Plant Methods最新文献

{"title":"A high-efficiency transient expression system mediated by Agrobacterium tumefaciens in Spinacia oleracea leaves.","authors":"Yumeng Zhang, Liuliu Qiu, Yongxue Zhang, Yiran Wang, Chunxiang Fu, Shaojun Dai, Meihong Sun","doi":"10.1186/s13007-024-01218-y","DOIUrl":"10.1186/s13007-024-01218-y","url":null,"abstract":"<p><strong>Background: </strong>Optimization of a highly efficient transient expression system is critical for the study of gene function, particularly in those plants in which stable transformation methods are not widely available. Agrobacterium tumefaciens‑mediated transient transformation is a simple and low-cost method that has been developed and applied to a wide variety of plant species. However, the transient expression in spinach (Spinacia oleracea L.) is still not reported.</p><p><strong>Results: </strong>We developed a transient expression system in spinach leaves of the Sp75 and Sp73 varieties. Several factors influencing the transformation efficiency were optimized such as Agrobacterium strain, spinach seedling stage, leaf position, and the expression time after injection. Agrobacterium strain GV3101 (pSoup-p19) was more efficient than AGL1 in expressing recombinant protein in spinach leaves. In general, Sp75 leaves were more suitable than Sp73 leaves, regardless of grow stage. At four-leaf stage, higher intensity and efficiency of transient expression were observed in group 1 (G1) of Sp75 at 53 h after injection (HAI) and in G1 of Sp73 at 64 HAI. At six-leaf stage of Sp75, group 3 (G3) at 72 HAI were the most effective condition for transient expression. Using the optimized expression system, we detected the subcellular localization of a transcriptional co-activator SoMBF1c and a NADPH oxidase SoRbohF. We also detected the interaction of the protein kinase SoCRK10 and the NADPH oxidase SoRbohB.</p><p><strong>Conclusion: </strong>This study established a method of highly efficient transient expression mediated by Agrobacterium in spinach leaves. The transient expression system will facilitate the analysis of gene function and lay a solid foundation for molecular design breeding of spinach.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"100"},"PeriodicalIF":4.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11220957/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141493028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 improved bacterial mRNA enrichment strategy in dual RNA sequencing to unveil the dynamics of plant-bacterial interactions.","authors":"Jayabalan Shilpha, Junesung Lee, Ji-Su Kwon, Hyun-Ah Lee, Jae-Young Nam, Hakgi Jang, Won-Hee Kang","doi":"10.1186/s13007-024-01227-x","DOIUrl":"10.1186/s13007-024-01227-x","url":null,"abstract":"<p><strong>Background: </strong>Dual RNA sequencing is a powerful tool that enables a comprehensive understanding of the molecular dynamics underlying plant-microbe interactions. RNA sequencing (RNA-seq) poses technical hurdles in the transcriptional analysis of plant-bacterial interactions, especially in bacterial transcriptomics, owing to the presence of abundant ribosomal RNA (rRNA), which potentially limits the coverage of essential transcripts. Therefore, to achieve cost-effective and comprehensive sequencing of the bacterial transcriptome, it is imperative to devise efficient methods for eliminating rRNA and enhancing the proportion of bacterial mRNA. In this study, we modified a strand-specific dual RNA-seq method with the goal of enriching the proportion of bacterial mRNA in the bacteria-infected plant samples. The enriched method involved the sequential separation of plant mRNA by poly A selection and rRNA removal for bacterial mRNA enrichment followed by strand specific RNA-seq library preparation steps. We assessed the efficiency of the enriched method in comparison to the conventional method by employing various plant-bacterial interactions, including both host and non-host resistance interactions with pathogenic bacteria, as well as an interaction with a beneficial rhizosphere associated bacteria using pepper and tomato plants respectively.</p><p><strong>Results: </strong>In all cases of plant-bacterial interactions examined, an increase in mapping efficiency was observed with the enriched method although it produced a lower read count. Especially in the compatible interaction with Xanthmonas campestris pv. Vesicatoria race 3 (Xcv3), the enriched method enhanced the mapping ratio of Xcv3-infected pepper samples to its own genome (15.09%; 1.45-fold increase) and the CDS (8.92%; 1.49-fold increase). The enriched method consistently displayed a greater number of differentially expressed genes (DEGs) than the conventional RNA-seq method at all fold change threshold levels investigated, notably during the early stages of Xcv3 infection in peppers. The Gene Ontology (GO) enrichment analysis revealed that the DEGs were predominantly enriched in proteolysis, kinase, serine type endopeptidase and heme binding activities.</p><p><strong>Conclusion: </strong>The enriched method demonstrated in this study will serve as a suitable alternative to the existing RNA-seq method to enrich bacterial mRNA and provide novel insights into the intricate transcriptomic alterations within the plant-bacterial interplay.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"99"},"PeriodicalIF":4.