An easy and robust method for isolation and validation of single-nucleotide polymorphic markers from a first Erysiphe alphitoides draft genome

Isolating genetic markers is often costly and time-consuming for non-model fungal species. However, these markers are of primary importance to identify the origin of invasive species and to infer their reproductive mode and dispersal ability. We slightly modified a recent molecular method to quickly isolate and validate single-nucleotide polymorphism (SNP) markers, from a first Erysiphe alphitoides draft genome, one of the main causal agent of oak powdery mildew in Europe. Although the draft assembly was strongly fragmented (555,289 contigs), we successfully isolated 1700 SNPs from 75 single-copy genes conserved in most fungal genomes. Ninety percent of them allowed to clearly distinguish the two main Erysiphe species reported on European oaks: E. alphitoides and E. quercicola. Thirty-six SNPs, located in distinct genes, were then validated using a strategy of MassArray genotyping on 95 E. alphitoides isolates sampled in Europe. This genotyping showed that only monospore isolates had the expected haploid signature, whereas direct genotyping from field leaves showed signature of mixed infection. Considering haploid isolates, these markers led to the first results of population genetic diversity, and suggested that E. quercicola may have a more asexual reproduction than its sister species, E. alphitoides.


Introduction
Invasive fungal species represent a great threat for ecosystems, especially for forests (Gladieux et al. 2015;Desprez-Loustau et al. 2016). In the recent decades, a dramatic increase of emerging diseases, mostly caused by introductions of exotic pathogens, has been reported in forests worldwide, causing severe damage (Santini et al. 2013;Gross et al. 2014;Wingfield et al. 2017). One of the first crucial steps for risk management is the accurate taxonomic identification of the fungal species associated with the disease, since many emerging pathogens were unknown before their invasion (e.g., Gross et al. 2014). Taxonomic identification has been greatly simplified by the development of molecular markers, and especially the use of the nuclear ribosomal internal transcribed spacer (ITS), defined as the fungal taxonomic barcode (Schoch et al. 2012). However, additional genetic markers are sometimes required to accurately resolve more difficult species complexes (e.g., Feau et al. 2011;Queloz et al. 2011;Tsykun et al. 2013). A second step is the identification Section Editor: Marco Thines Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11557-020-01580-w) contains supplementary material, which is available to authorized users. of the geographic origin of the emergent pathogen, assessment of its genetic diversity, and reproduction regime (sexual/asexual) allowing to retrace the history of introduction, and to determine its adaptive potential in introduced areas (Gladieux et al. 2015). Identifying the geographic origin can be useful to find sources of natural regulation in native areas (for example, genetic resistance of host species or occurrence of natural enemies), in view of their putative deployment in the introduced areas (e.g., Rouxel et al. 2013).
Traditionally, microsatellite loci, also called single sequence repeats (SSR), have been widely used for phylogeographic and population genetic studies (Selkoe and Toonen 2006). However, these markers may sometimes be difficult to isolate, especially in fungi (Dutech et al. 2007). In addition, routine genotyping with SSR may be costly because it needs inter-calibration of alleles between studies, taking into account stutter bands and the presence of null alleles (Ellis et al. 2011;Chapuis and Estoup 2007). Due to an unclear mutational model and potential homoplasy between some alleles (Estoup et al. 2002), it might also be difficult, in some cases, to infer a robust phylogeographic signal (but see Hardy et al. 2003). The recent advent of next-generation sequencing (NGS) has made possible the identification of thousands of singlenucleotide polymorphisms (SNP) in non-model species, helping in deciphering their genetic diversity, reproductive regime, and evolutionary history (e.g., Elshire et al. 2011). Given the availability of these new tools and their ever decreasing costs, pathologists might be tempted to design population genetic studies of organisms without any previous knowledge of the reproduction biology and dissemination strategy of the organism. However, regardless of marker choice, an adequate sampling strategy and experimental design remain crucial in order to be able to answer basic population genetic questions (e.g., Arnaud-Haond et al. 2007;Meirmans 2015). Testing population genetic hypotheses may require in some cases taking into account spatial genetic structures to avoid coming to wrong conclusions (e.g., Meirmans 2012). The first step requires performing a pilot study by sampling several individuals; this can be done either with a random sampling or by using a hierarchical approach based on the spatial distribution of populations and their respective density (Arnaud-Haond et al. 2007;Barrès et al. 2012). However, when using NGS technology, this first study could represent a substantial waste of time and money, especially for clonal populations with many identical genotypes. By contrast, several studies have shown that genotyping a few SNPs, especially in fungal populations, may be sufficient for this first objective (e.g., Dutech et al. 2017;Tsykun et al. 2017). In addition, these SNPs may be quickly isolated using an easy, cheap, and robust strategy targeting conserved sets of single-copy genes in a chosen taxonomic group (e.g., Feau et al. 2011;Tonnabel et al. 2014;Dutech et al. 2016). A significant advantage of this strategy is that it can be easily applied for a large panel of fungal species ) and does not require bioinformatic expertise to deal with false positive SNPs generated by NGS, and associated with bias in computational analysis (e.g., Puritz et al. 2014;Ribeiro et al. 2015;Verdu et al. 2016).
