Abstract Premise Cuscuta (dodders) consists of ~200 species circumscribed into four subgenera ( Monogynella , Cuscuta , Pachystigma , and Grammica ) and is the only parasitic genus in Convolvulaceae (the morning‐glory family). This group shows a significant diversity in plastid functionality and represents a rare mixotrophic system among parasitic plants. Apart from a few placeholders in broadscale phylogenies, subg. Monogynella had not been extensively examined until a recent molecular systematics study. Despite this effort, a few lineages still remained poorly resolved and some backbone relationships lacked support. Methods To obtain greater resolution and support for the phylogeny alongside studying the effect of hemiparasitism on different organellar genomes, we selected 31 samples, chosen to represent the phylogenetic diversity of each clade, and sequenced them using high‐throughput sequencing. We assembled plastid genomes and retrieved mitochondrial genes and nuclear ribosomal arrays (NRAs) for phylogenomic analyses. Results Plastomes in this subgenus show similar lengths and gene composition and retain the bulk of photosynthesis genes. About 33 mitochondrial genes were recovered from assemblies and are more conserved in comparison to plastid genes. In addition, complete NRAs were also found to be well maintained. The members of subg. Monogynella show no evidence of hybridization. Trees obtained from all three matrices corroborate previously published molecular phylogenies with increased resolution and backbone support across the board. Conclusions These results characterize the state of the organellar genomes and particularly plastomes in subg. Monogynella , bridging the gap in this field of study of Cuscuta and allowing us to compare these patterns across other heterotrophic lineages.
Abstract Premise Taxonomic differentiation of teosinte species ( Zea spp.), the closest relatives of maize ( Z. mays ) is crucial for understanding their distribution, ecology, and evolutionary history. Resolving the taxonomic uncertainties is of scientific interest and has practical implications for biodiversity management, preservation, and utilization. Methods We examined the evolutionary history of Zea based on species representation, improved multilocus phylogenies and estimation of relative times of diversification. Relationships among 379 samples, representing all species of Zea , were inferred from genotyping‐by‐sequencing (GBS) data, morphological, and climatic descriptors. Results Phylogenies from GBS data were congruent, and species and races were identified; multivariate analysis with morphological data and those combining genomic and climatic variables supported the taxonomy and relationships among species. Phylogenetic results showed that Huehuetenango is a sister group to the Mexican annual teosintes, while Zea nicaraguensis is not differentiated from Zea luxurians . The newly discovered populations are distinct from each other and from other Zea species and represent three new entities. Our results reinforce the hypothesis of historical gene introgression events, such as between Zea luxurians and Zea mays subsp. parviglumis . Modern maize originated from Z. mays subsp. parviglumis through a single evolutionary event in northern Guerrero. In the central highlands, maize admixed with what is known as the Chalco race of teosinte, which facilitated its domestication and subsequent adaptation. Conclusions Evidence from multiple independent sources augments previous knowledge of the relationships, origin, and migration of Zea species, supporting a new classification to resolve the taxonomy of this genus.
Abstract Premise The study of the early stages of divergence between populations is crucial to understanding how species and biodiversity originate. Geographic distributions that capture some aspects of the process of divergence, such as those that are markedly U‐shaped, could offer a window to identify systems undergoing incipient speciation, which have traditionally been difficult to identify. Methods We selected Ipomoea microsepala , a species of morning‐glory with a markedly U‐shaped distribution, as a candidate to evaluate potential incipient evolutionary divergence. We used a combination of principal component, phylogenetic, population, and correlation analyses (Mantel tests) of data derived from leaf morphometrics, climatic information, and genome‐wide DNA variation (RADseq) that span the whole species range to assess potential divergence in genomic, climatic, and morphological dimensions. Results We showed that Ipomoea microsepala achieved its current geographic distribution through historical range expansion by successively colonizing adjacent areas in a fashion that is consistent with a stepping‐stone model and isolation by distance. Phylogenetic and population genetic models supported three present leading fronts through which I. microsepala could continue to expand its range and diverge. Plants in these fronts are already genetically distinct, do not exhibit introgression, and use marginally different climate spaces, but lack differences in leaf morphology. Conclusions A geographic perspective continues to be useful to identify and shed light on the process of divergence. Further ecological experimentation with a genomic perspective is necessary to assess the degree to which the differentiation we documented is congruent with early stages of speciation.
Abstract Premise Herbivory induces complex plant defensive responses that may vary depending on the amount and spatial dispersion of damage on the plant; however, of the two variables, damage dispersion has received much less attention. To address this gap, we studied wild cotton ( Gossypium hirsutum ) defensive responses to different herbivory amounts and degrees of dispersion among leaves using the specialist caterpillar Alabama argillacea (Erebidae). Methods Four herbivory treatments differing in the amount and spatial distribution were applied to 4‐month‐old plants: no herbivory (controls), low (two caterpillars: one on each of two leaves), high‐concentrated (four caterpillars: one pair on each of two leaves), and high‐dispersed (four caterpillars: one on each of four leaves). We measured extrafloral nectar (EFN) and phenolics, both resistance‐related traits, and as a proxy for tolerance, regrowth capacity (new leaf biomass post‐herbivory). To differentiate local from systemic induction, we measured EFN and phenolics separately for damaged and undamaged leaves. Results EFN was significantly and more consistently induced in damaged leaves (i.e., stronger local induction) and in response to high‐dispersed damage, but phenolics were unaffected by the treatment. Biomass of new leaves produced post herbivory was similar to that of controls for most treatment groups, except for high‐concentrated damage (lower than controls), suggesting this damage treatment incurred higher costs. Conclusions These results highlight the importance of studying induced plant defenses under various herbivory patterns and suggest that the spatial distribution of within‐plant damage has contrasting effects on resistance‐ (namely EFN) versus tolerance‐related induced responses of importance for wild cotton growth and ant‐plant interactions.
Abstract Vascular wilt pathogens induce xylem blockages that disrupt plant water transport, posing critical threats to agricultural productivity and food security. Key processes including xylem transport, vessel blockage, and pathogen spread within the xylem remain poorly understood, largely due to our limited ability to internally monitor infected tissues. This review explores how complementary mathematical modeling alongside laboratory studies can elucidate features governing these critical processes. I first provide a brief history of xylem imaging and quantification, highlighting technological advances, and persistent limitations. I then review modeling approaches to describe xylem water transport and pathogen dynamics, emphasizing that different pathogens require fundamentally different modeling frameworks. Existing xylem flow models may provide suitable hydraulic conductivity estimates for healthy stems under idealized conditions; however, they lack explicit representation of pit membranes and lumen‐occluding structures, limiting their applicability to diseased stems where these features are actively modified during infection. Previously described biofilm models can replicate bacterial colony growth in controlled experimental settings but are often too complex for integration with flow simulations and rely on parameters that are difficult to quantify experimentally. Finally, I highlight directions and challenges for modeling occlusion and spread at the local scale and discuss how these models might be scaled to network‐level architecture. While these types of models remain computationally challenging, advances in multiscale imaging technologies and scaling approaches promise significant progress in the coming decades. Insights from such models stand to advance both our understanding of disease progression and the development of resilient crops for an uncertain climate future.
