Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
Abstract As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore pro...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-10-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13059-019-1834-9 |
| _version_ | 1818281120903462912 |
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| author | Jon G. Sanders Sergey Nurk Rodolfo A. Salido Jeremiah Minich Zhenjiang Z. Xu Qiyun Zhu Cameron Martino Marcus Fedarko Timothy D. Arthur Feng Chen Brigid S. Boland Greg C. Humphrey Caitriona Brennan Karenina Sanders James Gaffney Kristen Jepsen Mahdieh Khosroheidari Cliff Green Marlon Liyanage Jason W. Dang Vanessa V. Phelan Robert A. Quinn Anton Bankevich John T. Chang Tariq M. Rana Douglas J. Conrad William J. Sandborn Larry Smarr Pieter C. Dorrestein Pavel A. Pevzner Rob Knight |
| author_facet | Jon G. Sanders Sergey Nurk Rodolfo A. Salido Jeremiah Minich Zhenjiang Z. Xu Qiyun Zhu Cameron Martino Marcus Fedarko Timothy D. Arthur Feng Chen Brigid S. Boland Greg C. Humphrey Caitriona Brennan Karenina Sanders James Gaffney Kristen Jepsen Mahdieh Khosroheidari Cliff Green Marlon Liyanage Jason W. Dang Vanessa V. Phelan Robert A. Quinn Anton Bankevich John T. Chang Tariq M. Rana Douglas J. Conrad William J. Sandborn Larry Smarr Pieter C. Dorrestein Pavel A. Pevzner Rob Knight |
| author_sort | Jon G. Sanders |
| collection | DOAJ |
| description | Abstract As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing. |
| first_indexed | 2024-12-13T00:00:04Z |
| format | Article |
| id | doaj.art-42e8537276ff4a9bba279cd526759a65 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-13T00:00:04Z |
| publishDate | 2019-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-42e8537276ff4a9bba279cd526759a652022-12-22T00:06:27ZengBMCGenome Biology1474-760X2019-10-0120111410.1186/s13059-019-1834-9Optimizing sequencing protocols for leaderboard metagenomics by combining long and short readsJon G. Sanders0Sergey Nurk1Rodolfo A. Salido2Jeremiah Minich3Zhenjiang Z. Xu4Qiyun Zhu5Cameron Martino6Marcus Fedarko7Timothy D. Arthur8Feng Chen9Brigid S. Boland10Greg C. Humphrey11Caitriona Brennan12Karenina Sanders13James Gaffney14Kristen Jepsen15Mahdieh Khosroheidari16Cliff Green17Marlon Liyanage18Jason W. Dang19Vanessa V. Phelan20Robert A. Quinn21Anton Bankevich22John T. Chang23Tariq M. Rana24Douglas J. Conrad25William J. Sandborn26Larry Smarr27Pieter C. Dorrestein28Pavel A. Pevzner29Rob Knight30Department of Pediatrics, University of California San Diego School of MedicineCenter for Algorithmic Biotechnology, Institute for Translational Biomedicine, St. Petersburg State UniversityDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Computer Science and Engineering, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineIllumina, Inc.Division of Gastroenterology, Department of Medicine, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineInstitute for Genomic Medicine, University of California San DiegoInstitute for Genomic Medicine, University of California San DiegoInstitute for Genomic Medicine, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Pediatrics, University of California San Diego School of MedicineSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San DiegoSkaggs School of Pharmacy and Pharmaceutical Sciences, University of California San DiegoCenter for Algorithmic Biotechnology, Institute for Translational Biomedicine, St. Petersburg State UniversityDivision of Gastroenterology, Department of Medicine, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of California San DiegoDivision of Gastroenterology, Department of Medicine, University of California San DiegoDepartment of Computer Science and Engineering, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineDepartment of Computer Science and Engineering, University of California San DiegoDepartment of Pediatrics, University of California San Diego School of MedicineAbstract As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.http://link.springer.com/article/10.1186/s13059-019-1834-9Leaderboard metagenomeLong readsBenchmarkAssemblyBinning |
| spellingShingle | Jon G. Sanders Sergey Nurk Rodolfo A. Salido Jeremiah Minich Zhenjiang Z. Xu Qiyun Zhu Cameron Martino Marcus Fedarko Timothy D. Arthur Feng Chen Brigid S. Boland Greg C. Humphrey Caitriona Brennan Karenina Sanders James Gaffney Kristen Jepsen Mahdieh Khosroheidari Cliff Green Marlon Liyanage Jason W. Dang Vanessa V. Phelan Robert A. Quinn Anton Bankevich John T. Chang Tariq M. Rana Douglas J. Conrad William J. Sandborn Larry Smarr Pieter C. Dorrestein Pavel A. Pevzner Rob Knight Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads Genome Biology Leaderboard metagenome Long reads Benchmark Assembly Binning |
| title | Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| title_full | Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| title_fullStr | Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| title_full_unstemmed | Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| title_short | Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| title_sort | optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads |
| topic | Leaderboard metagenome Long reads Benchmark Assembly Binning |
| url | http://link.springer.com/article/10.1186/s13059-019-1834-9 |
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