Herein, we focused on the oak powdery mildew (OPM). This foliar disease affecting a large range of oak species in the northern hemisphere is caused by various species in several genera, especially Erysiphe (Takamatsu et al. 2007). In Europe, the disease suddenly appeared in the early twentieth century and was thought to be caused by a previously unknown Erysiphe species described as E. alphitoides (Griffon and Maublanc 1912). Recent studies have determined that OPM in Europe is actually caused by a complex of three Erysiphe species: E. alphitoides, the most abundant and widely spread, E. quercicola, and E. hypophylla (Mougou et al. 2008;Desprez-Loustau et al. 2018). These three species belong to a clade of at least five sister species all affecting oaks and present in Asia, suggesting an Asian origin of the species causing OPM in Europe (Desprez-Loustau et al. 2011;Takamatsu et al. 2007Takamatsu et al. , 2015. Today, the disease is widespread in Europe but its impact has strongly decreased since its emergence, although it can still cause high mortalities on young seedlings in forests. Therefore, it may act as an important selective agent for oak populations at this early stage (Marçais and Desprez-Loustau 2014). Numerous questions remain to be investigated about this species complex such as the ecological niche differentiation of the species (Feau et al. 2012;Desprez-Loustau et al. 2018), their reproductive mode and winter survival (Feau et al. 2012;Hamelin et al. 2016), dispersal ability, or their history of introduction.
Only a few genetic markers are available for E. alphitoides and related species . They have been useful at the inter-specific level to describe the host range (Desprez-Loustau et al. 2017) and spatial distribution at different scales of the cryptic species (Desprez-Loustau et al. 2018). The objective of the present study was to develop genetic resources for population genetic analyses of OPM species by developing a pipeline allowing the detection of SNPs in a conserved set of single-copy genes in fungal species, based on the principle described in Feau et al. (2011Feau et al. ( , 2018 with additional steps for species diversity analysis. The method presented here only requires basic bioinformatic analyses and public genetic resources. It can be applied to any fungal species by any research group even without strong expertise in genomics and bioinformatics. The preliminary population genetic analyses performed in this study confirmed that a first characterization of the population genetic structure and diversity of a non-model organism can be quickly estimated with the isolated SNPs, and provided useful guidelines of sampling for future genomic studies of the OPM European populations.

Materials and methods
Fungal isolation, DNA extraction, and genome sequencing Fungal DNA for genome sequencing was obtained from conidia of the E. alphitoides monospore MS_42D strain, initially isolated from a leaf lesion of a young oak seedling (Quercus robur) in south-western France (44.76 N; 0.71 W) in June 2013. To obtain sufficient quantities of spores, oak seedlings were inoculated with the MS_42D strain and incubated in a growth chamber in plastic boxes. DNA was extracted using a CTAB method following Mougou et al. (2008), after grinding the spores in liquid nitrogen. Species identification was performed following ITS sequencing. Shotgun pairedend sequencing of genomic DNA was performed on the Illumina Hiseq2000 genome analyzer, using the TruSeq Genomic kit (Illumina Inc., USA) at the Genotoul facilities (Institut national de la recherche agronomique, Toulouse, France).

