Applications in Plant Sciences最新文献

{"title":"A practical and easy-to-scale protocol for removing chlorophylls from leaf extracts","authors":"Alice Fossati,&nbsp;Valeria Cavalloro,&nbsp;Daniela Rossi,&nbsp;Simona Collina,&nbsp;Emanuela Martino","doi":"10.1002/aps3.70018","DOIUrl":"10.1002/aps3.70018","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Leaf extracts are valuable sources of bioactive compounds. However, co-extracted chlorophylls interfere with analyses, including spectroscopic and biochemical assays. Existing methods for chlorophyll removal often have limitations, including the use of hazardous solvents, low specificity, or high costs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>A solid-phase extraction protocol for chlorophyll removal from leaf extracts of <i>Corylus avellana</i> was developed using commercially available cartridges. The method requires standard equipment, can be completed within 10 minutes, and is scalable from analytical to preparative quantities. We validated this protocol across 20 taxa, demonstrating the removal of 85% of chlorophylls, successful scale up of quantities, cartridge reusability, and low solvent consumption.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Key innovations of the protocol include simplified elution steps and the possibility of multiple reuse cycles. The simplicity, sustainability, and scalability of this new protocol make it particularly valuable for high-throughput applications and process development.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144768118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in analyzing and engineering plant metabolic diversity","authors":"Kira J. Tiedge,&nbsp;Federico Roda,&nbsp;Stacey D. Smith,&nbsp;Gaurav D. Moghe","doi":"10.1002/aps3.70017","DOIUrl":"10.1002/aps3.70017","url":null,"abstract":"&lt;p&gt;The immense diversity of the members of the kingdom Plantae, so far comprising more than 400,000 known species (Guiry, &lt;span&gt;2024&lt;/span&gt;), is reflected not only in their morphological and genetic variability but also in their metabolic complexity. Plant metabolic networks are dynamic and expanding systems that evolve in a lineage-specific manner and produce hundreds of thousands of structurally diverse metabolites, which can be broadly categorized into general (or core/primary) and specialized (or secondary) metabolites. General metabolites, such as carbohydrates, amino acids, and lipids, are essential for fundamental physiological processes like growth, development, and reproduction. In contrast, specialized metabolites like alkaloids, flavonoids, terpenoids, and other phenolic compounds often have an impact at different levels beyond central carbon metabolism—from allosteric regulation of proteins, subcellular organization, and intercellular interactions to organismal phenotypes, phylogeographic/interspecies diversification, biotic/abiotic interactions, and ecosystem maintenance (Weng et al., &lt;span&gt;2021&lt;/span&gt;; Ono and Murata, &lt;span&gt;2023&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;The chemical diversity of plant metabolites constitutes a vast and largely untapped phytochemical space with significant potential for applications across multiple fields. In medicine, plant-derived compounds have been a cornerstone of drug discovery for centuries. For example, alkaloids, like morphine and quinine, and terpenoids, such as paclitaxel, have revolutionized the treatment of pain, malaria, and cancer, respectively (Newman and Cragg, &lt;span&gt;2020&lt;/span&gt;; Atanasov et al., &lt;span&gt;2021&lt;/span&gt;). In agriculture, phytochemicals are increasingly recognized for their contribution to plant defense against pests and diseases, reducing the need for synthetic pesticides while promoting sustainable farming practices and food security (Sousa et al., &lt;span&gt;2021&lt;/span&gt;). Beyond medicine and agriculture, plant metabolites hold promise for applications in biotechnology and industrial processes. For instance, terpenoids and phenolic compounds are being investigated for their potential as biofuels, bioplastics, and natural food preservatives (Mewalal et al., &lt;span&gt;2017&lt;/span&gt;). Even though less than 10% of plant species have been thoroughly investigated for their chemical composition (Li and Vederas, &lt;span&gt;2009&lt;/span&gt;), it is estimated that plants produce over a million compounds, although pinpointing a specific number is challenging because of the heterogeneity of metabolite databases available (Wang et al., &lt;span&gt;2016&lt;/span&gt;; Nguyen-Vo et al., &lt;span&gt;2020&lt;/span&gt;; Hawkins et al., &lt;span&gt;2021&lt;/span&gt;). Recent estimates suggest that the total number of unique structures across the entire plant kingdom likely spans into the millions to tens of millions (Engler Hart et al., &lt;span&gt;2025&lt;/span&gt;), indicating that over 99% of the phytochemical space remains unexplored and highlighting its