Applications in Plant Sciences

Plant DNA metabarcoding enables the identification of plant taxa in mixed samples, with the trnL (UAA) intron and its P6 loop mini-barcode region performing as well as or better than other commonly used markers. Reliable metabarcoding requires high-quality reference databases, yet a regularly maintained trnL resource is currently lacking. Consequently, most studies use uncurated sequences downloaded directly from public repositories without essential validation. We address these gaps by providing guidance through a systematic comparison of three database curation tools - OBITools3/ecoPCR, RESCRIPt, and MetaCurator - to generate three trnL reference sequence databases and evaluate their classification performance across commonly sequenced trnL regions (CD, CH, and GH). Reference trnL sequences and taxonomy files were retrieved from public sequence repositories and curated using standardized filtering steps to reduce taxonomic errors, sequence ambiguity, and redundancy. Four simulated query datasets--two base sets and their mutated counterparts--were constructed to assess classification performance of the databases using the Naive Bayesian Classifier implemented in DADA2.- The evaluation showed that performance differed by trnL region: MetaCurator and RESCRIPt yielded higher and similar metrics for trnL CD; OBITools3/ecoPCR and RESCRIPt were comparable for trnL CH; and MetaCurator attained the highest performance for trnL GH region. All reference databases, taxonomy, and evaluation files are available at Zenodo (https://doi.org/10.5281/zenodo.17969450). The complete computational workflow and scripts are available on GitHub (https://github.com/oskuddar/trnL_DB). Although evaluation was focused on plant taxa in the United States, the resulting databases are suitable for use as global trnL reference databases.

PremiseHerbarium specimens are increasingly used to extract morphological traits for ecological and evolutionary studies, yet the effects of tissue desiccation on trait measurements remain poorly understood. Here, we tested whether higher tissue water content leads to greater measurement changes after herborization (H1) and whether fresh trait values can be reliably predicted from herbarium measurements (H2). MethodsWe evaluated the reliability of herbarium-based measurements by comparing fresh and dried traits of leaves, flowers, fleshy fruits, and seeds across 262 individuals representing 133 Neotropical Myrtaceae species. Phylogenetic least square models and machine-learning regressions were used to test H1 and H2. ResultsLeaves and flowers generally shrank after herborization, fruits size metrics tended to increase, and seeds were largely unaffected. Water content was significantly associated with the magnitude of herborization effects in flowers and some leaf and seed traits. Fresh trait values were accurately predicted from herbarium measurements. Prediction errors were lowest for leaf traits, followed by fruits, flowers, and seeds. DiscussionThese results partially support H1 and support H2, indicating that herbarium specimens can be reliably used for trait analyses when organ-specific responses are considered, providing a practical framework to account for potential desiccation bias in functional trait research.

Understanding crop genetic diversity is essential for conservation and breeding, yet farmer-maintained germplasm remains largely underrepresented in genomic studies. Theobroma cacao L. has a complex domestication history and extensive global diversity, and cacao currently cultivated in Central America, particularly in Costa Rica, has been understudied compared to South American and Mexican cultivars despite cultural and historical importance. In this study, we investigate the genetic diversity of cacao from farmer-managed systems across Costa Rica to search for Criollo germplasm and identify and characterize any unique local genetic groups. Ninety-four trees were sampled from 17 farms across four regions of the country and sequenced using whole genome resequencing. Farmer materials were analyzed alongside 166 previously characterized reference accessions representing major cacao genetic groups. Population structure analyses, phylogenetic reconstruction, and network approaches revealed that Costa Rican cacao encompasses multiple known genetic groups, including Criollo-derived lineages, while also harboring locally distinct diversity not fully represented in current global reference collections. Analyses revealed close kinship between many accessions with no clear geographic patterns corresponding to the observed population differentiation, reflecting the effects of farmers in creating dominant patterns of gene flow through seed-saving, clonal propagation, and sharing genotypes among farms. Heterozygosity levels varied substantially among individuals, consistent with a mixture of highly inbred Criollo trees and more heterozygous, admixed genotypes. We find that farmer-managed cacao systems are reservoirs of genetic diversity, including possibly rare or historically important lineages, underscoring the value of these farming systems for effective conservation and management of genomic resources for cacao resilience and improvement.

