De novo reconstruction of microbial haplotypes by integrating statistical and physical linkage

cao, c.; he, j.; mak, l.; Perera, D.; Kwok, D.; Wang, J.; Li, M.; Mourier, T.; Gavriliuc, S.; Greenberg, M.; Morrissy, S.; Sycuro, L.; yang, g.; Jeffares, D. C.; Long, Q.

doi:10.1101/2020.03.29.014704

bioRxiv · 10.1101/2020.03.29.014704

De novo reconstruction of microbial haplotypes by integrating statistical and physical linkage

cao, c.·he, j.·mak, l.·Perera, D.·Kwok, D.·Wang, J.·Li, M.·Mourier, T.·Gavriliuc, S.·Greenberg, M.·Morrissy, S.·Sycuro, L.·yang, g.·Jeffares, D. C.·Long, Q.

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Abstract

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or haplotypes. However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

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cao, c., he, j., mak, l., Perera, D., Kwok, D., Wang, J., Li, M., Mourier, T., Gavriliuc, S., Greenberg, M., Morrissy, S., Sycuro, L., yang, g., Jeffares, D. C., Long, Q.. 2020-03-30. De novo reconstruction of microbial haplotypes by integrating statistical and physical linkage. https://doi.org/10.1101/2020.03.29.014704

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