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11218159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141477216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-destructive wood identification using X-ray µCT scanning: which resolution do we need?","authors":"Sofie Dierickx, Siska Genbrugge, Hans Beeckman, Wannes Hubau, Pierre Kibleur, Jan Van den Bulcke","doi":"10.1186/s13007-024-01216-0","DOIUrl":"10.1186/s13007-024-01216-0","url":null,"abstract":"<p><strong>Background: </strong>Taxonomic identification of wood specimens provides vital information for a wide variety of academic (e.g. paleoecology, cultural heritage studies) and commercial (e.g. wood trade) purposes. It is generally accomplished through the observation of key anatomical features. Classic methodologies mostly require destructive sub-sampling, which is not always acceptable. X-ray computed micro-tomography (µCT) is a promising non-destructive alternative since it allows a detailed non-invasive visualization of the internal wood structure. There is, however, no standardized approach that determines the required resolution for proper wood identification using X-ray µCT. Here we compared X-ray µCT scans of 17 African wood species at four resolutions (1 µm, 3 µm, 8 µm and 15 µm). The species were selected from the Xylarium of the Royal Museum for Central Africa, Belgium, and represent a wide variety of wood-anatomical features.</p><p><strong>Results: </strong>For each resolution, we determined which standardized anatomical features can be distinguished or measured, using the anatomical descriptions and microscopic photographs on the Inside Wood Online Database as a reference. We show that small-scale features (e.g. pits and fibres) can be best distinguished at high resolution (especially 1 µm voxel size). In contrast, large-scale features (e.g. vessel porosity or arrangement) can be best observed at low resolution due to a larger field of view. Intermediate resolutions are optimal (especially 3 µm voxel size), allowing recognition of most small- and large-scale features. While the potential for wood identification is thus highest at 3 µm, the scans at 1 µm and 8 µm were successful in more than half of the studied cases, and even the 15 µm resolution showed a high potential for 40% of the samples.</p><p><strong>Conclusions: </strong>The results show the potential of X-ray µCT for non-destructive wood identification. Each of the four studied resolutions proved to contain information on the anatomical features and has the potential to lead to an identification. The dataset of 17 scanned species is made available online and serves as the first step towards a reference database of scanned wood species, facilitating and encouraging more systematic use of X-ray µCT for the identification of wood species.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"98"},"PeriodicalIF":4.7,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11194899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141446724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining the fractional order derivative and machine learning for leaf water content estimation of spring wheat using hyper-spectral indices.","authors":"Zinhar Zununjan, Mardan Aghabey Turghan, Mutallip Sattar, Nijat Kasim, Bilal Emin, Abdugheni Abliz","doi":"10.1186/s13007-024-01224-0","DOIUrl":"10.1186/s13007-024-01224-0","url":null,"abstract":"<p><p>Leaf water content (LWC) is a vital indicator of crop growth and development. While visible and near-infrared (VIS-NIR) spectroscopy makes it possible to estimate crop leaf moisture, spectral preprocessing and multiband spectral indices have important significance in the quantitative analysis of LWC. In this work, the fractional order derivative (FOD) was used for leaf spectral processing, and multiband spectral indices were constructed based on the band-optimization algorithm. Eventually, an integrated index, namely, the multiband spectral index (MBSI) and moisture index (MI), is proposed to estimate the LWC in spring wheat around Fu-Kang City, Xinjiang, China. The MBSIs for LWC were calculated from two types of spectral data: raw reflectance (RR) and the spectrum based on FOD. The LWC was estimated by combining machine learning (K-nearest neighbor, KNN; support vector machine, SVM; and artificial neural network, ANN). The results showed that the fractional derivative pretreatment of spectral data enhances the implied information of the spectrum (the maximum correlation coefficient appeared using a 0.8-order differential) and increases the number of sensitive bands, especially in the near-infrared bands (700-1100 nm). The correlations between LWC and the two-band index (RVI_{1156, 1628 nm}), three-band indices (3BI-3_{(766, 478, 1042 nm)}, 3BI-4_{(1129, 1175, 471 nm)}, 3BI-5_{(814, 929, 525 nm)}, 3BI-6_{(1156, 1214, 802 nm)}, 3BI-7_{(929, 851, 446 nm)}) based on FOD were higher than that of moisture indices and single-band spectrum, with r of - 0.71**, 0.74**, 0.73**, - 0.72**, 0.75** and - 0.76** for the correlation. The prediction accuracy of the two-band spectral indices (DVI_{(698, 1274 nm)} DVI_{(698, 1274 nm)} DVI_{(698, 1274 nm)}) was higher than that of the moisture spectral index, with R² of 0.81 and R² of 0.79 for the calibration and validation, respectively. Due to a large amount of spectral indices, the correlation coefficient method was used to select the characteristic spectral index from full three-band indices. Among twenty seven models, the FWBI-3BI_{- 0.8 order} model performed the best predictive ability (with an R² of 0.86, RMSE of 2.11%, and RPD of 2.65). These findings confirm that combining spectral index optimization with machine learning is a highly effective method for inverting the leaf water content in spring wheat.