Integrating taxonomic data from various sources presents a significant challenge in the study of biodiversity research, due to non-standardized nomenclature and evolving species classifications. Discrepancies between major repositories like the Global Biodiversity Information Facility (GBIF) and the National Center for Biotechnology Information (NCBI), as well as citizen science platforms such as iNaturalist, lead to fragmented and sometimes inaccurate biological data. We present TaxonMatch, a tool designed to address these challenges. TaxonMatch aligns taxonomic names, resolves synonymy, and corrects typographical and structural inconsistencies across databases. We show how it can be used to build a common backbone arthropod taxonomy over NCBI, GBIF and iNaturalist, to find the closest molecular data to a given fossil, and to identify IUCN endangered species with molecular data. TaxonMatch provides a cohesive taxonomic framework and a consistent taxonomic backbone, and can be applied to any taxonomic source. The tool is available at https://github.com/MoultDB/TaxonMatch.

The combination of target capture sequencing (TCS) with low-coverage whole genome sequencing (lcWGS), an approach known as Hyb-Seq, has allowed the integration of natural history collections into the genomics revolution, transforming biodiversity research. To implement Hyb-Seq, a collection of genomic targets, often nuclear orthologs, is needed to design probes for TCS. In flowering plants, the universal Angiosperms353 probe set has been proven resolutive at multiple evolutionary scales, with caveats. Malpighiales is known to be one of the most challenging flowering plant orders to resolve. Within this order, the clusioid clade ([~]2.2K species, 94 genera, five families) is no exception. To resolve phylogenetic relationships in this recalcitrant clade, we design a custom probe set, the Clusioids626 kit, composed of 39,936 120-mer probes targeting 626 nuclear orthologs ([~]6.6M nucleotides). This probe set includes all Angiosperms353 targets and 273 clusioid-specific ones, carefully chosen taking copy-number, length evenness, and phylo-informativeness into account. We test our probe set on 70 accessions representing all families and tribes in the clusioid clade. On average, 50.4% of TCS reads mapped to our targets, recovering a median of [~]600 orthologs. Relationships for all clusioid families are fully resolved for our nuclear targets. Additionally, 105 plastid coding DNA sequences were retrieved from the lcWGS fraction. A strong cyto-nuclear conflict was detected. The Clusioids626 kit performs better than the universal Angiosperms353 enrichment panel alone. Our kit design workflow can be extended into other lineages for which a universal probe set exists but more resolution is needed.

Genomic imprinting is a rare epigenetic phenomenon in plants and animals, defined by parent-of-origin specific gene expression. Its molecular mechanisms and evolutionary significance remain incompletely understood. In this study, we investigated whether genomic imprinting occurs in Scots pine and, by extension, in other conifers to gain insight into the evolutionary origins of imprinting. We performed reciprocal crosses to assess imprinting in seed embryos and applied a unique approach that used exome-capture data from the haploid, maternally inherited megagametophyte tissue to identify maternal alleles, thereby allowing us to infer paternal alleles in the embryos of the same seeds. Our findings show that maternally inherited haploid megagametophyte tissue offers an effective strategy for resolving parental alleles in offspring while simultaneously removing extensive paralogous variation from the dataset. This framework is broadly applicable to other conifer species and to taxa that possess comparable maternally derived haploid tissues. No evidence of genomic imprinting was detected. Although the limited overlap between the exome-capture and RNA-sequencing datasets and the stringent paralog filtering reduced the amount of analyzable data considerably, the absence of detectable imprinting may also reflect genuinely weak or absent imprinting signals in conifers. We identified several limitations in this preliminary study and outline recommendations for future work to overcome them, and additional research will be necessary to determine whether genomic imprinting occurs in conifers