vast and largely untapped p","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying interpretable machine learning to assess intraspecific trait divergence under landscape-scale population differentiation","authors":"Sambadi Majumder,&nbsp;Chase M. Mason","doi":"10.1002/aps3.70015","DOIUrl":"10.1002/aps3.70015","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Here we demonstrate the application of interpretable machine learning methods to investigate intraspecific functional trait divergence using diverse genotypes of the wide-ranging sunflower <i>Helianthus annuus</i> occupying populations across two contrasting ecoregions—the Great Plains versus the North American Deserts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Recursive feature elimination was applied to functional trait data from the HeliantHOME database, followed by the application of the Boruta algorithm to detect the traits that are most predictive of ecoregion. Random forest and gradient boosting machine classifiers were then trained and validated, with results visualized using accumulated local effects plots.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The most ecoregion-predictive functional traits span categories of leaf economics, plant architecture, reproductive phenology, and floral and seed morphology. Relative to the Great Plains, genotypes from the North American Deserts exhibit shorter stature, fewer leaves, higher leaf nitrogen content, and longer average length of phyllaries.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This approach readily identifies traits predictive of ecoregion origin, and thus the functional traits most likely to be responsible for contrasting ecological strategies across the landscape. This type of approach can be used to parse large plant trait datasets in a wide range of contexts, including explicitly testing the applicability of interspecific paradigms at intraspecific scales.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel combination of in vitro propagation and hydroponic culture for hybrid cacao (Theobroma cacao) plants","authors":"Luis David Vera Pinargote,&nbsp;Elisabeth Jamet,&nbsp;Naga Raju Maddela","doi":"10.1002/aps3.70014","DOIUrl":"10.1002/aps3.70014","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Currently, there is a lack of controlled cultivation methods for cacao (<i>Theobroma cacao</i>), a plant species with high commercial value. One major concern is the tendency of cacao plants to accumulate high concentrations of cadmium (Cd), a heavy metal with high toxicity to living organisms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>We describe a new two-step method for the propagation of hybrid cacao plants, consisting of (1) in vitro germination for two weeks, followed by (2) transfer to a vertical hydroponic system for growth under controlled conditions. As a test case, two new cacao hybrids were cultivated in the presence of Cd and showed different levels of tolerance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our simple approach offers a new research direction for the controlled cultivation of cacao plants and can potentially be applied to other plants of agronomic interest. Moreover, this method allows the identification of plants that are resistant to various toxic substances, which could then be used in phytoremediation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving computer vision for plant pathology through advanced training techniques","authors":"Jamie R. Sykes,&nbsp;Katherine J. Denby,&nbsp;Daniel W. Franks","doi":"10.1002/aps3.70010","DOIUrl":"10.1002/aps3.70010","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>This study investigates advanced training techniques to improve the performance of convolutional neural networks for disease detection in cocoa, <i>Theobroma cacao</i>.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Despite recent stagnation in accuracy improvements in computer vision for image classification, our research demonstrates significant advancements in performance through semi-supervised learning, specialised loss functions, and the inclusion of a non-cocoa class.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Semi-supervised learning reduced overfitting and enhanced generalisability, particularly for subtle symptoms. The non-cocoa class exposed models to a broad range of relevant features, significantly improving model robustness and performance in difficult cases. Grad-CAM for qualitative assessment provided valuable insights into model behaviour, highlighting cases of overfitting missed by summary statistics. We also describe dynamic focal loss, a novel loss function that uses an empirical measure of difficulty to weight each image. Our results suggest that while PhytNet shows promise in terms of computational efficiency and superior handling of difficult images, ResNet18 with semi-supervised learning and dynamic focal loss emerged as the strongest contender for real-world deployment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This research underscores the potential of semi-supervised learning and advanced loss functions in enhancing the applicability of deep learning models in agricultural disease management. It also presents a new high-quality benchmark dataset of 7220 images of diseased and healthy cocoa trees, offering a much greater and more realistic challenge than the Plan Village dataset.