A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers

By M. Quail, Miriam Smith, P. Coupland, Thomas D. Otto, Simon R. Harris, Thomas Richard Connor, A. Bertoni, H. Swerdlow, Yong Gu. BMC Genomics, 2012

2,057 citations recorded by the source corpus.

BackgroundNext generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent’s PGM, Pacific Biosciences’ RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms, and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy.ResultsSequence generated by Ion Torrent, MiSeq and Pacific Biosciences technologies displays near perfect coverage behaviour on GC-rich, neutral and moderately AT-rich genomes, but a profound bias was observed upon sequencing the extremely AT-rich genome of Plasmodium falciparum on the PGM, resulting in no coverage for approximately 30% of the genome. We analysed the ability to call variants from each platform and found that we could call slightly more variants from Ion Torrent data compared to MiSeq data, but at the expense of a higher false positive rate. Variant calling from Pacific Biosciences data was possible but higher coverage depth was required. Context specific errors were observed in both PGM and MiSeq data, but not in that from the Pacific Biosciences platform.ConclusionsAll three fast turnaround sequencers evaluated here were able to generate usable sequence. However there are key differences between the quality of that data and the applications it will support.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/11bc28c49fc164952f587bba71e55d25db0d1757

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Citations in the corpus

Selection of biological indicators appropriate for European soil monitoring (2016, methodology): “For example, with regard to next generation sequencing (NGS) three new 100 platforms were released in 2011 alone: Ion Torrent’s PGM Pacific Biosciences’ RS 101 and the Illumina MiSeq (Quail et al., 2012).”
A first look at the Oxford Nanopore MinION sequencer (2014, methodology): “Together with other kinds of data, such as more accurate Illumina reads, it may assist genome assembly through scaffolding, similar to the way Pacific Biosciences reads are used now (Quail et al. 2012).”
Advances and Trends in Omics Technology Development (2022, background): “TGS, the third revolution in sequencing technology as enabled by Paciﬁc Biosciences (PacBio, 2011) (76) and Oxford Nanopore Technologies (ONT, 2014) (77), is a single molecular and real-time sequencing technique that allows for the long-read sequencing with low alignment and mapping errors during…”
Metabarcoding of lake benthic diatoms: from structure assemblages to ecological assessment (2018, background): “…(Elbrecht & Leese 2015), the choice of the PCR amplification protocol (Kebschull & Zador, 2015), the choice of the sequencing technology (Quail et al., 2012), the choice of the bioinformatics data processing (Schmidt et al., 2015), and the importance of the variation of cell biomass…”
'Big data', Hadoop and cloud computing in genomics (2013, background): “Advances in next generation sequencing technologies [1] has resulted in the generation of unprecedented levels of sequence data.”
Characterizing and measuring bias in sequence data (2013, background): “Illumina sequencing [18] has been shown to lose coverage in regions of high or low GC [19-22], a phenomenon also seen in other ‘ next-generation ’ technologies [3,6].”
A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples (2014, background): “However, the latest NGS laboratory workflows incur minimum turnaround times exceeding 8 h from clinical sample to sequence (Quail et al. 2012).”
The Third Revolution in Sequencing Technology. (2018, background): “5 kb) and average error rates were high ( 13%) [19], the technology has strongly improved over recent years.”
Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data (2013, methodology): “Two studies comparing benchtop sequencers, including the PGM, were recently published [2,3], both focusing on the assembly prospects of benchtop platforms on single isolate genomes.”
Real-Time Whole-Genome Sequencing for Routine Typing, Surveillance, and Outbreak Detection of Verotoxigenic Escherichia coli (2014, methodology): “Since the WGS part of this study was performed using the IonTorrent PGM, the price of routine typing and surveillance could be further decreased by performing sequencing on the Illumina MiSeq benchtop sequencer (35), as our current in-house material cost price on this sequencing platform is around 1”
Overview of Next Generation Sequencing Technologies (2018, methodology): “SBS methods have taken several distinct approaches (Fuller et al., 2009; Mardis, 2008; Metzker, 2010; Quail et al., 2012; Shendure & Ji, 2008).”