Understanding evolutionary relationships in hyperdiverse plant groups remains a major challenge in systematics. The orchid genus Bulbophyllum, the second largest genus of flowering plants, represents an exceptional example of phylogenetic and morphological complexity. Relationships, particularly within the species-rich Asian clade, have remained poorly resolved due to extensive morphological variation and limited resolution in previous phylogenetic studies. Here, we reconstructed phylogenetic relationships using 63 plastid genes from 355 specimens representing 322 species and 65 of the 97 recognised sections of Bulbophyllum. Our analyses confirmed that the genus comprises five major evolutionary lineages comprised of species predominantly from Australasia, Madagascar, Continental Africa, Neotropics, and Asia. We provide the first robust phylogenetic evidence for a dichotomous split within the Asian clade into two well-supported lineages: the Asian-Malesian clade and the Malesian-Papuasian clade, with the latter containing a strongly supported Papuasian subclade. Additionally, this study supports the monophyly of several currently recognised sections while clarifying relationships in previously problematic groups. This study provides the most comprehensive plastid-based phylogenomic framework for Bulbophyllum to date and establishes a foundation for future taxonomic revision and integrative analyses of diversification and trait evolution within this hyperdiverse genus.

Grapevine cluster architecture is a key selection target in breeding programs because it influences disease susceptibility, yield stability and juice quality. High-throughput phenotyping offers a rapid and non-destructive approach to capture biochemical and structural variation in these traits, yet the influence of plant organ reflectance and data partitioning strategies on trait prediction remains poorly understood. In this study, we evaluated how hyperspectral reflectance from different grapevine organs contributes to the prediction of cluster architecture and juice quality traits in two clonal populations of Riesling and Pinot. Using partial least squares regression (PLSR), we assessed the prediction accuracy of eight cluster architecture and six juice quality traits under two data partitioning strategies. Models based on cluster reflectance outperformed those using dry leaf reflectance for most traits, except for pH. Partitioning the dataset by cluster type increased trait variance and improved predictions for number of berries (R{superscript 2} = 0.53), berry diameter (R{superscript 2} = 0.79), and total acidity (R{superscript 2} = 0.48). Visible, red-edge and NIR spectra were most informative regions to predict the traits studied. Together, our results highlight the importance of organ-specific data and appropriate calibration strategies to improve phenomic models for the development of scalable proxies for grapevine improvement. HighlightSpectral phenomics reveals that prediction accuracy in grapevine depends on organ spectral signatures and traits, with cluster reflectance outperforming leaves, informing new phenotyping strategies for breeding improvement.

Pollen is a robust and widespread substance that captures a historical snapshot of a specific time and place, and it can be used to track movements through space by examining the pollen deposited on various objects. Palynology, the study of pollen, is used across fields such as conservation, natural history, and forensics, where it is particularly useful for tracing the origin and movement of objects. However, pollen has remained underutilized due to the difficulty of distinguishing many pollen taxa beyond the family level and limited pollen reference material to support location predictions. With recent developments in pollen DNA metabarcoding these issues have been rectified, but much of the available pollen data are primarily from wind-pollinated species, which are widespread and less informative of specific sample locations. Bee-collected pollen presents an untapped resource in training predictive models to geolocate sample origin. Here we compiled bee-collected pollen DNA sequence relative abundance data from three projects in the western U.S. and assessed the accuracy of supervised machine learning models to predict the location of sample origin based solely on pollen assemblage, without the need of incorporating additional data. Random Forest and k-Nearest Neighbors models yielded high accuracy across all projects. We also found that models trained on taxonomically clustered pollen assigned sequence variants (ASVs) performed slightly better than those trained on raw sequence data, but the difference was minor, indicating that models trained on raw sequence data can reliably predict location and avoid the time-consuming taxonomic assignment process. Our results demonstrate the utility of repurposing bee-collected pollen for geolocation and provide a framework for employing supervised machine learning in future geolocation efforts. HighlightsO_LIBee-collected pollen metabarcoding data was used to accurately predict sample origin C_LIO_LIRandom Forest and k-Nearest Neighbors algorithms were most accurate with lowest error C_LIO_LITaxonomically-classified and raw DNA sequence data training sets performed comparably C_LI

