Applications in Plant Sciences最新文献

{"title":"An optimized CTAB method for genomic DNA extraction from green seaweeds (Ulvophyceae)","authors":"Riyad Hossen,&nbsp;Myles Courtney,&nbsp;Alasdair Sim,&nbsp;Md Abdullah Al Kamran Khan,&nbsp;Heroen Verbruggen,&nbsp;Trevor Bringloe","doi":"10.1002/aps3.11625","DOIUrl":"https://doi.org/10.1002/aps3.11625","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Seaweeds are gaining substantial research interest, particularly for genomic applications, where high-quality DNA is a prerequisite. Extracting DNA from these organisms presents challenges due to high levels of biomacromolecules resulting from their diverse cell structures. Existing protocols often lack versatility, leading to inconsistent outcomes across various materials and taxa, which highlights the need for a universal method for use with a variety of green seaweed samples.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>We optimized the conventional cetyltrimethylammonium bromide (CTAB) protocol for green seaweed DNA extraction. Our method, involving an initial sample treatment, lysis buffer adjustment, and enzyme incubation alterations, outperformed the conventional CTAB and commercial kits in terms of DNA yield and purity. Notably, the protocol's effectiveness was demonstrated across various green algal materials and preservation methods, and was tested with downstream applications with satisfactory results.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our optimized CTAB protocol offers a reliable solution for high-quality genomic DNA extraction from a wide variety of green seaweed samples.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11625","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120545","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":"From phylogenomics to breeding: Can universal target capture probes be used in the development of SNP markers for kinship analysis?","authors":"Kedra M. Ousmael,&nbsp;Ole K. Hansen","doi":"10.1002/aps3.11624","DOIUrl":"https://doi.org/10.1002/aps3.11624","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Leveraging DNA markers, particularly single-nucleotide polymorphisms (SNPs), in parentage analysis, sib-ship reconstruction, and genomic relatedness analysis can enhance plant breeding efficiency. However, the limited availability of genomic information, confined to the most commonly used species, hinders the broader application of SNPs in species of lower economic interest (e.g., most tree species). We explored the possibility of using universal target capture probes, namely Angiosperms353, to identify SNPs and assess their effectiveness in genomic relatedness analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We tested the approach in 11 tree species, six of which had a half-sib family structure. Variants were called within species, and genomic relatedness analysis was conducted in species with two or more families. Scalability via amplicon sequencing was tested by designing primers and testing them in silico.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Adequate SNPs for relatedness analysis were identified in all species. Relatedness values from Angiosperms353-based SNPs highly correlated with those from thousands of genome-wide DArTseq SNPs in <i>Cordia africana</i>, one of the species with a family structure. The in silico performance of designed primers demonstrated the potential for scaling up via amplicon sequencing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Utilizing universal target capture probes for SNP identification can help overcome the limitations of genomic information availability, thereby enhancing the application of genomic markers in breeding plant species with lower economic interest.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11624","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114422","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":"Ensemble automated approaches for producing high-quality herbarium digital records","authors":"Robert P. Guralnick,&nbsp;Raphael LaFrance,&nbsp;Julie M. Allen,&nbsp;Michael W. Denslow","doi":"10.1002/aps3.11623","DOIUrl":"https://doi.org/10.1002/aps3.11623","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>One of the slowest steps in digitizing natural history collections is converting labels associated with specimens into a digital data record usable for collections management and research. Here, we address how herbarium specimen labels can be converted into digital data records via extraction into standardized Darwin Core fields.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We first showcase the development of a rule-based approach and compare outcomes with a large language model–based approach, in particular ChatGPT4. We next quantified omission and commission error rates across target fields for a set of labels transcribed using optical character recognition (OCR) for both approaches. For example, we find that ChatGPT4 often creates field names that are not Darwin Core compliant while rule-based approaches often have high commission error rates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our results suggest that these approaches each have different strengths and limitations. We therefore developed an ensemble approach that leverages the strengths of each individual method and documented that ensembling strongly reduced overall information extraction errors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This work shows that an ensemble approach has particular value for creating high-quality digital data records, even for complicated label content. While human validation is still needed to ensure the best possible quality, automated approaches can speed digitization of herbarium specimen labels and are likely to be broadly usable for all natural history collection types.