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"97"},"PeriodicalIF":4.7,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11193302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141440789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field cabbage detection and positioning system based on improved YOLOv8n.","authors":"Ping Jiang, Aolin Qi, Jiao Zhong, Yahui Luo, Wenwu Hu, Yixin Shi, Tianyu Liu","doi":"10.1186/s13007-024-01226-y","DOIUrl":"10.1186/s13007-024-01226-y","url":null,"abstract":"<p><strong>Background: </strong>Pesticide efficacy directly affects crop yield and quality, making targeted spraying a more environmentally friendly and effective method of pesticide application. Common targeted cabbage spraying methods often involve object detection networks. However, complex natural and lighting conditions pose challenges in the accurate detection and positioning of cabbage.</p><p><strong>Results: </strong>In this study, a cabbage detection algorithm based on the YOLOv8n neural network (YOLOv8-cabbage) combined with a positioning system constructed using a Realsense depth camera is proposed. Initially, four of the currently available high-performance object detection models were compared, and YOLOv8n was selected as the transfer learning model for field cabbage detection. Data augmentation and expansion methods were applied to extensively train the model, a large kernel convolution method was proposed to improve the bottleneck section, the Swin transformer module was combined with the convolutional neural network (CNN) to expand the perceptual field of feature extraction and improve edge detection effectiveness, and a nonlocal attention mechanism was added to enhance feature extraction. Ablation experiments were conducted on the same dataset under the same experimental conditions, and the improved model increased the mean average precision (mAP) from 88.8% to 93.9%. Subsequently, depth maps and colour maps were aligned pixelwise to obtain the three-dimensional coordinates of the cabbages via coordinate system conversion. The positioning error of the three-dimensional coordinate cabbage identification and positioning system was (11.2 mm, 10.225 mm, 25.3 mm), which meets the usage requirements.</p><p><strong>Conclusions: </strong>We have achieved accurate cabbage positioning. The object detection system proposed here can detect cabbage in real time in complex field environments, providing technical support for targeted spraying applications and positioning.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"96"},"PeriodicalIF":4.7,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11188521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141432545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping and quantifying unique branching structures in lentil (Lens culinaris Medik.).","authors":"Adam M Dimech, Sukhjiwan Kaur, Edmond J Breen","doi":"10.1186/s13007-024-01223-1","DOIUrl":"10.1186/s13007-024-01223-1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Lentil (Lens culinaris Medik.) is a globally-significant agricultural crop used to feed millions of people. Lentils have been cultivated in the Australian states of Victoria and South Australia for several decades, but efforts are now being made to expand their cultivation into Western Australia and New South Wales. Plant architecture plays a pivotal role in adaptation, leading to improved and stable yields especially in new expansion regions. Image-based high-throughput phenomics technologies provide opportunities for an improved understanding of plant development, architecture, and trait genetics. This paper describes a novel method for mapping and quantifying individual branch structures on immature glasshouse-grown lentil plants grown using a LemnaTec Scanalyser 3D high-throughput phenomics platform, which collected side-view RGB images at regular intervals under controlled photographic conditions throughout the experiment. A queue and distance-based algorithm that analysed morphological skeletons generated from images of lentil plants was developed in Python. This code was incorporated into an image analysis pipeline using open-source software (PlantCV) to measure the number, angle, and length of individual branches on lentil plants.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Branching structures could be accurately identified and quantified in immature plants, which is sufficient for calculating early vigour traits, however the accuracy declined as the plants matured. Absolute accuracy for branch counts was 77.9% for plants at 22 days after sowing (DAS), 57.9% at 29 DAS and 51.9% at 36 DAS. Allowing for an error of ± 1 branch, the associated accuracies for the same time periods were 97.6%, 90.8% and 79.2% respectively. Occlusion in more mature plants made the mapping of branches less accurate, but the information collected could still be useful for trait estimation. For branch length calculations, the amount of variance explained by linear mixed-effects models was 82% for geodesic length and 87% for Euclidean branch lengths. Within these