Potato common scab (Streptomyces sp.) is an economically important disease that reduces the quality and market value of tubers. A key aspect in developing management strategies involves accurately quantifying the disease. Due to the three-dimensional nature of the tuber and the heterogeneous distribution of lesions across its surface, visual estimates of severity can be challenging. Therefore, the objectives of this study were to develop and validate a standard area diagram (SAD) for estimating common scab severity on potato tubers and to compare validation outcomes obtained using real tubers and digital images. A SAD comprising six severity levels (from 1.3 to 66.8%) was developed based on image analysis of naturally infected tubers. Validation was conducted using two complementary approaches in which inexperienced raters evaluated either real potato tubers or digital images of the same tubers under unaided and aided conditions. Accuracy, bias components, and inter-rater reliability were quantified using absolute error metrics, Lins concordance correlation coefficient, intraclass correlation coefficients, and overall concordance correlation coefficients. Use of the SAD significantly improved accuracy, reduced systematic bias, and increased inter-rater reliability across both validation approaches. No significant differences were detected between assessments conducted on real tubers and images, although image-based evaluations showed a slight, non-significant tendency toward reduced scale and location bias under aided conditions. These results demonstrate that a dimension-aware SAD integrating information across the full tuber surface enhances the reliability and reproducibility of visual severity assessments and supports the use of image-based evaluations for training, large-scale surveys, and remote or collaborative applications involving three-dimensional plant organs.

BackgroundPangenomes are a promising new approach to genomics that can reduce reference bias in genotyping, but the reliability of such a data model remains unclear in tracking variation across species. To test the utility of graph-based pangenomes for interspecific breeding, we developed a Minigraph-Cactus super-pangenome representing four Citrus species derived from the founder lines of a citrus breeding program. To benchmark SNP calling accuracy using graph and linear-based approaches, we performed whole genome short read sequencing for two sets of pedigreed progeny: 30 F1 hybrids and 244 advanced hybrids from an F1 crossed with a parent not included in the pangenome. ResultsThe linear approach yielded more SNP calls than the graph-based approach, however, both methods exhibited similar Mendelian Inheritance Error Rates (MIER) in a tool-dependent manner. Reconstruction of parental haplotype blocks in the advanced hybrids revealed a striking improvement in performance in the pangenome graph-based calls, suggesting MIER is vulnerable to error when reference bias influences both parental and progeny genotype calls. Masking of regions diverged from the reference path improved MIER accuracy metrics and haplotype block reconstruction in both the linear and graph-based SNP calls. ConclusionsIn non-model systems, inheritance patterns observed from pedigreed hybrids provide a framework for benchmarking variant-calling accuracy using pangenomes. SNP miscalls originating from diverged regions can falsely satisfy MIER filters, thus we recommend haplotype blocks. The inherent structure of the pangenome graph has promising applications for removing regions of unreliable mapping quality, which cannot otherwise be reliably removed using traditional filtering metrics.

If youve ever complained about a species name thats a mouthful--say, the soldier fly Parastratiosphecomyia stratiosphecomyioides or the myxobacterium Myxococcus llanfairpwllgwyngyllgogerychwyrndrobwllllantysiliogogogochensis--youre in very good company. But could the readability of binomial scientific names cause more than complaints? Could it influence how much species are studied and talked about? We examined a random sample of 3,019 species names spanning 29 phyla/divisions. We tested whether name length and reading difficulty are associated with species representation in the scientific literature (measured via literature mentions) and their visibility to the public (measured via Wikipedia pageviews). Both species name traits showed significant negative relationships with literature mentions and Wikipedia reads. Increasing name length from 10 to 30 characters is associated with a 66% decrease in expected mentions and a 65% decrease in Wikipedia reads, while shifting from the most to the least readable name in the dataset corresponds to 53% and 76% decreases. These patterns are consistent with something familiar: the fickleness of human attention, responding to features of the world that are far from rational. While creativity in naming is a cherished part of taxonomy, a touch of orthographic restraint may ultimately benefit both science and the species themselves--especially among understudied uncharismatic taxa.

