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Nucleic Acids Res. 2015 Sep 18;43(16):e105. doi: 10.1093/nar/gkv478. Epub 2015 May 18.

Frequency-based haplotype reconstruction from deep sequencing data of bacterial populations.

Author information

1
Department of Information Technology, Ghent University, iMinds, 9050 Gent, Belgium Department of Microbial and Molecular Systems, Centre of Microbial and Plant Genetics, KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium.
2
Department of Microbial and Molecular Systems, Centre of Microbial and Plant Genetics, KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium Departamento de Ciencias Naturales, Universidad Técnica Particular de Loja, San Cayetano Alto S/N, EC1101608 Loja, Ecuador.
3
Department of Microbial and Molecular Systems, Centre of Microbial and Plant Genetics, KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium.
4
Department of Information Technology, Ghent University, iMinds, 9050 Gent, Belgium.
5
Department of Information Technology, Ghent University, iMinds, 9050 Gent, Belgium Department of Microbial and Molecular Systems, Centre of Microbial and Plant Genetics, KU Leuven, Kasteelpark Arenberg 20, 3001 Leuven, Belgium Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium kathleen.marchal@ugent.be.

Abstract

Clonal populations accumulate mutations over time, resulting in different haplotypes. Deep sequencing of such a population in principle provides information to reconstruct these haplotypes and the frequency at which the haplotypes occur. However, this reconstruction is technically not trivial, especially not in clonal systems with a relatively low mutation frequency. The low number of segregating sites in those systems adds ambiguity to the haplotype phasing and thus obviates the reconstruction of genome-wide haplotypes based on sequence overlap information.Therefore, we present EVORhA, a haplotype reconstruction method that complements phasing information in the non-empty read overlap with the frequency estimations of inferred local haplotypes. As was shown with simulated data, as soon as read lengths and/or mutation rates become restrictive for state-of-the-art methods, the use of this additional frequency information allows EVORhA to still reliably reconstruct genome-wide haplotypes. On real data, we show the applicability of the method in reconstructing the population composition of evolved bacterial populations and in decomposing mixed bacterial infections from clinical samples.

PMID:
25990729
PMCID:
PMC4652744
DOI:
10.1093/nar/gkv478
[Indexed for MEDLINE]
Free PMC Article

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