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112425","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":"An open-source LED lamp for use with the LI-6800 photosynthesis system","authors":"Aarón I. Vélez-Ramírez,&nbsp;Juan de Dios Moreno,&nbsp;Uriel G. Pérez-Guerrero,&nbsp;Antonio M. Juarez,&nbsp;Hector Castillo-Arriaga,&nbsp;Josefina Vázquez-Medrano,&nbsp;Ilane Hernández-Morales","doi":"10.1002/aps3.11622","DOIUrl":"https://doi.org/10.1002/aps3.11622","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Controlling light flux density during carbon dioxide assimilation measurements is essential in photosynthesis research. Commercial lamps are expensive and are based on monochromatic light-emitting diodes (LEDs), which deviate significantly in their spectral distribution compared to sunlight.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>Using LED-emitted white light with a color temperature similar to sunlight, we developed a cost-effective lamp compatible with the LI-6800 Portable Photosynthesis System. When coupled with customized software, the lamp can be controlled via the LI-6800 console by a user or Python scripts. Testing and calibration show that the lamp meets the quality needed to estimate photosynthesis parameters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The lamp can be built using a basic electronics lab and a 3D printer. Calibration instructions are supplied and only require equipment commonly available at plant science laboratories. The lamp is a cost-effective alternative to perform photosynthesis research coupled with the popular LI-6800 photosynthesis measuring system.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119431","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":"Tailoring convolutional neural networks for custom botanical data","authors":"Jamie R. Sykes,&nbsp;Katherine J. Denby,&nbsp;Daniel W. Franks","doi":"10.1002/aps3.11620","DOIUrl":"https://doi.org/10.1002/aps3.11620","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Automated disease, weed, and crop classification with computer vision will be invaluable in the future of agriculture. However, existing model architectures like ResNet, EfficientNet, and ConvNeXt often underperform on smaller, specialised datasets typical of such projects.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We address this gap with informed data collection and the development of a new convolutional neural network architecture, PhytNet. Utilising a novel dataset of infrared cocoa tree images, we demonstrate PhytNet's development and compare its performance with existing architectures. Data collection was informed by spectroscopy data, which provided useful insights into the spectral characteristics of cocoa trees. Cocoa was chosen as a focal species due to the diverse pathology of its diseases, which pose significant challenges for detection.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ResNet18 showed some signs of overfitting, while EfficientNet variants showed distinct signs of overfitting. By contrast, PhytNet displayed excellent attention to relevant features, almost no overfitting, and an exceptionally low computation cost of 1.19 GFLOPS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We show that PhytNet is a promising candidate for rapid disease or plant classification and for precise localisation of disease symptoms for autonomous systems. We also show that the most informative light spectra for detecting cocoa disease are outside the visible spectrum and that efforts to detect disease in cocoa should be focused on local symptoms, rather than the systemic effects of disease.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117682","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":"Expression-based machine learning models for predicting plant tissue identity","authors":"Sourabh Palande,&nbsp;Jeremy Arsenault,&nbsp;Patricia Basurto-Lozada,&nbsp;Andrew Bleich,&nbsp;Brianna N. I. Brown,&nbsp;Sophia F. Buysse,&nbsp;Noelle A. Connors,&nbsp;Sikta Das Adhikari,&nbsp;Kara C. Dobson,&nbsp;Francisco Xavier Guerra-Castillo,&nbsp;Maria F. Guerrero-Carrillo,&nbsp;Sophia Harlow,&nbsp;Héctor Herrera-Orozco,&nbsp;Asia T. Hightower,&nbsp;Paulo Izquierdo,&nbsp;MacKenzie Jacobs,&nbsp;Nicholas A. Johnson,&nbsp;Wendy Leuenberger,&nbsp;Alessandro Lopez-Hernandez,&nbsp;Alicia Luckie-Duque,&nbsp;Camila Martínez-Avila,&nbsp;Eddy J. Mendoza-Galindo,&nbsp;David Cruz Plancarte,&nbsp;Jenny M. Schuster,&nbsp;Harry Shomer,&nbsp;Sidney C. Sitar,&nbsp;Anne K. Steensma,&nbsp;Joanne Elise Thomson,&nbsp;Damián Villaseñor-Amador,&nbsp;Robin Waterman,&nbsp;Brandon M. Webster,&nbsp;Madison Whyte,&nbsp;Sofía Zorilla-Azcué,&nbsp;Beronda L. Montgomery,&nbsp;Aman Y. Husbands,&nbsp;Arjun Krishnan,&nbsp;Sarah Percival,&nbsp;Elizabeth Munch,&nbsp;Robert VanBuren,&nbsp;Daniel H. Chitwood,&nbsp;Alejandra Rougon-Cardoso","doi":"10.1002/aps3.11621","DOIUrl":"https://doi.org/10.1002/aps3.11621","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>The selection of <i>Arabidopsis</i> as a model organism played a pivotal role in advancing genomic science. The competing frameworks to select an agricultural- or ecological-based model species were rejected, in favor of building knowledge in a species that would facilitate genome-enabled research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Here, we examine the ability of models based on <i>Arabidopsis</i> gene expression data to predict tissue identity in other flowering plants. Comparing different machine learning algorithms, models trained and tested on <i>Arabidopsis</i> data achieved near perfect precision and recall values, whereas when tissue identity is predicted across the flowering plants using models trained on <i>Arabidopsis</i> data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The identity of belowground tissue can be predicted more accurately than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from <i>Arabidopsis</i>. <i>k</i>-nearest neighbors is the most successful algorithm, suggesting that gene expression signatures, rather than marker genes, are more valuable to create models for tissue and cell type prediction in plants.