The remarkable diversity of life on Earth results from evolutionary processes functioning across different spatial and temporal scales. Species diversification occurs through various mechanisms and at widely varying rates, but identifying the conditions that trigger bursts of diversification over short timescales remains a central challenge in evolutionary biology. This difficulty is more pronounced when incomplete lineage sorting (ILS), hybridization, and ongoing gene flow obscure evolutionary relationships and complicate species delimitation. In this study, we investigated the evolutionary history and species boundaries within a group of recently diverged Petunia lineages shaped by pervasive gene flow. We integrated phylogenomic, population genetic, and species delimitation approaches to reconstruct lineage relationships and assess whether these lineages represent distinct species or stages along a speciation continuum. By applying methods that account for both ILS and gene flow, we revealed that most lineages are not fully independent evolutionary units but rather occupy intermediate positions along this continuum. Gene flow played a crucial role during diversification, blurring species boundaries and generating reticulate evolutionary patterns. Our findings demonstrate that traditional phylogenetic trees may oversimplify relationships in such systems, while phylogenetic networks offer a more accurate representation of evolutionary history. Comprehensive and integrative analyses, such as those employed here, are essential for capturing these complex dynamics. Ultimately, only four lineages could be confidently recognized as distinct species, whereas the remaining represent cases of ongoing divergence. These results emphasize the need to refine species delimitation frameworks for systems characterized by recent divergence and extensive reticulation.

Computational tools, including biological language models (LMs), show substantial promise in predicting the impact of genetic variants on plant fitness. However, validating variant effect predictions (VEP) requires experimental populations where genetic variation consists of discrete point mutations rather than segregating recombination blocks. In this study, we generated a novel population of Brachypodium distachyon mutant lines to evaluate the accuracy of VEP at single-base resolution. These lines were advanced through single-seed descent for five generations (M1 to M5), with whole-genome sequencing performed at M2 and M5 and phenotypic measurements recorded at M3 and M4. Using state-of-the-art VEP models, we predicted the functional impact of missense protein-coding variants and gene-proximal non-coding variants. We validated these predictions by estimating the effect of mutations on whole-plant measurements (burden tests) and their probability of fixation from M2 to M5 (purging tests). Among missense variants, the protein LM ESM showed superior predictive accuracy compared to the bioinformatic standard SIFT and the genomic LM PlantCAD. Notably, the relationship between VEP scores and allele fixation suggested a log-linear relationship between VEP scores and variant fitness. Among gene-proximal variants, PlantCAD appeared more accurate than supervised models of regulatory activity, such as chromatin accessibility (a2z) and RNA abundance (PhytoExpr). Collectively, our findings highlight the utility of state-of-the-art VEP tools as predictors of fitness and demonstrate the potential of mutant populations to evaluate computational tools for precision breeding applications.

We present here FennoTraits, which is a dataset of plant functional trait and community composition data which we collected from Fennoscandia across northern Finland, Norway, and Sweden in 2016-2025. This dataset has 42 049 abundance estimations and 155 794 functional trait observations from 10 traits representing 373 vascular plant species collected from 1 235 study sites within seven study areas. The trait measurements consist of size-structural, leaf economic, leaf spectral, and reproductive traits. The species represent the majority of the native vascular plant species that occur at the seven study areas, and many of the species occur in all seven areas across the two biomes and their ecotone: tundra and boreal forests. Each study area has distinct characteristics and a range of habitats: tundra, meadows, wetlands, shrublands, and boreal forests. These areas are under low anthropogenic influence, and many of the sites are within protected areas that are reserved for nature conservation and scientific research. Finally, we provide with this dataset a general description of the main trait patterns and profiles of the northern European flora.