models, both the mean geodesic and Euclidean distance measurements of branches were found to be significantly affected by genotype, DAS and their interaction. Two informative metrices were derived from the calculations of branch angle; 'splay' is a measure of how far a branch angle deviates from being fully upright whilst 'angle-difference' is the difference between the smallest and largest recorded branch angle on each plant. The amount of variance explained by linear mixed-effects models was 38% for splay and 50% for angle difference. These lower R&lt;sup&gt;2&lt;/sup&gt; values are likely due to the inherent difficulties in measuring these parameters, nevertheless both splay and angle difference were found to be significantly affected by cultivar, DAS and their interaction. When 276 diverse lentil genotypes with varying degrees of salt tolerance were grown in a glasshouse-based experiment where ","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"95"},"PeriodicalIF":4.7,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11188192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141427418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-cost and reliable substrate-based phenotyping platform for screening salt tolerance of cutting propagation-dependent grass, paspalum vaginatum.","authors":"Zhiwei Liu, Wentao Xue, Qijuan Jiang, Ademola Olufolahan Olaniran, Xiaoxian Zhong","doi":"10.1186/s13007-024-01225-z","DOIUrl":"10.1186/s13007-024-01225-z","url":null,"abstract":"<p><strong>Background: </strong>Salt tolerance in plants is defined as their ability to grow and complete their life cycle under saline conditions. Staple crops have limited salt tolerance, but forage grass can survive in large unexploited saline areas of costal or desert land. However, due to the restriction of self-incompatible fertilization in many grass species, vegetative propagation via stem cuttings is the dominant practice; this is incompatible with current methodologies of salt-tolerance phenotyping, which have been developed for germination-based seedling growth. Therefore, the performance of seedlings from cuttings under salt stress is still fuzzy. Moreover, the morphological traits involved in salt tolerance are still mostly unknown, especially under experimental conditions with varying levels of stress.</p><p><strong>Results: </strong>To estimate the salt tolerance of cutting propagation-dependent grasses, a reliable and low-cost workflow was established with multiple saline treatments, using Paspalum vaginatum as the material and substrate as medium, where cold stratification and selection of stem segments were the two variables used to control for experimental errors. Average leaf number (ALN) was designated as the best criterion for evaluating ion-accumulated salt tolerance. The reliability of ALN was revealed by the consistent results among four P. vaginatum genotypes, and three warm-season (pearl millet, sweet sorghum, and wild maize) and four cold-season (barley, oat, rye, and ryegrass) forage cultivars. Dynamic curves simulated by sigmoidal mathematical models were well-depicted for the calculation of the key parameter, Salt₅₀. The reliability of the integrated platform was further validated by screening 48 additional recombinants, which were previously generated from a self-fertile mutant of P. vaginatum. The genotypes displaying extreme ALN-based Salt₅₀ also exhibited variations in biomass and ion content, which not only confirmed the reliability of our phenotyping platform but also the representativeness of the aerial ALN trait for salt tolerance.</p><p><strong>Conclusions: </strong>Our phenotyping platform is proved to be compatible with estimations in both germination-based and cutting propagation-dependent seedling tolerance under salt stresses. ALN and its derived parameters are prone to overcome the species barriers when comparing salt tolerance of different species together. The accuracy and reliability of the developed phenotyping platform is expected to benefit breeding programs in saline agriculture.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"94"},"PeriodicalIF":4.7,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11186238/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141427417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven crop growth simulation on time-varying generated images using multi-conditional generative adversarial networks.","authors":"Lukas Drees, Dereje T Demie, Madhuri R Paul, Johannes Leonhardt, Sabine J Seidel, Thomas F Döring, Ribana Roscher","doi":"10.1186/s13007-024-01205-3","DOIUrl":"10.1186/s13007-024-01205-3","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. While image-based models provide more flexibility for crop growth modeling than process-based models, there is still a significant research gap in the comprehensive integration of various growth-influencing conditions. Further exploration and investigation are needed to address this gap.