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Our data-driven results highlight that the assertion that knowledge from <i>Arabidopsis</i> is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data, we should reevaluate the scientific emphasis on <i>Arabidopsis</i> and prioritize plant diversity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11621","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116963","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":"FlowerMate: Multidimensional reciprocity and inaccuracy indices for style-polymorphic plant populations","authors":"Violeta Simón-Porcar,&nbsp;A. Jesús Muñoz-Pajares,&nbsp;Juan Arroyo,&nbsp;Steven D. Johnson","doi":"10.1002/aps3.11618","DOIUrl":"https://doi.org/10.1002/aps3.11618","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Heterostyly in plants promotes pollen transfer between floral morphs, because female and male sex organs are located at roughly reciprocal heights within the flowers of each morph. Reciprocity indices, which assess the one-dimensional variation in the height of sex organs, are used to define the phenotypic structure of heterostyly in plant populations and to make inferences about selection. Other reciprocal stylar polymorphisms (e.g., enantiostyly) may function in a similar manner to heterostyly. In-depth assessment of their potential fit with pollinators requires accounting for the multidimensional variation in the location of sex organs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>We have adapted the existing reciprocity indices used for heterostylous plant populations to incorporate multidimensional data. We illustrate the computation of the adapted and original indices in the freely available R package FlowerMate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>FlowerMate provides fast computation of reliable indices to facilitate understanding of the evolution and function of the full diversity of reciprocal polymorphisms.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"12 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758745","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":"Truly the best of both worlds: Merging lineage-specific and universal probe kits to maximize phylogenomic inference","authors":"Luiz Henrique M. Fonseca,&nbsp;Pieter Asselman,&nbsp;Katherine R. Goodrich,&nbsp;Francis J. Nge,&nbsp;Vincent Soulé,&nbsp;Kathryn Mercier,&nbsp;Thomas L. P. Couvreur,&nbsp;Lars W. Chatrou","doi":"10.1002/aps3.11615","DOIUrl":"https://doi.org/10.1002/aps3.11615","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Hybridization capture kits are now commonly used for reduced representation approaches in genomic sequencing, with both universal and clade-specific kits available. Here, we present a probe kit targeting 799 low-copy genes for the plant family Annonaceae.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This new version of the kit combines the original 469 genes from the previous Annonaceae kit with 334 genes from the universal Angiosperms353 kit. We also compare the results obtained using the original Angiosperms353 kit with our custom approach using a subset of specimens. Parsimony-informative sites and the results of maximum likelihood phylogenetic inference were assessed for combined matrices using the genera <i>Asimina</i> and <i>Deeringothamnus</i>.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The Annonaceae799 genes derived from the Angiosperms353 kit have extremely high recovery rates. Off-target reads were also detected. When evaluating size, the proportion of on- and off-target regions, and the number of parsimony-informative sites, the genes incorporated from the Angiosperms353 panel generally outperformed the genes from the original Annonaceae probe kit.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>We demonstrated that the new sequences from the Angiosperms353 probe set are variable and relevant for future studies on species-level phylogenomics and within-species studies in the Annonaceae. The integration of kits also establishes a connection between projects and makes new genes available for phylogenetic and population studies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"12 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762825","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":"BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more","authors":"Nelson R. Salinas,&nbsp;Gil Eshel,&nbsp;Gloria M. Coruzzi,&nbsp;Rob DeSalle,&nbsp;Michael Tessler,&nbsp;Damon P. Little","doi":"10.1002/aps3.11604","DOIUrl":"https://doi.org/10.1002/aps3.11604","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Common steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>BAD2matrix is a Python script that performs the above-mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX-like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>BAD2matrix helps simplify phylogenomic pipelines and can be downloaded from https://github.com/dpl10/BAD2matrix/tree/master under a GNU General Public License v2.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"12 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762633","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":"An efficient and effective RNA extraction protocol for ferns","authors":"Jessie A. Pelosi,&nbsp;Ruth Davenport,&nbsp;W. Brad Barbazuk,&nbsp;Emily B. Sessa,&nbsp;Li-Yaung Kuo","doi":"10.1002/aps3.11617","DOIUrl":"10.1002/aps3.11617","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>The 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We 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 &gt; 1.6, and RNA integrity numbers &gt;7.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This 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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"12 6","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11617","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142199631","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}