Premise of studyUnder increasingly frequent pollinator-limited environments, plants need to rely on modes of reproductive assurance such as selfing and cloning. However, few studies investigate the interplay between selfing and cloning in plants that can do both. Here, we explore mechanisms determining the relative expression of selfing and cloning throughout the European distribution of the wild woodland strawberry (Fragaria vesca) under a pollinator-free environment. MethodsWe established an outdoor common garden with 121 woodland strawberry genotypes from across Europe and excluded them from pollinators. For each genotype, we recorded reproductive traits and performed hand-pollination treatments. Key ResultsWe found a weak trade-off between cloning and selfing, driven by increased seed and fruit provisioning rather than flower production. The capacity to autonomously self-fertilize was determined by the lateral proximity of the anthers to the pistils (lateral herkogamy), but not by early inbreeding depression. Genotypes sampled at lower latitudes and altitudes were better at self-fertilizing and had smaller petals. The propensity to clone increased towards the east, where genotypes also had smaller petals, particularly at higher latitudes. ConclusionAt the species level, we detected a trade-off between the propensity for clonal reproduction and the capacity for self-fertilization. At a continental scale, the capacity to self-fertilize varied along a north-south gradient, whereas clonal propensity varied along an east-west gradient. Our results suggest that these two modes of reproductive assurance may compensate for reduced pollinator attractiveness (smaller petals) in regions where each mode is most strongly expressed.

Community science data are increasingly recognized as important resources for biodiversity research, in part because of the spatial and temporal resolution that they afford. While these data are useful for applications such as describing occurrence patterns, tracking movement of migratory animals, and recording phenological events, they can also be probed for "second-order" purposes, such as documenting species interactions. Here, I present a dataset of more than 35,000 annotated interactions between monarch butterfly (Danaus plexippus) larvae and their associated host plants from the community science platform iNaturalist. I document more than 70 unique species of milkweed hosts (Apocynaceae: Asclepiadoideae) used by monarch larvae, including a number of previously undocumented interactions. Monarchs show strong seasonal turnover in the species of host plants used across the migratory cycle, highlighting the importance of early season hosts like Asclepias viridis and A. asperula in eastern North America and A. californica and A. cordifolia in the west. I also demonstrate that non-native horticultural milkweed species have increased the spatial extent of monarch breeding during winter (November - February) by more than 60%, a pattern previously suggested from observational data but not formally quantified until now. To my knowledge, this represents the largest analysis to date of species interactions using unstructured community science data and highlights the value of platforms like iNaturalist for conducting fundamental research in ecology and conservation.

BackgroundPlants are exposed to various environmental challenges. With ongoing climate change, droughts and insect outbreaks are expected to become more frequent. Thus, a better understanding is needed of how different plant species respond to such single and combined challenges. This study investigated common versus species-specific responses to environmental challenges in three perennial plant species of different growth forms and whether responses differ intraspecifically among accessions. Clones of different accessions of the herbaceous species Tanacetum vulgare, the woody vine Solanum dulcamara, and the tree Populus nigra were subjected to similar control, herbivory, drought, and combined (drought and herbivory) treatments for the same periods. After the exposure, concentrations of foliar phytohormones and various morphological traits were measured. ResultsAcross all species, several foliar phytohormones and one of ten morphological traits responded consistently to the environmental challenges. Jasmonoyl-isoleucine was induced by herbivory and the combined treatment, abscisic acid (ABA) by drought and the combined treatment, and indole acetic acid by the combined treatment in all species. Root mass remained unchanged in all species. However, structural equation models (SEMs) revealed a shared regulatory pathway across species in which ABA connected treatment and root mass, indicating a common hormonal response potentially linking challenges to growth responses. Despite these common patterns, species-specific responses were pronounced. In P. nigra, a unique induction of salicylic acid was found under the combined treatment, while aboveground mass and root-shoot ratio remained unaffected by any treatment, in contrast to the other two species. Species-specific SEMs further indicated distinct phytohormone-mediated pathways underlying morphological variation. Phenotypic plasticity reflected these species-specific patterns, with none of the phytohormones or morphological traits exhibiting uniform plasticity across species. Intraspecific variation further shaped responses, as phytohormone and morphological trait plasticity depended on accession, indicating substantial accession-specific plant responses. ConclusionsOur results indicate that some responses to comparable challenges may be conserved across species, while others are species-specific. The combined treatment elicited the most pronounced responses, and such complex responses may become more frequent under current global change. Our study highlights that comprehensive understanding of plant responses requires systematic comparisons at both interspecific and intraspecific scales.

