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Methods

Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform

James J. Kozich, Sarah L. Westcott, Nielson T. Baxter, Sarah K. Highlander, Patrick D. Schloss
James J. Kozich
aDepartment of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
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Sarah L. Westcott
aDepartment of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
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Nielson T. Baxter
aDepartment of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
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Sarah K. Highlander
bDepartment of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
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Patrick D. Schloss
aDepartment of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
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DOI: 10.1128/AEM.01043-13
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  • Fig 1
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    Fig 1

    Design of dual-index sequencing strategy and schematic describing the four sequencing reads. The primers specific to the 16S rRNA gene are shown in boldface black text, linkers are in blue, pads are in green, the index region is in red, and the adapters are underlined. This schematic is demonstrated using the V4-specific primer sequences and linkers. The PCR and sequencing primers for each of the three regions are provided in the supplemental material.

  • Fig 2
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    Fig 2

    Profile of sequencing errors in the first and second read (A and C) and the quality scores associated with different types of errors in the first and second read (B and D) using data from run 130403.

  • Fig 3
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    Fig 3

    Relationship between the error rate and the fraction of sequences kept as a function of the ΔQ value for the V34, V4, and V45 regions using data from run 130403.

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    Fig 4

    Principal coordinate ordination of ϴYC values (28) relating the community structures of the fecal microbiota from 12 mice collected on days 0 through 9 (Early) and days 141 through 150 (Late) after weaning.

Tables

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  • Table 1

    Summary of operating conditions for various MiSeq sequencing runs and machine-reported quality metricsa

    Run[DNA] (pM)Cluster density (103/mm2)% PhiX% of bases ≥Q30bReported machine error (%)No. of 16S rRNA pairs (×106)
    13040110.01,3133.863.71.3112.6
    1304035.01,0943.270.50.8912.4
    1304173.08396.274.60.9210.5
    1304221.86908.080.10.659.0
    • ↵a The four runs were performed using RTA v. 1.17.28 and MCS v. 2.2.0. Data for runs performed using previous versions of the software are provided in Tables S1 and S2 in the supplemental material.

    • ↵b Percentage of bases with a quality score of at least 30.

  • Table 2

    Summary of the error rates and number of observed OTUs for the sequencing runs described in Table 1

    Region and runError rate (%) for:% reads remaining from basic (ΔQ = 0)Average no. of OTUsa
    BasicΔQ = 6PreclusterMockbMockcSoilMouseHuman
    V34
        1304012.140.370.2110.326.949.61,110.6175.1187.5
        1304031.300.260.1227.631.147.81,095.8158.2164.1
        1304171.120.240.1027.935.152.21,038.6ND142.6
        1304220.910.290.1747.541.454.31,053.0162.5145.1
    V4
        1304011.080.060.0144.223.543.41,248.2136.1115.4
        1304030.670.050.0160.123.540.91,261.8133.9117.8
        1304170.400.050.0169.322.837.51,257.3135.5117.2
        1304220.280.050.0178.423.237.21,256.2132.8117.3
    V45
        1304014.600.870.6413.5191.9271.71,462.8198.0312.9
        1304033.310.790.5632.3180.4246.11,519.7213.3324.0
        1304172.380.660.4336.5110.8158.3ND180.4242.1
        1304221.670.580.3656.498.0131.61,403.3186.3227.2
    • ↵a The average number of OTUs is based on rarefaction of each sample to 5,000 sequences per sample; cells labeled ND reflect samples that did not have at least one replicate with more than 5,000 sequences.

    • ↵b Number of OTUs in the mock community when all chimeras were removed; in the absence of chimeras and sequencing errors, there should be 20 OTUs for all three regions.

    • ↵c Number of OTUs in the mock community when chimeras were removed using UCHIME.

  • Table 3

    Summary of assemblies using shotgun sequence data generated in parallel to 16S rRNA gene sequences

    LibraryNo. of reads (×106)No. of bases (×106 bp)No. of contigs (≥500 bp each)N50a (×103 bp)Reads that mapped to contigs (%)
    Clostridium clostridioforme D41.4436031737.8897
    C. clostridioforme CIP1102491.5438032343.8096
    Mock community2.4060031,9461.4666
    Human feces5.791,45027,3211.0049
    • ↵a The contig length where all contigs of that length or longer contain more than 50% of the bases found across all contigs.

Additional Files

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  • Supplemental material

    Files in this Data Supplement:

    • Supplemental file 1 -

      Challenges of sequencing the 16S rRNA gene with the MiSeq Platform, summary of operating conditions for various MiSeq sequencing runs and machine reported quality metrics (Table S1), summary of the error rates and number of observed OTUs for the sequencing runs described in Table S1 (Table S2), and protocols.

      PDF, 996K

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Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform
James J. Kozich, Sarah L. Westcott, Nielson T. Baxter, Sarah K. Highlander, Patrick D. Schloss
Applied and Environmental Microbiology Aug 2013, 79 (17) 5112-5120; DOI: 10.1128/AEM.01043-13

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Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform
James J. Kozich, Sarah L. Westcott, Nielson T. Baxter, Sarah K. Highlander, Patrick D. Schloss
Applied and Environmental Microbiology Aug 2013, 79 (17) 5112-5120; DOI: 10.1128/AEM.01043-13
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