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Comparative Study
, 13, 341

A Tale of Three Next Generation Sequencing Platforms: Comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq Sequencers

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Comparative Study

A Tale of Three Next Generation Sequencing Platforms: Comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq Sequencers

Michael A Quail et al. BMC Genomics.

Abstract

Background: Next 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.

Results: Sequence 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.

Conclusions: All 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.

Figures

Figure 1
Figure 1
Genome coverage plots for 15x depth randomly downsampled sequence coverage from the sequencing platforms tested. A) The percentage of the B. pertussis genome covered at different read depths; B) The number of bases covered at different depths for B. pertussis;C) The percentage of the S. aureus genome covered at different read depths; D) The number of bases covered at different depths for S. aureus;E) The percentage of the P. falciparum genome covered at different read depths; and F) The number of bases covered at different depths for P. falciparum.
Figure 2
Figure 2
Artemis genome browser[8]screenshots illustrating the variation in sequence coverage of a selected region of P. falciparum chromosome 11, with 15x depth of randomly normalized sequence from the platforms tested. In each window, the top graph shows the percentage GC content at each position, with the numbers on the right denoting the minimum, average and maximum values. The middle graph in each window is a coverage plot for the dataset from each instrument; the colour code is shown above graph a). Each of the middle graphs shows the depth of reads mapped at each position, and below that in B-D are the coordinates of the selected region in the genome with gene models on the (+) strand above and (−) strand below. A) View of the first 200 kb of chromosome 11. Graphs are smoothed with window size of 1000. A heatmap of the errors, normalized by the amount of mapping reads is included just below the GC content graph (PacBio top line, PGM middle and MiSeq bottom). B) Coverage over region of extreme GC content, ranging from 70% to 0%. C) Coverage over the gene PF3D7_1103500. D) Example of intergenic region between genes PF3D7_1104200 and PF3D7_1104300. The window size of B, C and D is 50 bp.
Figure 3
Figure 3
The effect of substituting Platinum HiFi PCR supermix with Kapa HiFi in the PGM library prep amplification step. A) The percentage of the P. falciparum genome covered at different read depths. The blue line shows the data obtained with the recommended Platinum enzyme and the green line with Kapa HiFi. The red line depicts ideal coverage behavior. B) The number of bases covered at different depths. C) Sequence representation vs. GC-content plots.
Figure 4
Figure 4
Illustration of platform-specific errors. The panels show Artemis BAM views with reads (horizontal bars) mapping to defined regions of chromosome 11 of P. falciparum from PacBio (P; top), Ion Torrent (I; middle) and MiSeq (M; bottom). Red vertical dashes are 1 base differences to the reference and white points are indels. A) Illustration of errors in Illumina data after a long homopolymer tract. Ion torrent data has a drop of coverage and multiple indels are visible in PacBio data. B) Example of errors associated with short homopolymer tracts. Multiple insertions are visible in the PacBio Data, deletions are observed in the PGM data and the MiSeq sequences read generally correct through the homopolymer tract. C) Example of strand specific deletions (red circles) observed in Ion Torrent data.
Figure 5
Figure 5
Accuracy of SNP detection from the S. aureus datasets generated from each platform, compared against the reference genome of its close relativeS. aureus USA300_FPR3757. Both the Torrent server variant calling pipeline and SAMtools were used for Ion Torrent data; SAMtools was used for Illumina data and SMRT portal pipeline for PacBio data. A) The percentage of SNPs detected using each platform overall (blue bar), and outside of repeats, indels and mobile genetic elements (red bar). B) The number of incorrect SNP calls for each platform overall (blue bar), and outside of repeats, indels and mobile genetic elements (red bar).

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References

    1. Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, Leamon JH, Johnson K, Milgrew MJ, Edwards M. et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature. 2011;475(7356):348–352. doi: 10.1038/nature10242. - DOI - PubMed
    1. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, Peluso P, Rank D, Baybayan P, Bettman B. et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009;323(5910):133–138. doi: 10.1126/science.1162986. - DOI - PubMed
    1. Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, Hall KP, Evers DJ, Barnes CL, Bignell HR. et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature. 2008;456(7218):53–59. doi: 10.1038/nature07517. - DOI - PMC - PubMed
    1. Kozarewa I, Ning Z, Quail MA, Sanders MJ, Berriman M, Turner DJ. Amplification-free Illumina sequencing-library preparation facilitates improved mapping and assembly of (G + C)-biased genomes. Nat Methods. 2009;6(4):291–295. doi: 10.1038/nmeth.1311. - DOI - PMC - PubMed
    1. Quail MA, Otto TD, Gu Y, Harris SR, Skelly TF, McQuillan JA, Swerdlow HP, Oyola SO. Optimal enzymes for amplifying sequencing libraries. Nat Methods. 2011;9(1):10–11. doi: 10.1038/nmeth.1814. - DOI - PubMed

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