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      A first look at the Oxford Nanopore MinION sequencer

      1 , 1
      Molecular Ecology Resources
      Wiley

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          Abstract

          Oxford Nanopore's third-generation single-molecule sequencing platform promises to decrease costs for reagents and instrumentation. After a 2-year hiatus following the initial announcement, the first devices have been released as part of an early access program. We explore the performance of this platform by resequencing the lambda phage genome, and amplicons from a snake venom gland transcriptome. Although the handheld MinION sequencer can generate more than 150 megabases of raw data in one run, at most a quarter of the resulting reads map to the reference, with less than average 10% identity. Much of the sequence consists of insertion/deletion errors, or is seemingly without similarity to the template. Using the lambda phage data as an example, although the reads are long, averaging 5 kb, at best 890 ± 1932 bases per mapped read could be matched to the reference without soft clipping. In the course of a 36 h run on the MinION, it was possible to resequence the 48 kb lambda phage reference at 16× coverage. Currently, substantially larger projects would not be feasible using the MinION. Without increases in accuracy, which would be required for applications such as genome scaffolding and phasing, the current utility of the MinION appears limited. Library preparation requires access to a molecular laboratory, and is of similar complexity and cost to that of other next-generation sequencing platforms. The MinION is an exciting step in a new direction for single-molecule sequencing, though it will require dramatic decreases in error rates before it lives up to its promise.

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          Most cited references16

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          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
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            An integrated semiconductor device enabling non-optical genome sequencing.

            The seminal importance of DNA sequencing to the life sciences, biotechnology and medicine has driven the search for more scalable and lower-cost solutions. Here we describe a DNA sequencing technology in which scalable, low-cost semiconductor manufacturing techniques are used to make an integrated circuit able to directly perform non-optical DNA sequencing of genomes. Sequence data are obtained by directly sensing the ions produced by template-directed DNA polymerase synthesis using all-natural nucleotides on this massively parallel semiconductor-sensing device or ion chip. The ion chip contains ion-sensitive, field-effect transistor-based sensors in perfect register with 1.2 million wells, which provide confinement and allow parallel, simultaneous detection of independent sequencing reactions. Use of the most widely used technology for constructing integrated circuits, the complementary metal-oxide semiconductor (CMOS) process, allows for low-cost, large-scale production and scaling of the device to higher densities and larger array sizes. We show the performance of the system by sequencing three bacterial genomes, its robustness and scalability by producing ion chips with up to 10 times as many sensors and sequencing a human genome.
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              Performance comparison of benchtop high-throughput sequencing platforms.

              Three benchtop high-throughput sequencing instruments are now available. The 454 GS Junior (Roche), MiSeq (Illumina) and Ion Torrent PGM (Life Technologies) are laser-printer sized and offer modest set-up and running costs. Each instrument can generate data required for a draft bacterial genome sequence in days, making them attractive for identifying and characterizing pathogens in the clinical setting. We compared the performance of these instruments by sequencing an isolate of Escherichia coli O104:H4, which caused an outbreak of food poisoning in Germany in 2011. The MiSeq had the highest throughput per run (1.6 Gb/run, 60 Mb/h) and lowest error rates. The 454 GS Junior generated the longest reads (up to 600 bases) and most contiguous assemblies but had the lowest throughput (70 Mb/run, 9 Mb/h). Run in 100-bp mode, the Ion Torrent PGM had the highest throughput (80–100 Mb/h). Unlike the MiSeq, the Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors (1.5 and 0.38 errors per 100 bases, respectively).
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                Author and article information

                Journal
                Molecular Ecology Resources
                Mol Ecol Resour
                Wiley
                1755098X
                November 2014
                November 2014
                September 24 2014
                : 14
                : 6
                : 1097-1102
                Affiliations
                [1 ]Ecology and Evolution Unit; Okinawa Institute of Science and Technology Graduate University; 1919-1 Tancha Onna-son Kunigami-gun Okinawa 904-0495 Japan
                Article
                10.1111/1755-0998.12324
                25187008
                b1072d22-3eee-49cc-ad04-9faefb32ced3
                © 2014

                http://doi.wiley.com/10.1002/tdm_license_1.1

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