Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency

<p>Abstract</p> <p>Background</p> <p>Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However...

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Main Authors: Hsu Ming-Tsung, Su Chien-Hao, Weng Francis C, Wang Tse-Yi, Tsai Huai-Kuang, Wang Daryi
Format: Article
Language:English
Published: BMC 2010-11-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/11/565
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spelling doaj-db9e3ad2642f4a4d8e5fea1baad949812020-11-24T22:10:24ZengBMCBMC Bioinformatics1471-21052010-11-0111156510.1186/1471-2105-11-565Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacencyHsu Ming-TsungSu Chien-HaoWeng Francis CWang Tse-YiTsai Huai-KuangWang Daryi<p>Abstract</p> <p>Background</p> <p>Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut-offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies.</p> <p>Results</p> <p>Among the discarded data, we found that 23.7 ± 3.9% of singletons and 14.1 ± 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The <it>Pearson </it>correlation coefficient revealed a high degree of similarity (0.94 ± 0.03 at the phylum rank and 0.80 ± 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach.</p> <p>Conclusions</p> <p>Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.</p> http://www.biomedcentral.com/1471-2105/11/565
collection DOAJ
language English
format Article
sources DOAJ
author Hsu Ming-Tsung
Su Chien-Hao
Weng Francis C
Wang Tse-Yi
Tsai Huai-Kuang
Wang Daryi
spellingShingle Hsu Ming-Tsung
Su Chien-Hao
Weng Francis C
Wang Tse-Yi
Tsai Huai-Kuang
Wang Daryi
Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
BMC Bioinformatics
author_facet Hsu Ming-Tsung
Su Chien-Hao
Weng Francis C
Wang Tse-Yi
Tsai Huai-Kuang
Wang Daryi
author_sort Hsu Ming-Tsung
title Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
title_short Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
title_full Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
title_fullStr Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
title_full_unstemmed Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency
title_sort reanalyze unassigned reads in sanger based metagenomic data using conserved gene adjacency
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2010-11-01
description <p>Abstract</p> <p>Background</p> <p>Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut-offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies.</p> <p>Results</p> <p>Among the discarded data, we found that 23.7 ± 3.9% of singletons and 14.1 ± 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The <it>Pearson </it>correlation coefficient revealed a high degree of similarity (0.94 ± 0.03 at the phylum rank and 0.80 ± 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach.</p> <p>Conclusions</p> <p>Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.</p>
url http://www.biomedcentral.com/1471-2105/11/565
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