NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data
Abstract Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-02-01
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| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.7146 |
| _version_ | 1818640708217602048 |
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| author | Kristoffer Sahlin Marisa C. W. Lim Stefan Prost |
| author_facet | Kristoffer Sahlin Marisa C. W. Lim Stefan Prost |
| author_sort | Kristoffer Sahlin |
| collection | DOAJ |
| description | Abstract Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon‐based high‐throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high‐quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long‐read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines. |
| first_indexed | 2024-12-16T23:15:34Z |
| format | Article |
| id | doaj.art-40fddca195964d17bc4d5f95ff639f37 |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-12-16T23:15:34Z |
| publishDate | 2021-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-40fddca195964d17bc4d5f95ff639f372022-12-21T22:12:18ZengWileyEcology and Evolution2045-77582021-02-011131392139810.1002/ece3.7146NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing dataKristoffer Sahlin0Marisa C. W. Lim1Stefan Prost2Department of Mathematics Science for Life Laboratory Stockholm University Stockholm SwedenDepartment of Population Health and Reproduction University of California Davis CA USALOEWE‐Centre for Translational Biodiversity GenomicsSenckenberg Frankfurt GermanyAbstract Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon‐based high‐throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high‐quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long‐read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines.https://doi.org/10.1002/ece3.7146amplicon sequencingDNA barcodingsequence clusteringthird‐generation sequencing |
| spellingShingle | Kristoffer Sahlin Marisa C. W. Lim Stefan Prost NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data Ecology and Evolution amplicon sequencing DNA barcoding sequence clustering third‐generation sequencing |
| title | NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data |
| title_full | NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data |
| title_fullStr | NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data |
| title_full_unstemmed | NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data |
| title_short | NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data |
| title_sort | ngspeciesid dna barcode and amplicon consensus generation from long read sequencing data |
| topic | amplicon sequencing DNA barcoding sequence clustering third‐generation sequencing |
| url | https://doi.org/10.1002/ece3.7146 |
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