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On variant discovery in genomes of fungal plant pathogens

MPS-Authors
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Potgieter,  Lizel
Max Planck Fellow Group Environmental Genomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Feurtey,  Alice
Max Planck Fellow Group Environmental Genomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Dutheil,  Julien Y.
Research Group Molecular Systems Evolution, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Stukenbrock,  Eva H.
Max Planck Fellow Group Environmental Genomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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fmicb-11-00626.pdf
(Publisher version), 610KB

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Citation

Potgieter, L., Feurtey, A., Dutheil, J. Y., & Stukenbrock, E. H. (2020). On variant discovery in genomes of fungal plant pathogens. Frontiers in Microbiology, 11: 626. doi:10.3389/fmicb.2020.00626.


Cite as: http://hdl.handle.net/21.11116/0000-0007-8503-F
Abstract
Comparative genome analyses of eukaryotic pathogens including fungi and oomycetes have revealed extensive variability in genome composition and structure. The genomes of individuals from the same population can exhibit different numbers of chromosomes and different organization of chromosomal segments, defining so-called accessory compartments that have been shown to be crucial to pathogenicity in plant-infecting fungi. This high level of structural variation confers a methodological challenge for population genomic analyses. Variant discovery from population sequencing data is typically achieved using established pipelines based on the mapping of short reads to a reference genome. These pipelines have been developed, and extensively used, for eukaryote genomes of both plants and animals, to retrieve single nucleotide polymorphisms and short insertions and deletions. However, they do not permit the inference of large-scale genomic structural variation, as this task typically requires the alignment of complete genome sequences. Here, we compare traditional variant discovery approaches to a pipeline based on de novo genome assembly of short read data followed by whole genome alignment, using simulated data sets with properties mimicking that of fungal pathogen genomes. We show that the latter approach exhibits levels of performance comparable to that of read-mapping based methodologies, when used on sequence data with sufficient coverage. We argue that this approach further allows additional types of genomic diversity to be explored, in particular as long-read third-generation sequencing technologies are becoming increasingly available to generate population genomic data.