Trimming, assembly, and genome annotation
Quality of the Illumina paired-end reads was assessed using FastQC 0.10.0 (Andrews 2010). Reads were then trimmed and assembled into a draft genome using CLC Genomics Workbench 7.0.3 with the de novo assembler tool (CLC bio, Aarhus, Denmark) using default parameters. CD-HIT-est V4.6.0 (Fu et al. 2012) was used to remove redundancy in the contigs with the sequence identity threshold set to 95%. To remove possible oak sequence contamination, contigs were aligned against the oak transcriptome assembly OCV3 (Lesur et al. 2015). In addition, given the large number of contigs following the first assembly, we suspected microbiological contamination led to chimeric contigs (see "Results"). We thus decided to perform a two-steps supplementary filtering: first, we selected E. alphitoides contigs longer than 10Kb; then, we kept only those with a sufficient protein homology with the 6843 scaffolds of Blumeria graminis genome assembly V3 (available on https://mycocosm.jgi.doe.gov/Blugr1/Blugr1. home.html). This cereal powdery mildew genome assembly represents one of the most complete reference genomes among those sequenced for powdery mildew species (Spanu et al. 2010). The filtered set of E. alphitoides contigs was aligned against the Blumeria graminis reference genome using BlastN (Altschul et al. 1990) with an E-value cutoff of 1E−5. Gene prediction was performed on this final set of contigs using Augustus V2.6.1 (Stanke et al. 2006), trained with the Botrytis cinerea genome (Amselem et al. 2011). Genes identified by Augustus were finally validated by comparison of their nucleotidic sequences with the 6470 B. graminis proteins using BlastX (Altschul et al. 1990) with an E-value cutoff of 1E−5.

Identification of single-copy genes and primer design
For SNP identification, we used candidate genes of the Funybase database (Marthey et al. 2008) which contains 246 reliable orthologous gene clusters present as single-copy genes in 21 fungal genomes. Since Sclerotinia sclerotiorum is the closest species relative to Erysiphe sp. in Funybase (http://genome.jouy.inra.fr/funybase/), we extracted all protein sequences of this species and searched them in the E. alphitoides contigs using TblastN (Altschul et al. 1990) with an E-value cutoff of 1E−20. All sequences with more than one hit in the E. alphitoides draft genome were rejected from subsequent analyses. We then checked whether these isolated nucleotidic sequences matched with the nucleotidic sequences of predicted genes obtained from Augustus, using BlastN and an E-value cutoff of 1E−20. Oligonucleotidic primers were then designed from selected candidate genes such that fragments of 300-450 bp are amplified and that each future amplified sequence (hereafter called amplicon) contained at least one intron (assuming that introns have a higher rate of polymorphism than exons; Feau et al. 2011). Primer3 (Untergasser et al. 2012) was used for primer design using the default parameters. Figure 1 describes the different steps of the workflow analysis to isolate SNPs from the E. alphitoides draft genome.

Gene sequencing and SNP identification
A total of 47 monospore E. alphitoides and E. quercicola isolates were obtained from lesions on oak and mango leaves sampled in five European countries, by sub-culturing the monospore isolates on excised oak leaves in Petri dishes (Table 1). Each leaf inoculated with a single spore was desiccated and stored at INRAE-Pierroton. High molecular weight genomic DNA was extracted from these spores according to the protocol of Feehan et al. (2017). DNA was amplified using Targeted DNA Seq Library Reagent Kits (Fluidigm, San Francisco, USA) on an Access Array 48.48 IFC, following manufacturer's instructions. For each sample, two primer pairs were mixed together in the PCR reaction after the identification of the best combination among all the designed primer pairs of amplicons, using MultiPLX (Kaplinski et al. 2005). The quality and quantity of the final library were measured on a Bioanalyzer 2100 using High Sensitivity DNA kit (Agilent Technologies, Santa Clara, USA), and the final pool was diluted to 18 pM before sequencing on Ion Torrent PGM (Thermo Fisher Scientific, Waltham, USA). Ion Torrent sequencing data were analyzed to identify SNPs using two custom Python (V 2.7.6) scripts. Using the first script, Ion Torrent reads of each isolate were grouped into different amplicons and then aligned to the corresponding reference sequences (i.e., the sequences extracted from the E. alphitoides draft genome) using MUSCLE (Edgar 2004). The second Python script was used to (i) build a consensus sequence for each amplicon, (ii) remove short indels which are often produced by the Ion Torrent sequencing technology (Loman et al. 2012), and (iii) detect SNPs between the consensus sequences for each isolate and the reference amplicon. These scripts are available on https://doi.org/10.15454/ UGMTBK.

