Genome Biology (Oct 2019)
Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
- 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
Affiliations
- Jon G. Sanders
- Department of Pediatrics, University of California San Diego School of Medicine
- Sergey Nurk
- Center for Algorithmic Biotechnology, Institute for Translational Biomedicine, St. Petersburg State University
- Rodolfo A. Salido
- Department of Pediatrics, University of California San Diego School of Medicine
- Jeremiah Minich
- Department of Pediatrics, University of California San Diego School of Medicine
- Zhenjiang Z. Xu
- Department of Pediatrics, University of California San Diego School of Medicine
- Qiyun Zhu
- Department of Pediatrics, University of California San Diego School of Medicine
- Cameron Martino
- Department of Pediatrics, University of California San Diego School of Medicine
- Marcus Fedarko
- Department of Computer Science and Engineering, University of California San Diego
- Timothy D. Arthur
- Department of Pediatrics, University of California San Diego School of Medicine
- Feng Chen
- Illumina, Inc.
- Brigid S. Boland
- Division of Gastroenterology, Department of Medicine, University of California San Diego
- Greg C. Humphrey
- Department of Pediatrics, University of California San Diego School of Medicine
- Caitriona Brennan
- Department of Pediatrics, University of California San Diego School of Medicine
- Karenina Sanders
- Department of Pediatrics, University of California San Diego School of Medicine
- James Gaffney
- Department of Pediatrics, University of California San Diego School of Medicine
- Kristen Jepsen
- Institute for Genomic Medicine, University of California San Diego
- Mahdieh Khosroheidari
- Institute for Genomic Medicine, University of California San Diego
- Cliff Green
- Institute for Genomic Medicine, University of California San Diego
- Marlon Liyanage
- Department of Pediatrics, University of California San Diego School of Medicine
- Jason W. Dang
- Department of Pediatrics, University of California San Diego School of Medicine
- Vanessa V. Phelan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego
- Robert A. Quinn
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego
- Anton Bankevich
- Center for Algorithmic Biotechnology, Institute for Translational Biomedicine, St. Petersburg State University
- John T. Chang
- Division of Gastroenterology, Department of Medicine, University of California San Diego
- Tariq M. Rana
- Department of Pediatrics, University of California San Diego School of Medicine
- Douglas J. Conrad
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of California San Diego
- William J. Sandborn
- Division of Gastroenterology, Department of Medicine, University of California San Diego
- Larry Smarr
- Department of Computer Science and Engineering, University of California San Diego
- Pieter C. Dorrestein
- Department of Pediatrics, University of California San Diego School of Medicine
- Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California San Diego
- Rob Knight
- Department of Pediatrics, University of California San Diego School of Medicine
- DOI
- https://doi.org/10.1186/s13059-019-1834-9
- Journal volume & issue
-
Vol. 20,
no. 1
pp. 1 – 14
Abstract
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.
Keywords
