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Joining Illumina paired-end reads for classifying phylogenetic marker sequences
BACKGROUND: Illumina sequencing of a marker gene is popular in metagenomic studies. However, Illumina paired-end (PE) reads sometimes cannot be merged into single reads for subsequent analysis. When mergeable PE reads are limited, one can simply use only first reads for taxonomy annotation, but that...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071698/ https://www.ncbi.nlm.nih.gov/pubmed/32171248 http://dx.doi.org/10.1186/s12859-020-3445-6 |
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author | Liu, Tsunglin Chen, Chen-Yu Chen-Deng, An Chen, Yi-Lin Wang, Jiu-Yao Hou, Yung-I Lin, Min-Ching |
author_facet | Liu, Tsunglin Chen, Chen-Yu Chen-Deng, An Chen, Yi-Lin Wang, Jiu-Yao Hou, Yung-I Lin, Min-Ching |
author_sort | Liu, Tsunglin |
collection | PubMed |
description | BACKGROUND: Illumina sequencing of a marker gene is popular in metagenomic studies. However, Illumina paired-end (PE) reads sometimes cannot be merged into single reads for subsequent analysis. When mergeable PE reads are limited, one can simply use only first reads for taxonomy annotation, but that wastes information in the second reads. Presumably, including second reads should improve taxonomy annotation. However, a rigorous investigation of how best to do this and how much can be gained has not been reported. RESULTS: We evaluated two methods of joining as opposed to merging PE reads into single reads for taxonomy annotation using simulated data with sequencing errors. Our rigorous evaluation involved several top classifiers (RDP classifier, SINTAX, and two alignment-based methods) and realistic benchmark datasets. For most classifiers, read joining ameliorated the impact of sequencing errors and improved the accuracy of taxonomy predictions. For alignment-based top-hit classifiers, rearranging the reference sequences is recommended to avoid improper alignments of joined reads. For word-counting classifiers, joined reads could be compared to the original reference for classification. We also applied read joining to our own real MiSeq PE data of nasal microbiota of asthmatic children. Before joining, trimming low quality bases was necessary for optimizing taxonomy annotation and sequence clustering. We then showed that read joining increased the amount of effective data for taxonomy annotation. Using these joined trimmed reads, we were able to identify two promising bacterial genera that might be associated with asthma exacerbation. CONCLUSIONS: When mergeable PE reads are limited, joining them into single reads for taxonomy annotation is always recommended. Reference sequences may need to be rearranged accordingly depending on the classifier. Read joining also relaxes the constraint on primer selection, and thus may unleash the full capacity of Illumina PE data for taxonomy annotation. Our work provides guidance for fully utilizing PE data of a marker gene when mergeable reads are limited. |
format | Online Article Text |
id | pubmed-7071698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70716982020-03-18 Joining Illumina paired-end reads for classifying phylogenetic marker sequences Liu, Tsunglin Chen, Chen-Yu Chen-Deng, An Chen, Yi-Lin Wang, Jiu-Yao Hou, Yung-I Lin, Min-Ching BMC Bioinformatics Methodology Article BACKGROUND: Illumina sequencing of a marker gene is popular in metagenomic studies. However, Illumina paired-end (PE) reads sometimes cannot be merged into single reads for subsequent analysis. When mergeable PE reads are limited, one can simply use only first reads for taxonomy annotation, but that wastes information in the second reads. Presumably, including second reads should improve taxonomy annotation. However, a rigorous investigation of how best to do this and how much can be gained has not been reported. RESULTS: We evaluated two methods of joining as opposed to merging PE reads into single reads for taxonomy annotation using simulated data with sequencing errors. Our rigorous evaluation involved several top classifiers (RDP classifier, SINTAX, and two alignment-based methods) and realistic benchmark datasets. For most classifiers, read joining ameliorated the impact of sequencing errors and improved the accuracy of taxonomy predictions. For alignment-based top-hit classifiers, rearranging the reference sequences is recommended to avoid improper alignments of joined reads. For word-counting classifiers, joined reads could be compared to the original reference for classification. We also applied read joining to our own real MiSeq PE data of nasal microbiota of asthmatic children. Before joining, trimming low quality bases was necessary for optimizing taxonomy annotation and sequence clustering. We then showed that read joining increased the amount of effective data for taxonomy annotation. Using these joined trimmed reads, we were able to identify two promising bacterial genera that might be associated with asthma exacerbation. CONCLUSIONS: When mergeable PE reads are limited, joining them into single reads for taxonomy annotation is always recommended. Reference sequences may need to be rearranged accordingly depending on the classifier. Read joining also relaxes the constraint on primer selection, and thus may unleash the full capacity of Illumina PE data for taxonomy annotation. Our work provides guidance for fully utilizing PE data of a marker gene when mergeable reads are limited. BioMed Central 2020-03-14 /pmc/articles/PMC7071698/ /pubmed/32171248 http://dx.doi.org/10.1186/s12859-020-3445-6 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Liu, Tsunglin Chen, Chen-Yu Chen-Deng, An Chen, Yi-Lin Wang, Jiu-Yao Hou, Yung-I Lin, Min-Ching Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title | Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title_full | Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title_fullStr | Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title_full_unstemmed | Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title_short | Joining Illumina paired-end reads for classifying phylogenetic marker sequences |
title_sort | joining illumina paired-end reads for classifying phylogenetic marker sequences |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071698/ https://www.ncbi.nlm.nih.gov/pubmed/32171248 http://dx.doi.org/10.1186/s12859-020-3445-6 |
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