SummaryCrop disease outbreaks are often associated with clonal expansions of single pathogenic lineages. To determine whether similar boom-and-bust scenarios hold for wild pathosystems, we carried out a multi-year, multi-site survey of Pseudomonas in its natural host Arabidopsis thaliana. The most common Pseudomonas lineage corresponded to a ubiquitous pathogenic clade. Sequencing of 1,524 genomes revealed this lineage to have diversified approximately 300,000 years ago, containing dozens of genetically identifiable pathogenic sublineages. There is differentiation at the level of both gene content and disease phenotype, although the differentiation may not provide fitness advantages to specific sublineages. The coexistence of sublineages indicates that in contrast to crop systems, no single strain has been able to overtake the studied A. thaliana populations in the recent past. Our results suggest that selective pressures acting on a plant pathogen in wild hosts are likely to be much more complex than those in agricultural systems.

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, support the acquisition of nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of the 16S rRNA gene and/or the internal transcribed spacer (ITS) of rRNA genomic loci, which show the relative abundance of the microbes to each other. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S and eukaryotic ITS1 rRNA amplicon data from 176 of these samples. Shotgun data, which unlike the amplicon data capture the ratio of microbe to plant DNA, enable scaling of microbial read abundances to reflect the microbial load on the host. In a more cost-effective hybrid strategy, we show they also allow a similar scaling of amplicon data to overcome compositionality problems. Our wild plants were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. Microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. Critically, considering absolute microbial load led to fundamentally different conclusions about microbiome assembly and the interaction networks among major taxa.

A central goal in microbiome research is to learn what distinguishes a healthy from a dysbiotic microbial community. Shifts in diversity and taxonomic composition are important indicators of dysbiosis, but a full understanding also requires knowledge of absolute microbial biomass. Simultaneous information on both microbiome composition and the quantity of its components can provide insight into microbiome function and disease state. Here we use shotgun metagenomics to simultaneously assess microbiome composition and microbial load in the phyllosphere of wild populations of the plant Arabidopsis thaliana. We find that wild plants vary substantially in the load of colonizing microbes, and that high loads are typically associated with the proliferation of single taxa, with only a few putatively pathogenic taxa achieving high abundances in the field. Our results suggest (i) that the inside of a plant leaf is on average sparsely colonized with an estimated two bacterial genomes per plant genome and an order of magnitude fewer eukaryotic microbial genomes, and (ii) that higher levels of microbial biomass often indicate successful colonization by pathogens. Lastly, our results show that load is a significant explanatory variable for loss of estimated Shannon diversity in phyllosphere microbiomes, implying that reduced diversity may be a significant predictor of microbial dysbiosis in a plant leaf.

Repeated herbicide applications exert enormous selection on blackgrass (Alopecurus myosuroides), a major weed in cereal crops of the temperate climate zone including Europe. This inadvertent large-scale experiment gives us the opportunity to look into the underlying genetic mechanisms and evolutionary processes of rapid adaptation, which can occur both through mutations in the direct targets of herbicides and through changes in other, often metabolic, pathways, known as non-target-site resistance. How much either type of adaptation relies on de novo mutations versus pre-existing standing variation is important for developing strategies to manage herbicide resistance. We generated a chromosome-level reference genome for A. myosuroides for population genomic studies of herbicide resistance and genome-wide diversity across Europe in this species. Bulked-segregant analysis evidenced that non-target-site resistance has a complex genetic architecture. Through empirical data and simulations, we showed that, despite its simple genetics, target-site resistance mainly results from standing genetic variation, with only a minor role for de novo mutations.

SummaryCrop disease outbreaks are often associated with clonal expansions of single pathogenic lineages. To determine 20 whether similar boom-and-bust scenarios hold for wild plant pathogens, we carried out a multi-year multi-site 21 survey of Pseudomonas in the natural host Arabidopsis thaliana. The most common Pseudomonas lineage 22 corresponded to a pathogenic clade present in all sites. Sequencing of 1,524 Pseudomonas genomes revealed 23 this lineage to have diversified approximately 300,000 years ago, containing dozens of genetically distinct 24 pathogenic sublineages. These sublineages have expanded in parallel within the same populations and are 25 differentiated both at the level of gene content and disease phenotype. Such coexistence of diverse sublineages 26indicates that in contrast to crop systems, no single strain has been able to overtake these A. thaliana 27 populations in the recent past. Our results suggest that the selective pressures acting on a plant pathogen in 28 wild hosts may be more complex than those in agricultural systems. 29 Introduction 30In agricultural and clinical settings, pathogenic colonizations are frequently associated with expansions of single 31 or a few genetically identical microbial lineages (Butler et al., 2013; Cai et al., 2011;Kolmer, 2005; Park et al., 32 2015;Stukenbrock and McDonald, 2008; Yoshida et al., 2013). The conditions that lead to such epidemics-such 33 as reduced host genetic diversity (Zhu et al., 2000), absence of competing microbial communities (Brown et al., 34 2013) or high transmission rates (Park et al., 2015)-are, however, by no means a universal feature of 35 pathogenic infections. Instead, many, if not most, pathogens can colonize host populations that are both 36 genetically diverse and that can accommodate a diversity of other microbes (Barrett et al., 2009; Falkinham et 37 al., 2015;Woolhouse et al., 2001). 38Factors that drive pathogen success in such more complex situations are less well understood than for 39 clonal epidemics. For example, if a pathogen species persists at high numbers in non-host environments, does 40 each host become infected by a different pathogen strain? Or does a multitude of genetically distinct pathogens 41 infect each host? And do different colonizing strains use disparate mechanisms to become established even 42 within genetically similar host individuals? The answers to these questions inform on how (and if) a host 43 population can evolve partial or even complete pathogen resistance (Anderson and May, 1982; Barrett et al., 44 2009; Karasov et al., 2014a;Laine et al., 2011). Several studies over the past 20 years have attempted to infer 45 the distributions of non-epidemic pathogens in both host and non-host environments (Falkinham et al., 2015; 46 Wiehlmann et al., 2007). These studies, which have observed a range of different patterns, are unfortunately 47 often limited to the historic strains that are available, and the conclusions vary for different collections, even of 48 the same pathogen ...