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"infinitylists: A Shiny application and R package for rapid generation of place-based species checklists","authors":"Thomas Mesaglio,&nbsp;Fonti Kar,&nbsp;Hervé Sauquet,&nbsp;William K. Cornwell","doi":"10.1002/aps3.70012","DOIUrl":"10.1002/aps3.70012","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Biodiversity researchers often need to answer the question: “Which species of taxon X have been documented in (or near) spatial polygon Y?” Online databases with billions of occurrence records, including vouchered specimens and citizen science records, can provide the answer; however, quick spatial processing of huge biodiversity datasets can be difficult, and many general-purpose tools are constrained by dataset size.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p><i>infinitylists</i> is a Shiny application and R package that allows users to generate species checklists for a user-specified taxon and area. It downloads taxon–country datasets (e.g., Madagascan geckos) from biodiversity data providers and uses an open source, column-oriented data file for fast retrieval and visualization. Available as a mobile-friendly web tool with preloaded data, it can also be run locally in R for very flexible applications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p><i>infinitylists</i> is an easy-to-use tool with applications including supplementing survey data, planning collecting expeditions, and informing gap-filling. <i>infinitylists</i> is a complementary tool to existing databases to help field ecologists and naturalists globally.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Computer-Assisted Sequence Annotation (CASA) workflow for enzyme discovery","authors":"Gemma R. Takahashi,&nbsp;Franchesca M. Cumpio,&nbsp;Carter T. Butts,&nbsp;Rachel W. Martin","doi":"10.1002/aps3.70009","DOIUrl":"10.1002/aps3.70009","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>With the advent of inexpensive nucleic acid sequencing and automated annotation at the level of basic functionality, the central problem of enzyme discovery is no longer finding active sequences, it is determining which ones are suitable for further study. This requires annotation that goes beyond sequence similarity to known enzymes and provides information at the sequence and structural levels.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Here we introduce a workflow for generating highly informative, richly annotated sequence alignments from protein sequence data. Computer-Assisted Sequence Annotation (CASA) is a freely available Python-based workflow designed to automate portions of novel protein characterization, while producing a human-interpretable final output.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We demonstrate CASA using one enzyme from the <i>Drosera capensis</i> genome. The workflow generates detailed annotations providing comparisons to known reference sequences. In addition to sequence similarity and predicted function, user-specified features such as active site residues, disulfide bonds, and substrate-binding residues can be displayed, and these can then be combined with downstream analyses to gain new insights into enzyme structure and function.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This work demonstrates the utility of detailed annotations and protein structure prediction for choosing protein targets for biochemistry or structural biology from nucleic acid sequence data. The toolchain is freely available along with instructions and representative examples.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using large language models to extract plant functional traits from unstructured text","authors":"Viktor Domazetoski,&nbsp;Holger Kreft,&nbsp;Helena Bestova,&nbsp;Philipp Wieder,&nbsp;Radoslav Koynov,&nbsp;Alireza Zarei,&nbsp;Patrick Weigelt","doi":"10.1002/aps3.70011","DOIUrl":"10.1002/aps3.70011","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Functional plant ecology seeks to understand how functional traits govern species distributions, community assembly, and ecosystem functions. While global trait datasets have advanced the field, substantial gaps remain, and extracting trait information from text in books, research articles, and online sources via machine learning offers a valuable complement to costly field campaigns.