A bstract: Genome evolution is driven by the activity of transposable elements (TEs). The spread of TEs can have deleterious effects including the destabilization of genome integrity and expansions. However, the precise triggers of genome expansions remain poorly understood because genome size evolution is typically investigated only among deeply divergent lineages. Here, we use a large population genomics dataset of 284 individuals from populations across the globe of Zymoseptoria tritici , a major fungal wheat pathogen. We built a robust map of genome-wide TE insertions and deletions to track a total of 2,456 polymorphic loci within the species. We show that purifying selection substantially depressed TE frequencies in most populations but some rare TEs have recently risen in frequency and likely confer benefits. We found that specific TE families have undergone a substantial genome-wide expansion from the pathogen’s center of origin to more recently founded populations. The most dramatic increase in TE insertions occurred between a pair of North American populations collected in the same field at an interval of 25 years. We find that both genome-wide counts of TE insertions and genome size have increased with colonization bottlenecks. Hence, the demographic history likely played a major role in shaping genome evolution within the species. We show that both the activation of specific TEs and relaxed purifying selection underpin this incipient expansion of the genome. Our study establishes a model to recapitulate TE-driven genome evolution over deeper evolutionary timescales.

Variety testing systems in Europe do not account for cannabis varieties selected specifically for flower and cannabinoid production. These “flower varieties” are morphologically distinct from industrial varieties, with significant implications for agronomic characterization in the Value for Cultivation and Use (VCU) testing system. However, they are not considered as drug-type varieties due to their low Δ⁹-tetrahydrocannabinol (Δ⁹-THC) content. Identifying specific traits that can objectively describe these varieties is integral to establishing stable and high-quality production standards. We evaluated specific traits tailored to the VCU testing of flower varieties in two field trials. The assessed phenological traits showed significant differences between varieties (p < 0.0001) for all traits except ease of harvest (EH) and lodging, with significant differences also found in all yield-related traits. The number of branches per plant (NBP), flower and leaf yield (FLY), harvest index (HI) and raceme compactness index (RCI) could therefore be considered for VCU testing. The varieties differed significantly in their cannabinoid content, with all falling below the THC limit under Swiss regulation (1%) but not all meeting the 0.3% limit set by European countries. Variations in THC content were dependent on the testing year, the timing of sampling and the number of plants sampled, underscoring the need to clarify VCU testing methodologies. Incorporating cannabinoid content along with morphological and phenological traits is crucial in introducing a new “flower” category within the VCU system for cannabis.

Wheat and maize productivity gains depend on accurate estimates of genetic trends, genotypic effects (G), and genotype-by-environment interactions (GEI). Here, we compiled a unique European Value for Cultivation and Use (VCU) database for wheat and maize (2003–2018) to estimate genetic trends, G and GEI magnitudes, and variety-testing precision in grain yield using mixed-model methodology. We found that G and GEI variances were comparable across Europe, with variety-comparison precisions of 0.29–0.56 t ha^-1 (wheat) and 0.38–0.81 t ha^-1 (maize). Genetic trends ranged from 0.45% to 1.81% yr^-1 (wheat) and 0.90% to 1.31% yr^-1 (maize). Stronger GEI corresponded with larger genetic trends in maize yield, while GEI magnitude provided an upper bound for the wheat genetic trend. Current European VCU networks are well-optimized for location numbers given national testing periods of 2–3 years. Connecting national VCU systems can increase precision, with further improvements from genotypic and environmental characterizations.