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Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Costello, Maura, Fleharty, Mark, Abreu, Justin, Farjoun, Yossi, Ferriera, Steven, Holmes, Laurie, Granger, Brian, Green, Lisa, Howd, Tom, Mason, Tamara, Vicente, Gina, Dasilva, Michael, Brodeur, Wendy, DeSmet, Timothy, Dodge, Sheila, Lennon, Niall J., Gabriel, Stacey·2018·BMC Genomics
DOI 10.1186/s12864-018-4703-0PMC PMC5941783

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Fig. 1 Percent contamination over time for whole genomes sequenced on HiSeqX. Panel at left: Single indexed PCR-free library contamination by month. Contamination significantly increased when we began 8-plex pooling and worsened as we introduced 24-plex pooling. Panel at right: Single indexed PCR-plus library contamination by month. Although overall contamination was lower for PCR-plus, rates did increase significantly as well when we began pooling
Fig. 1 Percent contamination over time for whole genomes sequenced on HiSeqX. Panel at left: Single indexed PCR-free library contamination by month. Contamination significantly increased when we began 8-plex pooling and worsened as we introduced 24-plex pooling. Panel at right: Single indexed PCR-plus library contamination by month. Although overall contamination was lower for PCR-plus, rates did increase significantly as well when we began poolingCC BY · PubMed Central
Fig. 2 Contamination for single versus dual indexed pooled PCR-free libraries on HiSeqX. Percent contamination month by month continuous run chart as measured by VerifyBamID [3] for 24-plexed PCR-free genomes, demonstrating the drop in mean contamination after implementation of unique dual indexing. Red reference line is the mean, green reference lines are upper and lower control limits of the data generated by JMP statistical software
Fig. 2 Contamination for single versus dual indexed pooled PCR-free libraries on HiSeqX. Percent contamination month by month continuous run chart as measured by VerifyBamID [3] for 24-plexed PCR-free genomes, demonstrating the drop in mean contamination after implementation of unique dual indexing. Red reference line is the mean, green reference lines are upper and lower control limits of the data generated by JMP statistical softwareCC BY · PubMed Central
Fig. 3 Index swapping leads to incorrect assignment of reads from fusion transcripts in cell line RNA-seq data. Counts of reads spanning fusion transcripts for 5 different gene fusions in 3 different cell lines using STAR-Fusion software. Four RNA-seq libraries were pooled for each cell line for a total of 12 libraries, and sequenced on a HiSeq 4000 lane. Only the K562 cell line should contain the BCR—ABL1 translocation, however reads containing BCR—ABL1 (blue and black striped) were also found in data files for the other two cell lines due to index swapping
Fig. 3 Index swapping leads to incorrect assignment of reads from fusion transcripts in cell line RNA-seq data. Counts of reads spanning fusion transcripts for 5 different gene fusions in 3 different cell lines using STAR-Fusion software. Four RNA-seq libraries were pooled for each cell line for a total of 12 libraries, and sequenced on a HiSeq 4000 lane. Only the K562 cell line should contain the BCR—ABL1 translocation, however reads containing BCR—ABL1 (blue and black striped) were also found in data files for the other two cell lines due to index swappingCC BY · PubMed Central
Fig. 4 Variability of index swap rates from pool to pool and flow cell to flow cell. Index swapping rates plotted for seven 24-plex pools, each sequenced on at least two HiSeqX flow cells and prepared using identical automated methods on a Hamilton MiniStar. Each data point represents a flow cell lane. The data shows variability between different pools, but also variability for the same pools run on different flow cells, indicating that flow cell and/or ExAmp reagents also influence swap rate variability
Fig. 4 Variability of index swap rates from pool to pool and flow cell to flow cell. Index swapping rates plotted for seven 24-plex pools, each sequenced on at least two HiSeqX flow cells and prepared using identical automated methods on a Hamilton MiniStar. Each data point represents a flow cell lane. The data shows variability between different pools, but also variability for the same pools run on different flow cells, indicating that flow cell and/or ExAmp reagents also influence swap rate variabilityCC BY · PubMed Central
Fig. 5 Characterization of index swapping mechanism. a Diagram of a HiSeqX flow cell lane colored by number of index swaps detected at each surface tile, showing relatively uniform distribution of swapping across the entire lane and both surfaces. b Read counts for all 36 index combinations in a 6-plex pool of uniquely dual indexed libraries. The combinations in heavy bordered cells with blue text along the diagonal are the correct index combinations; read counts for all other combinations are due to index swapping. Note all indexes participate in swapping relatively equally. c Mean insert size (bp) and percent chimerism calculated by Picard for both swapped and non-swapped reads. Swapped reads have shorter inserts and higher rates of chimeric read pairs. d Normalized human coverage across GC content bins, indicating there are less high GC reads in the swapped population (blue) compared to non-swapped (red) and all other non-demultiplexed (green) populations
Fig. 5 Characterization of index swapping mechanism. a Diagram of a HiSeqX flow cell lane colored by number of index swaps detected at each surface tile, showing relatively uniform distribution of swapping across the entire lane and both surfaces. b Read counts for all 36 index combinations in a 6-plex pool of uniquely dual indexed libraries. The combinations in heavy bordered cells with blue text along the diagonal are the correct index combinations; read counts for all other combinations are due to index swapping. Note all indexes participate in swapping relatively equally. c Mean insert size (bp) and percent chimerism calculated by Picard for both swapped and non-swapped reads. Swapped reads have shorter inserts and higher rates of chimeric read pairs. d Normalized human coverage across GC content bins, indicating there are less high GC reads in the swapped population (blue) compared to non-swapped (red) and all other non-demultiplexed (green) populationsCC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 16

  1. Illumina, Inc. Illumina HiSeqX series specification sheet. 2017. https://www.illumina.com/content/dam/illumina-marketing/documents/products/datasheets/datasheet-hiseq-x-ten.pdf . Accessed 15 Nov 2017.
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  4. Illumina, Inc. Effects of index Misassignment on multiplexing and downstream analysis. 2017. https://www.illumina.com/content/dam/illumina-marketing/documents/products/whitepapers/index-hopping-white-paper-770-2017-004.pdf?linkId=36607862 . Accessed 15 Nov 2017.
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Metadata

Authors
Costello, M., Fleharty, M., Abreu, J., Farjoun, Y., Ferriera, S., Holmes, L., Granger, B., Green, L., Howd, T., Mason, T., Vicente, G., Dasilva, M., Brodeur, W., DeSmet, T., Dodge, S., Lennon, N. J., & Gabriel, S.
ORCID
Costello, Maura
Venue
BMC Genomics
Publisher
Springer Science and Business Media LLC
Published
2018-05-08
Volume
19
Issue
1
ISSN
1471-2164
DOI
10.1186/s12864-018-4703-0
PMC
PMC5941783
Cited by
260
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (tdm)
Funders
Center for Common Disease (UM1HG008895)

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