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Abstract PremiseThe extraction of high‐quality RNA is the critical first step for the analysis of gene expression and gene space. This remains particularly challenging in plants, and especially in ferns, where the disruption of the cell wall and separation of organic compounds from nucleic acids is not trivial. MethodsWe developed a cetyltrimethylammonium bromide (CTAB)‐based RNA extraction protocol that consistently performs well across a large phylogenetic breadth of ferns—a lineage of plants high in secondary compounds—and in an array of tissue types. Two alternative options (precipitation vs. clean‐up without intermediate precipitation) are presented, both of which yield high‐quality RNA extracts with optical density (OD) ratios of OD 260/280 = 1.9–2.1 and OD 260/230 > 1.6, and RNA integrity numbers >7. ConclusionsThis study presents an efficient protocol for the extraction of high‐quality RNA from multiple tissues and across the fern phylogeny, a clade of plants that still lags behind other major lineages in the development of genomic resources. We hope that this method can be used to help facilitate the closing of this gap. 

Abstract PremiseReticulate evolution, often accompanied by polyploidy, is prevalent in plants, and particularly in the ferns. Resolving the resulting non‐bifurcating histories remains a major challenge for plant phylogenetics. Here, we present a phylogenomic investigation into the complex evolutionary history of the vining ferns,Lygodium(Lygodiaceae, Schizaeales). MethodsUsing a targeted enrichment approach with theGoFlag 408flagellate land plant probe set, we generated large nuclear and plastid sequence datasets for nearly all taxa in the genus and constructed the most comprehensive phylogeny of the family to date using concatenated maximum likelihood and coalescence approaches. We integrated this phylogeny with cytological and spore data to explore karyotype evolution and generate hypotheses about the origins of putative polyploids and hybrids. ResultsOur data and analyses support the origins of several putative allopolyploids (e.g.,L. cubense, L. heterodoxum) and hybrids (e.g.,L.×fayae) and also highlight the potential prevalence of autopolyploidy in this clade (e.g.,L. articulatum, L. flexuosum, andL. longifolium). ConclusionsOur robust phylogenetic framework provides valuable insights into dynamic reticulate evolution in this clade and demonstrates the utility of target‐capture data for resolving these complex relationships. 

Summary Climate change is rapidly altering natural habitats and generating complex patterns of environmental stress. Ferns are major components of many forest understories and, given their independent gametophyte generation, may experience unique pressures in emerging temperature and drought regimes. Polyploidy is widespread in ferns and may provide a selective advantage in these rapidly changing environments. This work aimed to understand whether the gametophytes of allopolyploid ferns respond differently to climate‐related physiological stress than their diploid parents.The experimental approach involved a multifactorial design with 27 treatment combinations including exposure to multiple levels of drought and temperature over three treatment durations, with recovery measured at multiple timepoints. We measured Chl fluorescence from over 2000 gametophytes to evaluate stress avoidance and tolerance in diploid and polyploid species.Polyploids generally showed a greater ability to avoid and/or tolerate a range of stress conditions compared with their diploid counterparts, suggesting that polyploidy may confer enhanced flexibility and resilience under climate stress.Overall, these results suggest that polyploidy may provide some resilience to climate change in mixed ploidy populations. However, all species remain susceptible to the impacts of extreme drought and heat stress. 

Abstract Premise The functional annotation of genes is a crucial component of genomic analyses. A common way to summarize functional annotations is with hierarchical gene ontologies, such as the Gene Ontology (GO) Resource. GO includes information about the cellular location, molecular function(s), and products/processes that genes produce or are involved in. For a set of genes, summarizing GO annotations using pre‐defined, higher‐order terms (GO slims) is often desirable in order to characterize the overall function of the data set, and it is impractical to do this manually. Methods and Results The GOgetter pipeline consists of bash and Python scripts. From an input FASTA file of nucleotide gene sequences, it outputs text and image files that list (1) the best hit for each input gene in a set of reference gene models, (2) all GO terms and annotations associated with those hits, and (3) a summary and visualization of GO slim categories for the data set. These output files can be queried further and analyzed statistically, depending on the downstream need(s). Conclusions GO annotations are a widely used “universal language” for describing gene functions and products. GOgetter is a fast and easy‐to‐implement pipeline for obtaining, summarizing, and visualizing GO slim categories associated with a set of genes.