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We propose a natural language processing pipeline that extracts traits from unstructured species descriptions by using classification models for categorical traits and question-answering models for numerical traits. The pipeline's performance is evaluated on two large databases with over 50,000 species descriptions, utilizing approaches ranging from a keyword search to large language models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our final optimized pipeline used a transformer architecture and obtained a mean precision of 90.8% (range 81.6–97%) and a mean recall of 88.6% (77.4–97%) across five categorical traits, representing a 9.83% increase in precision and 42.35% increase in recall over a regular expression-based approach. The question-answering model yielded a normalized mean absolute error of 10.3% averaged across three numerical traits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The natural language processing pipeline we propose has the potential to facilitate the digitization and extraction of large amounts of plant functional trait information residing in scattered textual descriptions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fully automatic extraction of morphological traits from the web: Utopia or reality?","authors":"Diego Marcos,&nbsp;Robert van de Vlasakker,&nbsp;Ioannis N. Athanasiadis,&nbsp;Pierre Bonnet,&nbsp;Hervé Goëau,&nbsp;Alexis Joly,&nbsp;W. Daniel Kissling,&nbsp;César Leblanc,&nbsp;André S. J. van Proosdij,&nbsp;Konstantinos P. Panousis","doi":"10.1002/aps3.70005","DOIUrl":"10.1002/aps3.70005","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Plant morphological traits, their observable characteristics, are fundamental to understanding the role played by each species within its ecosystem; however, compiling trait information for even a moderate number of species is a demanding task that may take experts years to accomplish. At the same time, online species descriptions contain massive amounts of information about morphological traits, but the lack of structure makes this source of data impossible to use at scale.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To overcome this, we propose to leverage recent advances in large language models and devise a mechanism for gathering and processing plant trait information in the form of unstructured textual descriptions, without manual curation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We evaluate our approach by automatically replicating three manually created species–trait matrices. Our method found values for over half of all species–trait pairs, with an F1 score of over 75%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Our results suggest that large-scale creation of structured trait databases from unstructured online text is now feasible due to the information extraction capabilities of large language models. However, the process is currently limited by the availability of textual descriptions that cover all traits of interest.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chromosome-scale reference genome of Pectocarya recurvata, the species with the smallest reported genome size in Boraginaceae","authors":"Poppy C. Northing,&nbsp;Jessie A. Pelosi,&nbsp;D. Lawrence Venable,&nbsp;Katrina M. Dlugosch","doi":"10.1002/aps3.70008","DOIUrl":"10.1002/aps3.70008","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p><i>Pectocarya recurvata</i> (Boraginaceae, subfamily Cynoglossoideae), a species native to the Sonoran Desert (North America), has served as a model system for a suite of ecological and evolutionary studies. However, no reference genomes are currently available in Cynoglossoideae. A high-quality reference genome for <i>P. recurvata</i> would be valuable for addressing questions in this system and across broader taxonomic scales.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using PacBio HiFi sequencing, we assembled a reference genome for <i>P. recurvata</i> and annotated coding regions with full-length transcripts from an Iso-Seq library. We assessed genome completeness with BUSCO and <i>k</i>-mer analysis, and estimated the genome size of six individuals using flow cytometry.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The chromosome-scale genome assembly for <i>P. recurvata</i> was 216.0 Mbp long (N50 = 12.1 Mbp). Previous observations indicated <i>P. recurvata</i> is 2<i>n</i> = 24. Our assembly included 12 primary contigs (158.3 Mbp) containing 30,655 genes with telomeres at 23 out of 24 ends. Flow cytometry measurements from the same population included two plants with 1C = 196.9 Mbp, the smallest measured for Boraginaceae, and four with 1C = 385.8 Mbp, which is consistent with tetraploidy in this population.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The <i>P. recurvata</i> genome assembly and annotation provide a high-quality genomic resource in a sparsely represented area of the angiosperm phylogeny. This new reference genome will facilitate answering open questions in ecophysiology, biogeography, and systematics.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}