Inferring short-range linkage information from sequencing chromatograms

PLoS One. 2013 Dec 20;8(12):e81687. doi: 10.1371/journal.pone.0081687. eCollection 2013.

Abstract

Direct Sanger sequencing of viral genome populations yields multiple ambiguous sequence positions. It is not straightforward to derive linkage information from sequencing chromatograms, which in turn hampers the correct interpretation of the sequence data. We present a method for determining the variants existing in a viral quasispecies in the case of two nearby ambiguous sequence positions by exploiting the effect of sequence context-dependent incorporation of dideoxynucleotides. The computational model was trained on data from sequencing chromatograms of clonal variants and was evaluated on two test sets of in vitro mixtures. The approach achieved high accuracies in identifying the mixture components of 97.4% on a test set in which the positions to be analyzed are only one base apart from each other, and of 84.5% on a test set in which the ambiguous positions are separated by three bases. In silico experiments suggest two major limitations of our approach in terms of accuracy. First, due to a basic limitation of Sanger sequencing, it is not possible to reliably detect minor variants with a relative frequency of no more than 10%. Second, the model cannot distinguish between mixtures of two or four clonal variants, if one of two sets of linear constraints is fulfilled. Furthermore, the approach requires repetitive sequencing of all variants that might be present in the mixture to be analyzed. Nevertheless, the effectiveness of our method on the two in vitro test sets shows that short-range linkage information of two ambiguous sequence positions can be inferred from Sanger sequencing chromatograms without any further assumptions on the mixture composition. Additionally, our model provides new insights into the established and widely used Sanger sequencing technology. The source code of our method is made available at http://bioinf.mpi-inf.mpg.de/publications/beggel/linkageinformation.zip.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Genetic Linkage*
  • Hepatitis B virus / genetics
  • Reproducibility of Results
  • Sequence Analysis, DNA*

Grants and funding

The work of BB was supported by the German Centre for Infection Research (grant no. 8000 802-3). The work of MNF was supported by the German Bundesministerium für Bildung und Forschung (grant no. BMBF01ES0822). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.