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Primer-initiated sequence synthesis to detect and assemble structural variants

Nature Methods volume 7, pages 485–486 (2010)Cite this article

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To evaluate the performance of PrInSeS-G, we simulated paired-end reads from a 1 megabase (Mb) region of human chromosome 21 in which we introduced 500 insertions and deletions (indels) of 5 bp to 10 kb. PrInSeS-G's performance was robust, but the false positive and false negative rates were, as we expected, affected by indel size and by the quality of the alignment profile, which itself is dependent on the read format and the overall coverage (Supplementary Fig. 1 and Supplementary Table 1). Moreover, PrInSeS-G's performance compared favorably with that of the structural variation mapper Breakdancer3 (Supplementary Data and Supplementary Methods) with the important benefit that PrInSeS-G yielded sequence information on the variants.

To evaluate the performance of PrInSeS-G on real data, we used single-ended reads from Salmonella paratyphi A AKU12601. First, we used the AKU12601 genome as reference to detect false positives. PrInSeS-G detected 74 non–single-nucleotide polymorphism (non-SNP) variants. For 54 of these, we did not obtain improved read depth after realigning the reads to the new consensus sequence, indicating that this validation approach is efficient at removing potential false positives. To estimate the true positive rate, we used the genome of a related S. paratyphi strain, ATCC9150, as reference template and found that PrInSeS-G assembled 68% of detectable variants (28 of 41; Supplementary Data, Supplementary Methods and Supplementary Table 2). To enable comparison with Breakdancer on real data, we performed a similar analysis using paired-end reads from Mycobacterium tuberculosis and, consistent with the simulation data, found that PrInSeS-G outperformed BreakDancer in terms of false positive and false negative rates (Supplementary Data, Supplementary Table 3 and Supplementary Methods).

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Figure 1: PrInSeS-G principle and validation.

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Acknowledgements

We thank the members of the Lausanne DNA array facility for performing the Illumina sequencing, N. Gheldof for help with the figures, J. Sacchettini for providing the M. tuberculosis H37Rv-JS read data, and the members of the Deplancke laboratory for critical reading of the manuscript. A substantial part of the data analysis was performed at the Vital-IT Center for high-performance computing of the Swiss Institute of Bioinformatics. This work was supported by funds from the Swiss National Science Foundation, Systems X, a Marie Curie International Reintegration grant (B.D.) and the Seventh Research Framework Programme, and by Institutional support from the Ecole Polytechnique Fédérale de Lausanne.

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Author notes

  1. Andreas Massouras and Korneel Hens: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Andreas Massouras, Korneel Hens, Carine Gubelmann & Bart Deplancke

  2. Global Health Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Swapna Uplekar & Stewart T Cole

  3. Genohm, Zwijnaarde, Belgium

    Frederik Decouttere

  4. School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne, Switzerland

    Jacques Rougemont

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  1. Andreas Massouras
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  2. Korneel Hens
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  8. Bart Deplancke
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Correspondence to Bart Deplancke.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Tables 1–5, Supplementary Data, Supplementary Methods (PDF 666 kb)

Supplementary Table 6

List of all consensus Drosophila melanogaster RAL-304 variants. (XLS 23389 kb)

Supplementary Table 7

List of broad sense heritability values for genes with or without sequence variants. (XLS 1581 kb)

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Massouras, A., Hens, K., Gubelmann, C. et al. Primer-initiated sequence synthesis to detect and assemble structural variants. Nat Methods 7, 485–486 (2010). https://doi.org/10.1038/nmeth.f.308

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