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We present a two-stage framework consisting first of an image generation model and second of a growth estimation model, independently trained. The image generation model is a conditional Wasserstein generative adversarial network (CWGAN). In the generator of this model, conditional batch normalization (CBN) is used to integrate conditions of different types along with the input image. This allows the model to generate time-varying artificial images dependent on multiple influencing factors. These images are used by the second part of the framework for plant phenotyping by deriving plant-specific traits and comparing them with those of non-artificial (real) reference images. In addition, image quality is evaluated using multi-scale structural similarity (MS-SSIM), learned perceptual image patch similarity (LPIPS), and Fréchet inception distance (FID). During inference, the framework allows image generation for any combination of conditions used in training; we call this generation data-driven crop growth simulation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Experiments are performed on three datasets of different complexity. These datasets include the laboratory plant Arabidopsis thaliana (Arabidopsis) and crops grown under real field conditions, namely cauliflower (GrowliFlower) and crop mixtures consisting of faba bean and spring wheat (MixedCrop). In all cases, the framework allows realistic, sharp image generations with a slight loss of quality from short-term to long-term predictions. For MixedCrop grown under varying treatments (different cultivars, sowing densities), the results show that adding these treatment information increases the generation quality and phenotyping accuracy measured by the estimated biomass. Simulations of varying growth-influencing conditions performed with the trained framework provide valuable insights into how such factors relate to crop appearances, which is particularly useful in complex, less explored crop mixture systems. Further results show that adding process-based simulated biomass as a condition increases the accuracy of the derived phenotypic traits from the predi","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"93"},"PeriodicalIF":5.1,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11179353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141327777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Versatile DNA extraction from diverse plant taxa using ionic liquids and magnetic ionic liquids: a methodological breakthrough for enhanced sample utility.","authors":"Shashini De Silva, Cecilia Cagliero, Morgan R Gostel, Gabriel Johnson, Jared L Anderson","doi":"10.1186/s13007-024-01217-z","DOIUrl":"10.1186/s13007-024-01217-z","url":null,"abstract":"<p><strong>Background: </strong>There is a growing demand for fast and reliable plant biomolecular analyses. DNA extraction is the major bottleneck in plant nucleic acid-based applications especially due to the complexity of tissues in different plant species. Conventional methods for plant cell lysis and DNA extraction typically require extensive sample preparation processes and large quantities of sample and chemicals, elevated temperatures, and multiple sample transfer steps which pose challenges for high throughput applications.</p><p><strong>Results: </strong>In a prior investigation, an ionic liquid (IL)-based modified vortex-assisted matrix solid phase dispersion approach was developed using the model plant, Arabidopsis thaliana (L.) Heynh. Building upon this foundational study, the present study established a simple, rapid and efficient protocol for DNA extraction from milligram fragments of plant tissue representing a diverse range of taxa from the plant Tree of Life including 13 dicots and 4 monocots. Notably, the approach was successful in extracting DNA from a century old herbarium sample. The isolated DNA was of sufficient quality and quantity for sensitive molecular analyses such as qPCR. Two plant DNA barcoding markers, the plastid rbcL and nuclear ribosomal internal transcribed spacer (nrITS) regions were selected for DNA amplification and Sanger sequencing was conducted on PCR products of a representative dicot and monocot species. Successful qPCR amplification of the extracted DNA up to 3 weeks demonstrated that the DNA extracted using this approach remains stable at room temperature for an extended time period prior to downstream analysis.</p><p><strong>Conclusions: </strong>The method presented here is a rapid and simple approach enabling cell lysis and DNA extraction from 1.5 mg of plant tissue across a broad range of plant taxa. Additional purification prior to DNA amplification is not required due to the compatibility of the extraction solvents with qPCR. The method has tremendous potential for applications in plant biology that require DNA, including barcoding methods for agriculture, conservation, ecology, evolution, and forensics.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"91"},"PeriodicalIF":5.1,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177442/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141321378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Publisher Correction: New improvements in grapevine genome editing: high efficiency biallelic homozygous knock-out from regenerated plantlets by using an optimized zCas9i.","authors":"Jérémy Villette, Fatma Lecourieux, Eliot Bastiancig, Marie-Claire Héloir, Benoit Poinssot","doi":"10.1186/s13007-024-01204-4","DOIUrl":"10.1186/s13007-024-01204-4","url":null,"abstract":"","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"92"},"PeriodicalIF":5.1,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11177437/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141321377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}