Validation of SNPs and population genetic analyses
Using the MassArray genotyping technology described in Chancerel et al. (2013), we designed two SNP arrays to validate a subset of the SNPs identified with the method described above. First, we selected SNPs following a manual check of the aligned consensus sequences for each amplicon, and removal of SNPs close to indels. We then selected the best combination of primers for amplification of the highest number of SNPs located in distinct genes, using the MassArray Designer V4.0.20.2. Ninety-five samples of E. alphitoides sampled in Europe were chosen for SNP validation (Table S1), comprising 23 isolates among the 47 monospore isolates previously used to identify SNPs, 48 samples from a previous pan-European study (Desprez-Loustau et al. 2018) (called hereafter "lesion samples"), and 24 herbarium samples of oak powdery mildew from distinct European herbaria (called hereafter "herbarium samples"). For lesion and herbarium samples, a 6-mm infected leaf disc was excised, and DNA extraction was performed according to Desprez-Loustau et al. (2018). After validation of SNPs by MassArray genotyping (i.e., positive amplification and polymorphism), we finally selected a single SNP per gene for population genetic analyses. Genetic diversity and population structure analyses were carried out using the R-CRAN packages PopR (Kamvar et al. 2015) and Adegenet (Jombart and Ahmed 2011). Identical genetic analysis was also performed on the 13 E. quercicola sampled for this study (Table 1), using a subset of SNPs identified by Ion Torrent sequencing technology, each one located in distinct genes.

Results
Assembly and annotation of the Erysiphe alphitoides genome sequence Sequencing of the E. alphitoides strain generated 2 × 184,631,409,100 bp paired-end reads. Average base qualities of the forward and reverse reads were 35.32 and 33.62, respectively, with quality ranging from 31 to 41 (encoding Sanger/Illumina 1.9). Following trimming, 181,631,409 paired-end reads were de novo-assembled. A total of 592,884 contigs were obtained (N50 = 1646 bp, average length = 532 bp, total length = 315,529,701 bp; Table 2). Redundancy among contigs was removed using CD-HIT-est leading to a total of 555,289 contigs, with N50 = 1735 bp, contig length varying from 100 to 51,517 bp, a mean length of 532 bp, and a total genome size higher than 300 Mb (Table 2). A total of 3088 contigs were removed due to sequence similarities with the oak genome or transcriptome. By similarity with B. graminis scaffolds (using a threshold of the Blast E-value = 10E−5), we identified 951 E. alphitoides contigs longer than 10 kb. These 951 contigs added up to a length of 15,296,844 bp, and a N50 equals to 16,172 bp. Using these contigs, gene annotation resulted in 3045 gene models with a minimum and maximum length of 198 and 14,751 bp, respectively, and an average gene length of 1624 bp (Table 2). Ninety-eight percent of these gene models (i.e., 3039 out of 3045) were validated by comparison with the 6470 B. graminis proteins. Assembly and annotation data are available on https://arachne.pierroton.inra.fr/AlphiGeno/ Identification of single-copy genes in the draft E. alphitoides genome and selection of sequences for amplification TBlastN searches of 246 S. sclerotiorum protein sequences against the 951 E. alphitoides contigs longer than 10 kb revealed a total of 147 (59.8%) S. sclerotiorum genes with a homolog in these contigs, among which 103 showed one single hit (Table S2). From this reduced list, we then selected 95 sequences homolog (BlastN E-value > 1E−50) to one of the automatically annotated genes of the E. alphitoides draft genome. Finally, using Primer3, we successfully designed 192 pairs of primers allowing the amplification of amplicons with a sequence size between 306 and 425 bp (Table S3).

