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.

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 ...

The gold standard for studying natural selection is to quantify lifetime fitness in individuals from natural populations that have been grown together under different field conditions. This has been widely done in ecology to measure phenotypic selection in nature for a wide range of organisms -an evolutionary force that seems to be most determined by local precipitation patterns. Studies that include whole-genome data would enable the translation of coefficients of selection to the genetic level, but such studies are still scarce, even though this type of genetic knowledge will be critical to predict the effect of climate change in natural populations. Here we present such an experiment including rainfall-manipulation with the plant Arabidopsis thaliana . The experiment was carried out in a Mediterranean and a Central European field station with rainout shelters to simulate a high and low rainfall treatment within each location. For each treatment combination, we planted 7 pots with one individual and 5 pots with 30 counted seeds of 517 whole-genome sequenced natural accessions covering the global species distribution. Survival, germination, flowering time, and final seed output were measured for ca. 25,000 pots, which contained ca. 14,500 individual plants and over 310,00 plants growing in small populations. This high-throughput phenotyping was only possible thanks to image analysis techniques using custom-made scripts. To make the data and processing code available, we created an R package "dryAR"