chieh
A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title_full A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title_fullStr A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title_full_unstemmed A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title_short A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy
title_sort new genome-to-genome comparison approach for large-scale revisiting of current microbial taxonomy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616886/
https://www.ncbi.nlm.nih.gov/pubmed/31163634
http://dx.doi.org/10.3390/microorganisms7060161
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