Waterman, R. | bioRxiv Science

bioRxiv2025

Seed vernalization and gibberellic acid interact to affect life cycle type in facultative winter annual Canadian horseweed (Erigeron canadensis)

Background and AimsPlants display enormous variation in the phenological traits that make up their life cycle both within and between populations. Facultative winter annual species are particularly interesting because they can adopt either a fall-emerging/spring-flowering or spring-emerging/summer-flowering life cycle at the population level via evolution or at the individual level via within-generation and transgenerational plasticity. Responses of phenological traits to the environment have often been found to be mediated by changes in hormone levels, especially the growth hormone gibberellic acid (GA). MethodsWe conducted growth chamber and greenhouse experiments using the facultative winter annual agricultural weed Erigeron canadensis (horseweed) to investigate the interactive effects of genetic variation; parent plant life cycle; and plastic responses to temperature, light, and GA treatments. Key ResultsWe found that contrary to a prior report, exposing imbibed seeds to 3-4 weeks of cold (i.e., seed vernalization) does not always result in summer annual type growth, with considerable variation found among field-collected seeds from 10 populations. Further, we found that seed vernalization and exogenous application of GA both tended to increase summer annual characteristics, interacting in ways that were largely consistent with the hypothesis that GA is a mechanism for cold-induced life cycle differentiation. Light treatment did not significantly affect life cycle traits, while parent life cycle type had marginal effects on offspring life cycle type. Finally, genetic variation among and within sites explained far less of the variation in life cycle traits than the plastic responses to seed vernalization and GA treatments. ConclusionsOur study proposes that the seasonality of this harmful agricultural weed is influenced by a GA-mediated response to vernalization of seeds during winter, yet highlights the need for further study, given the variability in this response.

plant biology↗

bioRxiv2023

A data-driven evaluation of Arabidopsis-centric research and the model species concept

The selection of Arabidopsis as a model organism played a pivotal role in advancing genomic science, firmly establishing the cornerstone of today s plant molecular biology. Competing frameworks to select an agricultural- or ecological-based model species, or to decentralize plant science and study a multitude of diverse species, were selected against in favor of building core knowledge in a species that would facilitate genome-enabled research that could assumedly be transferred to other plants. Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plant species. Comparing different machine learning algorithms, models trained and tested on Arabidopsis data achieved near perfect precision and recall values using the K-Nearest Neighbor method, whereas when tissue identity is predicted across the flowering plants using models trained on Arabidopsis data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64, depending on the algorithm used. Below-ground tissue is more predictable than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from Arabidopsis. This suggests that gene expression signatures rather than marker genes are more valuable to create models for tissue and cell type prediction in plants. Our data-driven results highlight that, in hindsight, the assertion that knowledge from Arabidopsis is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data and computational resources, it may be prudent to reevaluate the scientific emphasis on Arabidopsis and to prioritize the exploration of plant diversity.

plant biology↗