Gene sequencing and SNP identification
Out of the 192 primer pairs tested on the 47 monospore Erysiphe isolates (E. alphitoides and E. quercicola), 165 pairs, targeting 79 distinct genes, produced amplicons (Table S3). We investigated the causes of failure of amplification by estimating phylogenetic relationships of the reference amplicons using PhyML 3.1 (Guindon et al. 2010), orthologs from the 21 complete genomes present in Funybase, and protein sequences from the B. graminis genome V3. Despite of our choice to only select the 10 kb contigs homolog to Blumeria for limiting DNA amplification associated with putative DNA contamination from other microorganisms or host plants, we found that 11 reference amplicons isolated from the E. alphitoides draft genome were related to Aspergillus sp. (Fig. S1). Our custom Python script detected 1794 SNPs in the 165 amplified sequences. These SNPs were located in 139 amplicons, corresponding to 79 distinct genes (Table S4). The median and maximum number of SNPs detected per amplicon was equal to 9 and 29, respectively. After filtering for putative spurious SNPs (i.e., not considering those located 30 bp before the 3′-end and after 5′-end of the alignment), we identified 203 intraspecific SNPs located in 53 genes for E. alphitoides, and 338 SNPs in 41 genes for E. quercicola. Among those, 22 SNPs were shared by the two species. For SNP validation in E. alphitoides, we selected a total of 58 SNPs within 38 distinct genes and grouped in two SNP arrays (Table 3). A set of 54 SNPs were polymorphic among the 23 monospore isolates (Table 3). The comparison between genotypes obtained by the Ion Torrent sequencing and the MassArray genotyping technology only revealed six discrepancies in the 23 control isolates, corresponding to an error rate of 0.0048. Most of these differences were concentrated on the isolate AG320. This isolate was probably not a monospore haploid isolate since several heterozygote SNPs were detected using the MassArray genotyping analysis. Most of monospore isolates (95%) had less than three missing data, whereas 93% of the lesion and herbarium samples had more than five missing data (mean 11.8 and 33.1 per isolate for leaf and herbarium samplings, respectively; Fig. 2). In addition, nearly all the lesions sampled from the field were diploid with at least one heterozygote SNP identified (Table S1), indicating that these lesions were likely a mix of (at least) two distinct haploid genotypes. It was therefore not possible to identify haplotypes and to estimate allelic frequencies and genetic diversity in these two samplings. Out of the 58 SNPs genotyped by MassArray, we finally selected 36 SNPs from 36 distinct genes to remove the effect of physically linked SNPs within genes, for population genetic analysis (Table 3). Based on this subset of SNPs, we inferred no repeated genotype among the 34 E. alphitoides monospore isolates analyzed by the Ion Torrent sequencing. The average genetic diversity estimated in this sample was 0.37 (SD = 0.15), and the standardized index of association (rD), measuring the multilocus linkage disequilibrium (Agapow and Burt 2001) was 0.027, not significantly different from zero (P value = 0.002). For E. quercicola, using a subset of 33 SNPs located in 33 genes detected in the 13 monospore isolates chosen for the SNP identification, we found two isolates with the same genotype and two pairs of genotypes distinct by a single SNP. We estimated a genetic diversity of 0.24 (SD = 0.09) and rD equals to 0.11, significantly different from zero (P value < 0.01).

Discussion
This study showed that reliable genetic markers can be quickly isolated from genomes hard to assemble such as those of Erysiphales (Spanu et al. 2010;Frantzeskakis et al. 2018). As obligate biotrophs non-culturable on axenic media, these fungi are also more likely to be contaminated by an unknown source of microorganisms since they are maintained on plant material. The method developed here allows to deal simply and efficiently with contamination by selecting sequences phylogenetically close to the target species. However, the Evalue cutoff should be carefully tested in case of close proximity between target and putative contaminant species. As illustrated in our study, the choice of a relaxed E-value threshold for TBlastN (i.e., 10E−20) finally selected a few sequences unrelated to our target species. Most of the nonamplified sequences were associated to Aspergillus sp., likely present on the oak leaves from which E. alphitoides was sampled (Unterseher et al. 2007). The phylogenetic analysis, such as presented in our study, should be performed before the final choice of candidate regions to better remove genes from contaminating taxa. Our method may also be applied to any other fungus since genomic resources can easily be generated today using high-throughput sequencing. Moreover, gene databases are available for several phyla (Grigoriev et al. 2014).