Species’ responses at the genetic level are key to understanding the long‐term consequences of anthropogenic global change. Herbaria document such responses, and, with contemporary sampling, provide high‐resolution time‐series of plant evolutionary change. Characterizing genetic diversity is straightforward for model species with small genomes and a reference sequence. For nonmodel species—with small or large genomes—diversity is traditionally assessed using restriction‐enzyme‐based sequencing. However, age‐related DNA damage and fragmentation preclude the use of this approach for ancient herbarium DNA. Here, we combine reduced‐representation sequencing and hybridization‐capture to overcome this challenge and efficiently compare contemporary and historical specimens. Specifically, we describe how homemade DNA baits can be produced from reduced‐representation libraries of fresh samples, and used to efficiently enrich historical libraries for the same fraction of the genome to produce compatible sets of sequence data from both types of material. Applying this approach to both Arabidopsis thaliana and the nonmodel plant Cardamine bulbifera, we discovered polymorphisms de novo in an unbiased, reference‐free manner. We show that the recovered genetic variation recapitulates known genetic diversity in A. thaliana, and recovers geographical origin in both species and over time, independent of bait diversity. Hence, our method enables fast, cost‐efficient, large‐scale integration of contemporary and historical specimens for assessment of genome‐wide genetic trends over time, independent of genome size and presence of a reference genome.

Repeated herbicide applications in agricultural fields exert strong selection on weeds such as blackgrass ( Alopecurus myosuroides ), which is a major threat for temperate climate cereal crops. This inadvertent selection pressure provides an opportunity for investigating the underlying genetic mechanisms and evolutionary processes of rapid adaptation, which can occur both through mutations in the direct targets of herbicides and through changes in other, often metabolic, pathways, known as non-target-site resistance. How much target-site resistance (TSR) relies on de novo mutations vs. standing variation is important for developing strategies to manage herbicide resistance. We first generated a chromosome-level reference genome for A. myosuroides for population genomic studies of herbicide resistance and genome-wide diversity across Europe in this species. Next, through empirical data in the form of highly accurate long-read amplicons of alleles encoding acetyl-CoA carboxylase (ACCase) and acetolactate synthase (ALS) variants, we showed that most populations with resistance due to TSR mutations—23 out of 27 and six out of nine populations for ACCase and ALS , respectively—contained at least two TSR haplotypes, indicating that soft sweeps are the norm. Finally, through forward-in-time simulations, we inferred that TSR is likely to mainly result from standing genetic variation, with only a minor role for de novo mutations.

Microorganisms from all domains of life establish associations with plants. Although some harm the plant, others antagonize pathogens or prime the plant immune system, acquire nutrients, tune plant hormone levels, or perform additional services. Most culture-independent plant microbiome research has focused on amplicon sequencing of 16S rDNA and/or the internal transcribed spacer (ITS) of rDNA loci, but the decreasing cost of high-throughput sequencing has made shotgun metagenome sequencing increasingly accessible. Here, we describe shotgun sequencing of 275 wild Arabidopsis thaliana leaf microbiomes from southwest Germany, with additional bacterial 16S rDNA and eukaryotic ITS1 amplicon data from 176 of these samples.The shotgun data were dominated by bacterial sequences, with eukaryotes contributing only a minority of reads. For shotgun and amplicon data, microbial membership showed weak associations with both site of origin and plant genotype, both of which were highly confounded in this dataset. There was large variation among microbiomes, with one extreme comprising samples of low complexity and a high load of microorganisms typical of infected plants, and the other extreme being samples of high complexity and a low microbial load. We use the 1 Regalado et al.Combining sequencing methods in plant metagenomics metagenome data, which captures the ratio of bacterial to plant DNA in leaves of wild plants, to scale the 16S rDNA amplicon data such that they reflect absolute bacterial abundance. We show that this cost-effective hybrid strategy overcomes compositionality problems in amplicon data and leads to fundamentally different conclusions about microbiome community assembly.