Phytophthora infestans, the cause of potato late blight, is infamous for having triggered the Irish Great Famine in the 1840s. Until the late 1970s, P. infestans diversity outside of its Mexican center of origin was low, and one scenario held that a single strain, US-1, had dominated the global population for 150 years; this was later challenged based on DNA analysis of historical herbarium specimens. We have compared the genomes of 11 herbarium and 15 modern strains. We conclude that the 19th century epidemic was caused by a unique genotype, HERB-1, that persisted for over 50 years. HERB-1 is distinct from all examined modern strains, but it is a close relative of US-1, which replaced it outside of Mexico in the 20th century. We propose that HERB-1 and US-1 emerged from a metapopulation that was established in the early 1800s outside of the species' center of diversity.DOI: http://dx.doi.org/10.7554/eLife.00731.001

BackgroundIntraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly - without measuring DNA content - from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats.ResultsWe demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker’s yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log- likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies.ConclusionsnQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2128-z) contains supplementary material, which is available to authorized users.

Both plants and animals rely on nucleotide-binding domain and leucine-rich repeat-containing (NB-LRR or NLR) proteins to respond to invading pathogens and activate immune responses. How plant NB-LRR proteins respond to pathogens is poorly understood. We undertook a gain-of-function random mutagenesis screen of the potato NB-LRR immune receptor R3a to study how this protein responds to the effector protein AVR3a from the oomycete pathogen Phytophthora infestans. R3a response can be extended to the stealthy AVR3aEM isoform of the effector while retaining recognition of AVR3aKI. Each one of eight single amino acid mutations is sufficient to expand the R3a response to AVR3aEM and other AVR3a variants. These mutations occur across the R3a protein, from the N terminus to different regions of the LRR domain. Further characterization of these R3a mutants revealed that at least one of them was sensitized, exhibiting a stronger response than the wild-type R3a protein to AVR3aKI. Remarkably, the N336Y mutation, near the R3a nucleotide-binding pocket, conferred response to the effector protein PcAVR3a4 from the vegetable pathogen P. capsici. This work contributes to understanding how NB-LRR receptor specificity can be modulated. Together with knowledge of pathogen effector diversity, this strategy can be exploited to develop synthetic immune receptors.

Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly -without measuring DNA content -from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats.We demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker's yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log-likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies.nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at github.com/clwgg/nQuire under the MIT license. Contact

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