Our approach may provide an alternative to the RAD-Seq method since, on one hand, it does not require complex laboratory protocols (Harvey et al. 2016) and, on the other hand, it allows to easily control both the phylogenetic origin and duplications of the targeted sequences. The choice of focusing on a set of conserved genes, generally present in single copy in most fungal genomes, should prevent the risk of amplifying paralogs, reducing errors in estimation of allelic frequencies (Gayral et al. 2013). Controlling for gene duplicates with our method is dependent on the selected threshold for the Blast Table 2 Basic statistics of the Erysiphe alphitoides genome assembly, contigs ≥ 10 kb: contigs longer than 10 kb homologs to Blumeria graminis contigs (Blast E-value less than 1E−5). Genes were detected with Augustus annotation software V2.6.1 using B. graminis as gene model analysis (see, for example, Feau et al. 2011) and quality of the genome assembly. However, the results obtained from the MassArray genotyping showed no evidence of copy number variations for the chosen SNP (data not shown), and especially, we detected heterozygote SNPs for only one of the 23 monospore haploid isolates used as controls, consistent with absence of duplication of the chosen genes. Although it is likely that large parts of the E. alphitoides genome, especially regions of low complexity, have probably not been accurately assembled (Frantzeskakis et al. 2018), our results suggest that our targeted single-copy genes are frequently located in the easiest regions to assemble, greatly helping their isolation in draft genomes. In addition, we showed that a small quantity of DNA (which is usually what is obtained for obligate fungal biotrophs, like OPM) is not a limitation for the isolation of these targeted markers by using this method. This method might further be improved by increasing the depth of sequencing, by using long-read sequencing technologies which would allow better assembly of full genomes (Faino et al. 2015). Using additional gene databases to identify conserved genes such as OrthoMCL-DB (Li et al. 2003) might also allow to increase the number of targeted genes. Nevertheless, even a limited number of SNPs (i.e., around 40, such as obtained in this study) may allow to get a first insight on population genetic structure (e.g., Dutech et al. 2017;Tsykun et al. 2017). The study published by Tsykun et al. (2017) showed no major difference in population structure characterized with SSR or SNP markers. DNA amplification using the Fluidigm methodology made it possible to obtain numerous SNPs for a preliminary population genetic study in E. alphitoides, and its sister species E. quercicola. A limitation of our study was due to the use of the Ion Torrent sequencing methodology which generates a large number of spurious indels linked to homopolymers (Loman et al. 2012). Our in-house script designed to remove these indels from the consensus sequences built for each individual seemed to efficiently solve this problem. Actually, the validation of more than 90% of the selected SNPs following MassArray genotyping confirmed that our method is robust. In addition, 72% of the detected SNPs are fixed in each species, as expected in absence of recent gene flow between the two Erysiphe species , and support they are not false positive SNPs. By contrast, we also used another method implemented in DiscoSNP (Uricaru et al. 2015) which detected less than 300 SNPs, suggesting that numerous SNPs are missed relative to our method of SNP calling. Additional tests should be performed to define the best set of parameters of DiscoSNP on such sequence data with a large presence of indels generated by Ion Torrent sequencing, but these results suggest that this automatic method of SNP calling is unadapted to these sequence data.
Using 33 to 36 SNPs located in different genes, we could perform a preliminary population genetic study for the two main OPM species introduced in Europe. The genotyping of 36 SNPs with the MassArray genotyping in 34 E. alphitoides isolates from five regions in Europe detected no repeated genotypes and absence of significant linkage disequilibrium between SNPs suggesting frequent sexual crossing and gene flow among populations. By contrast, in E. quercicola, several isolates had the same or a very close genotype and a significant deviation from zero was obtained for the standardized index of association. Although these results were obtained on a limited sampling, these findings are consistent with biological observations suggesting the quasi-absence of sexual reproduction in E. quercicola, which overwinters as mycelium and conidia in buds (Feau et al. 2012). The sister species E. alphitoides does sexual reproduction and differentiates chasmothecia, the sexual reproductive structures that also act as resistant structures (Feau et al. 2012). These first results should be further confirmed by a genetic analysis on a more thorough sampling at both local and regional geographical scales by using the SNPs isolated in this study. Our results on the lesions sampled directly on naturally infected oak leaves without monospore isolation also showed that field colonies of OPM often result from mixed infections of at least two distinct genotypes. A similar finding was reported for the Plantago powdery mildew (Tollenaere et al. 2012), whereas in a study performed on E. necator, the causal agent of powdery mildew on grapevines, only one genotype was generally detected in field lesions (Kisselstein et al. 2018). It would be interesting to further investigate whether these findings reveal differences in pathogen genetic structure between natural ecosystems and crops, with strong directional pressures in the latter maybe associated with lower diversity in powdery mildew populations. Our generic method could make it possible to study a wider range of powdery mildew species. From a practical point of view, the finding of mixed infections may hamper any population genetic study requiring the estimate of allele frequencies without prior monospore isolation and subculturing, which is a delicate and time-consuming step. This difficulty might be circumvented by an early sampling in the vegetative season when single colonies, putatively resulting from a single spore infection, are still clearly distinguishable.