Accurate genome annotation remains challenging as assembly quality often exceeds annotation reliability. Resolving ambiguities of gene presence, absence, and orthology typically requires integrating two complementary lines of evidence: sequence homology between species and the conservation of gene order (i.e., synteny). BLAST remains the standard for homology detection, yet its raw output can be difficult to interpret. Existing tools address this challenge but operate at opposing scales. Alignment viewers provide detailed pairwise statistics without genomic context, while synteny tools offer chromosome-scale perspectives without sequence-level resolution. To fill this intermediate gap, we developed Novabrowse, an interactive BLAST results interpretation framework featuring high-resolution multi-species synteny analysis, chromosomal re-arrangement investigation, ortholog detection, and gene signal discovery. Users define a genomic region of interest in a query species and/or use custom sequences, then select one or more subject species for comparison. The pipeline retrieves query gene sequences via NCBI API integration and performs BLAST searches against each subject transcriptome or genome. Results are presented via an interactive HTML file featuring alignment statistics, chromosomal maps, coverage visualizations, ribbon plots, and distance-based clustering of high-scoring segment pairs into putative gene units. We demonstrate these capabilities by investigating Foxp3, Aire, and Rbl1, three highly conserved vertebrate genes, in the recently assembled genome of the newt Pleurodeles waltl. Foxp3 and Aire have not been described in any salamander species to date, despite availability of multiple assemblies and extensive transcriptomic datasets. Using Novabrowse, we discovered conserved loci and gene signals for both genes in P. waltl, the presence of which was subsequently confirmed via Nanopore long-read RNA sequencing. In contrast, Rbl1 analysis uncovered a chromosomal rearrangement at its expected locus with no gene signal detected, indicating a gene loss specific to P. waltl despite the genes retention in the closely related axolotl (Ambystoma mexicanum). Our findings demonstrate Novabrowses capacity for evidence-based evaluation of annotation artifacts, an essential capability as high-quality assemblies become more available for phylogenetically diverse species. Novabrowse is open source (MIT license) and freely available at: https://github.com/RegenImm-Lab/Novabrowse.

The temperate rainforests of the Pacific Northwest of North America harbor many endemic taxa whose evolutionary histories have been shaped by major climatic and geologic events. The enigmatic taildropper slugs (genus Prophysaon) are one example, notable for their ability to autonomize their tails to escape predators. Despite extensive work uncovering the evolutionary history of individual lineages, relationships among the nine recognized species of Prophysaon remain poorly understood due to insufficient molecular data. To address this, we collected transcriptomes for six of the nine currently accepted species of Prophysaon. Using these data, we were able to resolve species relationships, calling into question the existing subgeneric classification based on morphology. We also detected undescribed phenotypic diversity within the P. andersonii--P. foliolatum species complex, with molecular data supporting the distinctness of two phenotypically distinct populations from Washington. Finally, our transcriptomic data suggest a moderate role of introgression in shaping the evolutionary history of Prophysaon. Here, we synonymize the subgenus Mimetarion with nominotypical Prophysaon. Future work should further investigate whether the undescribed diversity detected here represents species level differentiation.